Abstract
The integration of renewable energy sources within the energy transition is associated with major difficulties due to their often hard-to-predict production pattern. Consequently, stakeholders are challenged to balance the energy within the energy systems to avoid severe consequences for grid stability. Energy literature holds the view that flexibility is a key concept to deal with this challenge. Flexibility can be created via different sources as demand and supply side management or storage. The integration of residential parties holding such flexibility sources, for instance home storage systems or electrical vehicles, provides enormous potential in increasing the needed flexibility in the energy market. Yet, literature analyses the flexibility creation of residential flexibility suppliers predominantly from a technical angle of vision while neglecting the business or comfort behaviours of the relevant actors involved. Therefore, a multiple case study was conducted to obtain empirical information to create insights on the key actors and their constraints influencing the flexibility creation and provision process. The results reveal three main actors, namely the aggregator who is in charge of collecting flexibility opportunities and subsequently offering them on the market, the flexibility asset owner and the flexibility asset user. The constraints find their origin in technical, comfort, financial and market dimensions. It was found that all four perspectives can influence the flexibility creation process, especially comfort and market constraints were identified to significantly limit the final flexibility provision. Based on these findings, this thesis provides suggestions on optimisation approaches. Results indicate that original equipment manufacturers should integrate the technical requirements in their flexibility assets to enable a smooth flexibility provision. Furthermore, adjustments in the current market structures and legislations can significantly help to increase the flexibility provision by residential flexibility suppliers.
Key words: Flexibility, Renewable energy systems, Residential flexibility suppliers, Flexibility services, Flexibility creation
Preface
1. Introduction
The market share of renewable energy sources (RES) is constantly increasing. Challenges like the climate change, the unsolved question of the nuclear repository and the finite nature of fossil fuels are only a few reasons to explain this development (Huber et al., 2014; Alizadeh et al., 2014). Hence, the integration of carbon friendly electricity sources as solar panels and wind turbines is a task of particular interest (Pavić et al., 2015). However, the integration of RES is associated with difficulties as they often miss predictable production times due to environmental conditions, which can lead to severe consequences for grid stability (Carreiro et al., 2017; Biegel et al., 2014). Within traditional power systems, generating plants on coal and gas basis are able to provide support against fluctuations in demand and supply of energy. The shared view among experts imply that flexibility is a key instrument to create solutions for the aforementioned problem (Hurtado et al., 2017; Verzijlbergh et al., 2017).
Flexibility in energy systems can be described as the ability of a power system to respond to variability and uncertainty in both production and consumption to maintain a satisfactory level of reliability at a reasonable cost, over different time horizons (Ma et al., 2013). To create flexibility in energy systems, different flexibility sources are discussed in literature, namely demand and supply side management, energy storage or conversion (Huber et al., 2014; Lund et al., 2015). Parties owning flexibility, for instance owner of electrical vehicles (EVs) or home storage systems, are often decentralized distributed and need markets to offer and trade their flexibility. Hence, ‘flexibility services’ emerge, where parties collect, manage and subsequently offer flexibility to parties which are confronted with difficulties arising from RES (Eid et al., 2016; Van der Burg et al., 2018).
This master thesis aims to shed light on the flexibility creation process of residential flexibility suppliers (RFS) and the way it is influenced by the interaction between actor(s) and the flexibility device(s). Comfort constraints (e.g. provision of flexibility only in specific timeframes), business constraints (e.g. price sensitivity) and technical constraints (e.g. capacity of storage system) can influence the final flexibility creation in considerable amount. Further, factors as property rights (e.g. ownership of the flexibility device) might also affect the flexibility creation since many flexibility devices like EVs or storage systems are rented or leased (Carley et al., 2013). Insufficient provision of flexibility services can result in grid instability and (financial) penalties for the parties offering flexibility services and the flexibility supplier. Therefore, parties collecting flexibility, and subsequently managing and offering flexibility services need precise and reliable information on the flexibility provision to integrate and manage the flexibility suppliers effectively and efficiently in their supply chain in order to provide reliable and economical flexibility services on the market. This master thesis contributes to energy literature by providing insights on the flexibility creation process of residential flexibility suppliers and how it is affected by above mentioned influence factors. Therefore, the following research questions will be addressed: 1. What relevant actors are involved in the flexibility creation of RFS? 2. What constraints are influencing the flexibility creation of RFS? 3. How can the flexibility creation of RFS be optimized? First, a literature review about the changing energy system and their stakeholders will be presented. Secondly, the term flexibility and its definition in energy literature will be discussed. Additionally, different sources of flexibility and how RFS are described in energy literature will be analysed. Subsequently, an empirical case study with multiple cases was conducted in order to get practical insights on the creation of flexibility by RFS and their associated constraints limiting the flexibility provision. By answering the aforementioned research questions, this thesis will contribute practical insights to energy literature, which can help to maximize the flexibility creation by RFS and optimize
2. Theoretical background
This section provides general information about the energy market and current changes within the energy system. Secondly, the term flexibility is defined and specified. The last section analyses how RFS and their flexibility creation are discussed in literature.
2.1 The changing energy market and new actors/services
portfolio of services and finally offer flexibility services on the market (Van der Burg et al., 2018). These parties are named ‘flexibility aggregators’. The consumers of flexibility services are the system operators, energy producers or retailers and other balancing responsible parties. Figure 1 provides an overview about the new roles and key actors in flexibility service systems, namely the ‘flexibility supplier’, the ‘flexibility aggregator’ and the ‘flexibility consumer’. It needs to be pointed out that the actual physical energy flow is not in line with the flow of flexibility (services). Figure 1: Flexibility service system in the supply chain (Van der Burg et al., 2018)
2.2 The concept of flexibility in energy systems
The concept of flexibility in energy systems is divided into ‘structural flexibility’ (Lannoye et al., 2012) and ‘operational flexibility’ (Ulbig and Andersson, 2015). When flexibility in energy system is discussed in a service perspective, energy literature refers to ‘operational flexibility’, which is defined as the technical ability of a power system to manage and control flexibility devices in order to react accordingly to changes in electricity demand and generation (Ulbig and Andersson, 2015). Structural flexibility is related to the technical ability of energy systems to provide flexibility, e.g. investments in flexibility assets enabling the flexibility provision (Lannoye et al., 2012).2.2.1 Specific characteristics of operational flexibility
with more focus on flexibility services is provided by Eid et al. (2016). They describe operational flexibility as a power adjustment sustained at a given moment for a given duration from a specific location within the network. Furthermore, they argue flexibility services can be allocated and characterized by five characteristics: the direction (a); its electrical composition in power (b); its temporal characteristics defined by its starting time
(c) and duration (d) and its base for location (e). Figure 2 illustrates the attributes of an electric flexibility service except for the attribute location. To summarise, the attributes of operational flexibility are differently described in literature with different foci.
2.2.2 Define flexibility as a ‘tradable good’ (flex-package)
In order to specify flexibility as a tradable and measurable good, Van der Burg et al. (2018) propose to define the flexibility provision of flexibility suppliers as discrete ‘packages’. These flex-packages can be specified by the following flexibility characteristics:
1. Flexibility form: Infeed or Outfeed flexibility
2. Physical features: Power provision capability (kW), Ramp-rate capability (kW/h), Energy provision capability (kWh) 3. Available time: Start time and End time availability 4. Location: The physical location in the grid The flexibility provision of flexibility suppliers can be characterized and precisely described by these four attributes.
2.2.3 Flexibility sources
Demand side flexibility (DSF) builds upon the assumption that the energy demand pattern can be influenced. Lund et al. (2015) argue that DSF involves a brought set of means to affect the patterns and magnitude of end-user electricity consumption. DSF can be clustered into three categories (Lund et al, 2015). A reduction of demand can be achieved by peak shaving or conservation (option 1) whereas increasing demand is obtained by valley filling or load growth (option 2). The third option is rescheduling the energy demand, e.g. via load shifting. DSF has many benefits in normal as well as emergency conditions (e.g. grid congestion or shortage) and can provide cost reduction and grid stability (Sajjad et al., 2014). DSF is commonly realized through smart devices which are able to adjust energy demand in line with predefined attributes, e.g. start a washing machine or dish washer according to real-time energy prices (Palensky and Dietrich, 2011). Supply side flexibility (SSF) is realized with measures or technologies through which the output of power generation units can be adjusted to attain the power balance in the grid (Lund et al., 2015). The ability to provide SSF flexibility relies heavily on system characteristics. Accordingly, Lund et al. (2015) divide power plants in three categories: base load, peaking and load following. Whereas base load plants (e.g. nuclear or coal) run usually at consistent level providing a constant amount of energy, load following and peaking power plants (e.g. gas or hydropower) are used irregularly depending on the demand. SSF provided by RFS is commonly realized with stationary battery storages or EVs. Although a single flexibility asset of a RFS cannot provide the capacity to significantly balance the base load of a grid, the accumulation of a large number can offer a sufficient capacity to balance short-time peaks).
Conversion differs from storage technologies, although they are closely related. RE converted into thermal, gas or hydrogen is later used in that converted form. Whereas in storage systems, the RE is converted e.g. into chemical energy but is later needed in the form of electricity and need to be converted back. The technique of electricity conversion into hydrogen, gas or thermal energy is mainly applied in cases of oversupply of RE and if the energy can be used in the converted form for cooling, heating or other purposes (Lund et al., 2015). Conversion is often associated with energy losses due to a low efficiency rate (Lund et al., 2015). Compared to DSF, SSF and storage, conversion plays only a marginal role for RFS.
2.3 Flexibility of a residential flexibility supplier
On grounds of the changing energy market, new active parties as residential households can be observed. New technologies and decreasing prices of smart assets motivate smaller parties to play an active role in the energy system. Additionally, a new sense of awareness in lowering or even eliminating the negative environmental impact of energy production and consumption is promoting this development (Couture et al., 2014). Beside active consumers, mostly providing DSF, prosumers are playing an increasingly important role in modern energy systems due to their ability to provide energy to the market (Lampropoulos et al., 2010). Because of the large number of residential parties, vast potential is seen in integrating them into the energy system (Parag and Sovacool, 2016; Couture et al., 2014).
A basic framework of a flexibility supplier is provided in figure 3. A perfect forecast of the flexibility provision of flexibility suppliers can be described as the perfect condition for aggregators. Beside the technological characteristics of the used devices, which usually can be reliably defined and predicted, the actor or owner of the flexibility
device is also involved in the final flexibility provision (Van der Berg et al., 2018). Comfort constraints of the actor/owner (e.g. when to use the washing machine or dishwasher, use of EV) or economic constraints (price sensitivity) are influencing the flexibility creation as well. Energy literature is offering many papers focusing on the technical devices. Fischer et al. (2016) and Nuytten et al. (2013) investigated the flexibility potential of heat pumps and develop models on how to optimize the flexibility provision. Marra et al. (2011) and Al-Awami and Sortomme (2012) analysed the potential of EVs when connected to the grid (V2G) and develop algorithms for the optimal usage. Heat pumps as well as V2G demonstrate numerous advantages as lower charging costs, reduced local grid congestion and shortages.
A rather behaviour-based approach is to investigate the price sensitivity of flexibility suppliers. Hu et al. (2015) investigated the responsive residential demand to financial incentives. They present a stochastic model based on the residents’ portfolios to analyse responsive residential demand in response to a specific time, location and financial incentive. A stochastic model is used because it is rarely feasible to keep frequently updating customers’ demand reduction data and interact with numerous customers which makes it too time-consuming to serve as an online implementation. Their results clearly indicate that the higher the incentive is the more likely they are willing to adjust their load. A study by Thimmapuram and Kim (2013) analyses the consumers’ behaviour in smart grid environments, demonstrating that price-elastic consumers could benefit by smart energy load management and furthermore are able to reduce congestion in local grid areas. To sum up, flexibility suppliers adapt their flexibility provision according to economic incentives depending on their individual load capacity and price sensitivity. Yet, measuring price elasticity is a complex task, and estimated elasticity coefficients usually have a wide range of uncertainty attached to them (Thimmapuram and Kim, 2013).
Another approach is to model the flexibility potential of RFS independently of the underlying demand response scheme and subsequently use the data to assess the potential flexibility provision for flexibility services. The analysis of the utilization patterns based on device usage provides insights about the potential amount of deferrable load (Sadeghianpourhamami et al., 2016). Laicane et al. (2015) conducted a time-of-use survey and investigated the usage pattern of a washing machine and dishwasher to obtain data of customers’ behaviour pattern with the result of reducing the peak load of a dwelling on average by 24 % and 13.5 %, respectively. Kouzelis et al. (2015) and Labeeuw et al. (2015) are using the technique of clustering the load profiles of flexibility suppliers to use these ‘packages’ for flexibility services on the market.
be considered. Secondly, the answer of the second research question will provide a better understanding of the creation process of flexibility and their various constraints. These constraints can be related to the structural flexibility, e.g. investments needed in infrastructure, or to operational flexibility affecting the four characteristics of flexibility. Beside financial and technical constraints, as often discussed in literature, other constraints relating to the comfort needs of RSF or market regulations can affect the flexibility considerably. These insights can help to activate potential flexibility suppliers, optimize their flexibility provision and subsequently contribute to a well-working energy system, which will be elaborated in the third research question. Although it seems that a single RFS cannot offer vast amount of flexibility, the activation of large numbers of RFS and their flexibility potential can contribute on a notable level to the decarbonisation of the energy system.
3. Methodology
This section elaborates on the applied methodologies of this thesis. The main character of this research is explorative and accordingly uses a qualitative approach to collect and analyse data. Hence, the selected method is a multiple case study. Firstly, the research approach of a case study is explained followed by the corresponding phases of this research. Subsequently, the methodological steps, the selected cases, data collection and analysis are presented.
3.1 Case study research
Case research has been one of the most powerful and applied research methods, especially in the development of new theory (Boer et al., 2015). Case research uses case studies as its basis. Meredith et al. (1998) list three particular strengths of a case research. Firstly, the phenomenon can be studied in his natural setting and meaningful, relevant theory can be generated from the understanding obtained through the observation of actual practice. Since the research question addresses a wide scope, studying RFS within their environment might provide new insights in the process of flexibility creation. Secondly, why, what and how questions can be answered with a relatively full understanding of the nature and complexity of the entire phenomenon, which fits well with the research questions of this thesis. Lastly, the case method can be used for early, exploratory investigations when the variables are still unknown and the investigated phenomenon is not (fully) understood (Karlsson, 2016). A lack of previous studies, investigating the flexibility creation and the associated constraints, supports the choice of a case study for theory building.3.2 Case selection
The unit of analysis for this study are RFS. During the selection process of the cases, it became apparent that not only RFS are valuable sources of knowledge. Additionally, parties aggregating the flexibility opportunities and companies offering hard- and software products which enable the flexibility provision have valuable information about RFS and their flexibility creation as well. Hence, beside RFS, other parties specialized to aggregate and integrate RFS in the energy system were interviewed to obtain more insights. Furthermore, by selecting multiple different cases, a cross-case analysis can be performed in order to verify the replicability of the obtained data and as a consequence the external validity of the findings. Additionally, by investigating different parties in the flexibility service system, a triangulation of data is achieved (Karlsson, 2016; Yin, 2013). Table 1 provides an overview of the chosen cases.
Role in the flexibility service system Role/position of interviewee
Case A Aggregator of RFS with EVs Business Development Manager
Utilities Case B Aggregator and software provider for RFS
with stationary batteries and EVs Account and Project Manager Case C Aggregator and hard- and software
provider for RFS with stationary batteries and EVs
Managing Director
Case D Flexibility supplier with PV, storage and EV Actor and Owner Case E Flexibility Supplier with PV and EV Actor and Owner
Table 1: Overview of the selected cases
3.3 Scope
3.6 Validity and reliability
In case research, it is particularly important to pay attention to reliability and validity (Karlsson, 2016). Construct validity is the extent to which correct measures are established for the concepts being investigated (Karlsson, 2016). The internal validity describes the extent to which a causal relationship can be drawn by revealing why certain conditions lead to other conditions (Yin, 2013). External validity is to ensure that the findings can be generalized beyond the conducted case study (Karlsson, 2016). Lastly, the reliability ensures that the study can be repeated with the same results (Yin, 2013). The following table 2 provides an overview and summarises how validity and reliability are ensured.
Goal Case study tactic Phase of research
4. Results
This section presents the insights obtained from the cases. According to the research questions, this section is divided into two basic parts per case. The first part presents insights what actors are involved in the flexibility creation and provision and their role in the system. The next section analyses the constraints linked with the flexibility creation.
4.1 Case A
In case A, the flexibility is created with smart charging of EVs. EVs can provide a flexibility capacity between 20 and 100 kWh, with a power provision capability (on average) of 11 kW, both depending on the technical features of the EV and the charging station.
this information manually. Besides the provision of data, the OEM is an important actor from a marketing perspective, because ‘he already has a customer relationship and we want them to promote our service [during the sale process].’ Another actor which can be involved are public charging station operators by providing control over the charging process to the aggregator. In case the RFS charges the car at a private charging station, this actor is not involved.
4.1.2 Constraints which influence the flexibility creation
Technical constraints: The main technical constraints are related to the physical features of the battery of the EV, mainly the capacity (kWh). Aggregator A argues he ‘would not recommend smart charging for very small batteries’. The available time and capacity (kWh) for providing flexibility is rather limited with small batteries and ‘especially during winter people are more likely to want direct charging because of the lower battery capacity.’ Additionally, batteries require a converter to be able to provide infeed flexibility thus affecting the flexibility form. ‘The batteries are DC, the grid is AC and subsequently a converter is needed.’ Furthermore, if you provide infeed flexibility ‘you lose a bit of energy’ due to the conversion process which can lead to a lower flexibility capacity (kWh). Another aspect is that ’there can be constraints on the battery cycle side’. Batteries have a limited amount of charging cycles and subsequently the flexibility provision can lower the lifespan of a battery significantly. Accordingly, the deterioration needs to be financially compensated. Another constraint relating to needed infrastructure is the limited amount of smart meters on the market, ‘e.g. in Germany, they have very high demand in smart meters [demand in terms of regulations to measure and invoice the provided flexibility] but they are not well deployed.’
when second hand EVs will enter the market. As a result, ‘less wealthy customers will drive an EV not due to sustainability reasons but more because it’s the cheapest option and then I expect more price sensitivity […]. Financial constraints are also affecting the flexibility form because ‘to provide infeed flexibility [beside outfeed flexibility] you need specialized and costly equipment’.
Market constraints: Restrictions by the government often have a negative impact on the creation of flexibility. ‘There are quite some rules in the energy market and you are often not allowed to sell flexibility if you don’t have an arrangement with the energy supplier. Additionally, there are many rules concerning metering data in order to be allowed to participate in the energy market so using data from charging stations or cars is often not allowed to use in regular energy market processes’. To provide flexibility, there needs to be a market for flexibility services. The markets for flexibility services are often not standardized and are missing a general framework. Especially the different TSOs and DSOs are often not working together and ‘tend to come up with their own ideas which are often not in line with structures and ideas which are already there. […] For us it is impossible to create services and solutions for every DSO […]. So the DSOs working together with the TSOs and maybe even other countries would really help.’ To sum up, market constraints are often limiting the general possibility to provide flexibility.
Category Constraint Influence on flexibility
Technical Capacity of battery Conversion loss of battery Temperature sensitivity of battery Charging station Capacity (kWh) Capacity (kWh) Capacity (kWh) Power provision (kW)
Authorized smart meter Needed to measure and invoice the provided flexibility
Converter Needed to provide infeed flexibility
Comfort Demand for mobility of driver Available time (h) and capacity (kWh) Range anxiety of driver Available time (h) and capacity (kWh) Financial Low market prices for flexibility General willingness to provide flexibility
Low price sensitivity of RFS General willingness to provide flexibility
Market Rules at energy market Create products which enable RFS to provide flexibility
Data metering Metering of provided flexibility is often costly and complicated
General flexibility market framework missing
Create products which enable RFS to provide flexibility
4.2 Case B
In case B, flexibility is provided by smart charging of EVs and by smart energy management of stationary batteries. Aggregator B is providing a platform which offers all of the functions required to enable RFS to provide their
flexibility information (available time and capacity (kWh)) to the aggregator B. According to the flexibility information, aggregator B is controlling the flexibility asset. The flexibility is sold by the aggregator B at the frequency containment reserved market (FCR). At the FCR market, parties are not selling purely electricity (kWh) anymore, instead you have to provide your flexibility asset for one week. Additionally, the flexibility is used to profit from energy price fluctuations at the imbalance market. The profit is then shared between the RFS and aggregator B.
4.2.1 Relevant actors involved in the flexibility creation
In case B, the flexibility asset user is in charge to provide the flexibility information to aggregator B (available time and capacity (kWh)). The aggregator B will then take care of the “activation” and “deactivation” of the flexibility asset. According to aggregator B, ‘if flexibility suppliers have to do something manually to provide flexibility, that won’t work.’ If the flexibility asset user is not the owner, the owner has to authorize the usage for flexibility creation beforehand and can subsequently influence the flexibility on an operational level (e.g. capacity (kWh) or flexibility form).
4.2.2 Constraints which influence the flexibility creation
Technical constraints: To provide flexibility services on the FCR market, it is mandatory to ‘provide at least 1 MW per location for 1 week and it’s really difficult to build flexibility products for small flexibility assets’. Only a large number of accumulated batteries from many RFS can provide such flexibility attributes. But even batteries are not always suitable for flexibility services on the FCR market because ‘it is a continuous process, every second you need to do something. And not every battery is technical suitable for that specific service.’ Another issue is that often a software is needed to control the flexibility asset. ‘E.g. Tesla is not allowing to put additional software in the car or discharge the battery in a different way because they offer a guarantee on the car.’ A similar problem appeared when aggregator B tried to integrate cooling houses in their flexibility portfolio (‘every client computer is different and needs a “customized” service). Hence, results from case B indicates that for RFS the flexibility creation is often affected and limited on a structural perspective which subsequently impacts the flexibility on an operational level.
Comfort constraints: Generally, aggregator 2 argues that ‘preferably everything needs to be automated’ if RFS are providing flexibility. ‘If you don’t do it that way, it won’t work. Because people come from a situation where they only buy electricity. […] They think like it as a project so what is the investment and how long will it take me to get everything running […] on a daily basis. And if we say 15 minutes or more, there is no way that they going to do it.’ Again, aggregator B emphasises the importance for RFS of having appropriate structural preconditions (high automation) for optimal flexibility creation and provision. Financial constraints: A main problem are the low market prices for flexibility. ‘Prices for flexibility services dropped since 2016 but the prices for batteries stayed high. […] E.g. on the FCR market you got per week and per MW 2,500 €. And that is for a car, which has maximum 100 kWh and you can calculate with maybe 5% of that capacity for flexibility, and together with the high cost for hard- and software, that’s a very difficult business case’. For smaller flexibility suppliers ‘the incentive will be small, and that is the biggest problem’. Market constraints: The requirement of the FCR market to provide the flexibility service for 1 week can make it very difficult for RFS to provide flexibility. But ‘this will probably change in the future that 1 hour contracts will also be available’. The Development of new flexibility opportunities for RFS is also very complicated. E.g., Aggregator 2 developed together with TenneT (TSO who is owned by the government) a pilot project and suddenly ‘they said sorry we can’t continue at the moment because we need to make it public […].’ Another hurdle is the aggravating circumstance that every TSO in Europe is different and are pursuing different projects. ‘Then you have a meeting with 20 people and
hear 20 different stories and ideas so it’s difficult […].’
Category Constraint Influence on flexibility
Technical Capacity of battery Charging cycles Power provision capability of battery Capacity (kWh) Affecting capacity on the long term (kWh) Ramp-up/ramp-down rate (kW/h) Control equipment of flexibility asset Activation and deactivation of flexibility provision Comfort Effort to provide flexibility General willingness to provide flexibility
Financial Low market prices for flexibility General willingness to provide flexibility
Market Guarantee OEMs (e.g. Tesla) do not allow to use the battery for
every flexibility service
Rules at FCR market Create products which enable RFS to provide flexibility
4.3 Case C
In case C, flexibility is created with smart charging of EVs and smart energy management of stationary batteries of RFS. Company C offers services related to electric vehicles, charging infrastructure, access to public charging stations and
other services to RFS. Beside the integration of EVs into the grid, company C is offering RFS to help to use their battery of the EV as a stationary storage when they are not suitable anymore for the usage in the EV but still usable as a stationary storage. Together with a big energy trading partner, they founded a joint venture (aggregator C) to offer flexibility on the market. The interview was conducted with the managing director of company C.
4.3.1 Relevant actors involved in the flexibility creation
In case C, the flexibility asset user is in charge to provide the flexibility information (available time and capacity (kWh)) to the aggregator C. Company C is focusing on the hard- and software which enables the RFS to provide all relevant flexibility information to aggregator C. Company C wants to make the flexibility creation process as easy as possible for RFS. ‘The customer [RFS] doesn’t want to have a separate app for charging and flexibility information provision. We see that as a task of the car manufactures to integrate such features in their EVs and are in close contact with the OEMs’. In order to create optimal products for RFS, ‘automotive companies, hard- and software developer, energy producers and relevant authorities have to work together and align their ideas’. According to company C this seems to be the hardest part ‘to get all relevant parties like the TSOs, DSOs and OEMs at one table to develop global solutions’.
4.3.2 Constraints which influence the flexibility creation
Technical constraints: The main technical constraints using EVs for flexibility services are, that ‘you need to enable a bidirectional charging process for optimal flexibility provision. Accordingly, you need Wallboxes, DC-charger, converter and an appropriate software and regulations’, thus all relating to structural requirements. Company C rejected direct questions on technical constraints referring to the fact that ‘the real problems are not technical related [they are market related] because the technology is at a very high level and constantly improving’.Comfort constraints: Company C argues that if you want to activate RFS ‘you need to offer them a complete solution in one customer journey or interface which will be integrated by the automotive
manufacturer in their EVs’. Furthermore, he is not convinced that a “green” political and environmental attitude will activate RFS by stating ‘you need to be realistic. If you look at the streets, most of the cars can be assigned to the Golf-class which means most of the people care about the costs. And only with a good financial argument people will connect their EVs reliably to the grid’. The amount of financial incentives is also affecting the willingness of RFS because ‘for 50 € per year the flexibility provision should not make any effort at all’.
Financial constraints: Company C states, that the business case to provide flexibility with storage systems is very hard and ‘at the moment it is not possible to be profitable with flexibility services based on EVs. Only the smart meter, which allows customers to provide infeed flexibility, costs 400 € in Germany. If everything is optimal set up, you only earn maximal 100-150 € per year’. Exact numbers which will affect the willingness of RFS are hard to predict. ‘[...] Customers want to have at least 20% savings. If a customer spends 1000 € on electricity for his EV, for 50 € per year the flexibility provision should not make any effort at all.’ Market constraints: In order to create solutions to enable RFS to provide flexibility, many different parties have to work together. ‘Automotive manufactures are thinking internationally and strive for global solutions but DSOs think more locally and mostly care that everything works in their area. TSOs are thinking at least nationally. Additionally, many committees at federal state and international level are involved.’ In general, the very strict market regulations are limiting the development of new flexibility products for RFS. ‘The energy market is regulated down to the smallest details, the installation meaning all technical and electrical components […]. You cannot test new solutions if the government is not creating scopes for development’.
Category Constraint Influence on flexibility
Technical Enable bidirectional charging
process Needed for optimal flexibility provision (Infeed and outfeed flexibility) Comfort Convenient product/solution Willingness to provide flexibility
Effort to provide flexibility General willingness to provide flexibility Financial Low market prices for flexibility General willingness to provide flexibility
Market Rules at energy market Create products which enable RFS to provide flexibility
Cooperation of OEMs, TSOs,
DSOs and the government Create products which enable RFS to provide flexibility Limitations to test/develop new
flexibility products/solutions
Create products which enable RFS to provide flexibility
4.4 Case D
Case D consists of an RFS (RFS-D) with a 13 kilowatt-peak PV and an energy storage with a capacity of 12 kWh. Additionally, RFS-D has an EV (BMW i3s with 34 kWh battery). He is a member of the energy sharing community from Sonnen
(sonnenCommunity). They can share their home produced surplus energy with other members of the sonnenCommunity. For every kilowatt hour they share, they will receive a financial compensation that is well above the level of compensation offered by regular electricity providers. Further, if they receive electricity from other sonnenCommunity members, they will pay less than the regular market price. The company Sonnen is cooperating with TenneT (TSO). RFS-D is providing a small share of his storage to Sonnen which will only be used a couple of minutes each week to buffer short-term peaks in the power grid. As a financial compensation, RFS-D has access to an electricity flat rate (29,90 € per month for 8,000 kWh/year).
4.4.1 Relevant actors involved in the flexibility creation
The main actor involved for the flexibility provision is the company Sonnen. Confronted with the questions how RFS-D is providing infeed and outfeed flexibility, e.g. according to signals, the answer was ‘I can’t influence that at all. Sonnen has the control of a small share of my energy storage to provide flexibility services’. RFS-D can manually provide electricity to the grid but will only be paid a fixed price independently if the market prices are high or low. Accordingly, ‘it is most profitable if I use the electricity from my PV by myself’. Hence, only a small share of the battery capacity (kWh), which is controlled by Sonnen, is used for flexibility provision.
4.4.2 Constraints which influence the flexibility creation
Technical constraints: One major problem is the capacity of the home storage. ‘Although the battery has a capacity of 12 kWh, it is still too small. On sunny days, the storage is fully charged within 3 hours’. Another problem is that the EV has no converter included to be able to provide infeed flexibility, consequently affecting the flexibility form. Yet, even if the EV would have an integrated converter, RFS-D has not considered to provide infeed flexibility with his EV, stating ‘that was not important for me when I bought my EV. I usually need to drive 200 km per day and accordingly I need the car always fully charged. To provide infeed flexibility, the battery should be at least twice as big’. Again, RFS-D is affected by the available structural preconditions of his flexibility assets (mainly by the capacity (kWh) of the (stationary) battery).Comfort constraints: RFS-D considers the investment decision as the most difficult step. ‘Most people don’t inform themselves about the available possibilities [of flexibility assets]. They want to have it as comfortable as possible and electricity is coming out of the socket without any effort.’ Hence, much potential flexibility is not created since the effort to firstly acquire a flexibility asset and secondly provide flexibility is too high. Financial constraints: RFS-D has considered to use smart charging for his EV ‘but it is financially not interesting for me, although my wall box has the function for flexible charging [DSF], because I always pay the same price for electricity with my flat rate from Sonnen’. Hence, the approach from Sonnen to not compensate their RFS based on the exact amount of provided flexibility but instead provide RFS access to a flat rate can actually limit the provision of flexibility. The price of the home storage is a big constrain as RFS-D argues, ‘I would like to store more energy and provide more in- and outfeed flexibility. But 1 kW costs you 1000 € […]’.
Market constraints: The bureaucracy for RFS in order to provide flexibility should not be underestimated. ‘You have to register at your public authority as a small business owner because you’re making money with your energy. And that comes with much paper work.’ These regulations by the government are aggravating the activation of RFS and accordingly the provision of potential flexibility.
Category Constraint Influence on flexibility
Technical Capacity of battery Capacity (kWh)
Converter Needed to provide infeed flexibility with EV Comfort Information gathering Acquisition of flexibility asset
Financial Price of storage
Market price of flexibility
Acquisition of flexibility asset
General willingness to provide flexibility
Market Bureaucracy Activation of potential RFS and acquisition of flexibility asset
Table 6: Overview constraints - Case D
4.5 Case E
Case E is a RFS (RFS-E) with a PV (15 kW peak) and an EV (Renault Zoe with 41 kWh capacity). RFS-E is using his EV to use as much energy produced from his PV as possible. This is technically realized with his wall box. Additionally, he has a day-night charging tariff from his energy utility and provides flexibility by charging
his car mainly at night. Furthermore, he is using a smart charging provider when he has to charge the car on the road (5% of the time).
4.5.1 Relevant actors involved in the flexibility creation
Financial constraints: A larger battery size would increase the flexibility potential. But the costs for EVs with large batteries are still very high. ‘The Renault Zoe has in my opinion a very good cost-benefit ratio and suffices our needs’. Another financial constraint is that from a cost perspective it is most profitable for RFS to use as much electricity produced by their PVs for private consumption (‘[…]it is financially by far the best option to use the energy for private consumption’). Hence, to provide infeed flexibility, the energy production from the PV should be a lot higher than the consumption and it needs to cover up the costs for storage and/or converter.
Category Constraint Influence on flexibility
Technical Capacity of battery Capacity (kWh)
Converter Needed to provide infeed flexibility Comfort Charge only in specific
time frame
Available time and capacity (kW) Financial Price of EVs with large
battery capacity Acquisition of flexibility asset and capacity (kWh) Market Bureaucracy Activation of potential RFS and acquisition of
flexibility asset(s)
Table 7: Overview constraints - Case E
4.6 Cross-case analysis
In order to verify examined similarities and differences, a cross-case analysis was conducted. The following table represents a comparison of important topics within the different cases.
Case A Case B Case C Case D Case E
Flexibility asset(s) used EV EV and stationary battery storage EV and stationary battery storage Stationary battery storage EV Flexibility
form Outfeed In- and outfeed In- and outfeed In- and outfeed Outfeed
Influence of
location High High High Low High
Actors involved Driver of EV, OEM, Aggregator Driver of EV, Flexibility asset owner, Aggregator Driver of EV, OEM, Aggregator Aggregator, OEM Driver of EV Technical
constraints Battery capacity (kWh), Smart meter, Converter Battery capacity (kWh), Control of flexibility asset, Regulations of OEM Enabling of bidirectional charging process, Converter Battery capacity (kWh), Converter Battery capacity (kWh), Converter Comfort constraints Demand for mobility, Range anxiety Effort to provide flexibility Convenient product/solution, Effort to provide flexibility, range anxiety Investment decision of flexibility asset Effort to provide flexibility, range anxiety Financial
constraints Market prices of flexibility, Price sensitivity of driver
Market prices of
flexibility Market prices of flexibility Prices of storage
Market prices of flexibility Prices of EVs with large battery Market constraints Rules at energy market, Data metering Rules at energy market, Cooperation of TSOs and DSOs Rules at energy market, Cooperation of OEMs, TSOs, DSOs and government Bureaucracy Bureaucracy Table 8: Cross-case analysis
Firstly, a comparison of the cases revealed that the actors involved in the flexibility creation and provision vary within the cases. If EVs are used as flexibility asset, the driver is the most important actor in the flexibility creation process. For stationary battery storages, the aggregator has more control over the final flexibility creation and the user of the flexibility asset is only in charge for providing the available time and capacity upfront.
boundaries (case A, B, C and E). Stationary battery storages are providing in- and outfeed flexibility (case B, C and D). The influence of the location is high for EVs due to the fact that not every charging station can be used to provide flexibility. All five cases are providing flexibility to TSOs, subsequently the location of the grid, where the flexibility is provided, has no influence (if DSOs are the flexibility consumers, this would differ). The battery capacity (kWh) is influencing the flexibility provision of all examined cases.
Thirdly, the effort to provide flexibility is high, except for case D, related to the financial compensation. Additionally, the range anxiety of the drivers plays a crucial role in the flexibility provision in case A, C and E which is linked to the battery capacity (kWh). The flexibility provision of all five cases is directly or indirectly influenced by the low prices of flexibility on the energy market. A direct effect is the reduced willingness to provide flexibility with the flexibility asset. An indirect influence is that with flexibility provision it is often not possible to justify the high investment costs for stationary battery storages (case D).
Fourth, all three aggregators (case A, B and C) are struggling with the energy market rules which make it very complicated to develop flexibility products for RFS (e.g. metering of provided flexibility or minimum capacity (kWh) of flexibility needed per location). Additionally, the cooperation between the OEMs, TSOs and DSOs and other stakeholders to create flexibility products for RFS is difficult. The two RFS (case D and E) see the biggest market hurdle in the bureaucracy involved if you participate actively on the energy market.
4.7 Summary results
The data collection revealed interesting findings and insights on the flexibility creation and provision process of RFS. In the creation process of flexibility with EVs, the most important actor is the flexibility asset user. For stationary flexibility assets the aggregator is more involved. In order to create flexibility products for RFS, various parties are involved. The OEM plays an important role by integrating software or hardware in their products which enable flexibility provision.5. Discussion
The first part of the discussion reflects on the relevant actors involved in the flexibility creation and provision process and compare it to the working paper by Van der Burg et al (2018) on energy system flexibility. The second part will answer the question what constraints are affecting the flexibility creation process. Specifically, constraints strongly influencing the flexibility are highlighted, analysed and compared with results in energy literature. This chapter will end by providing insights on how small, private consumers and prosumers can provide solutions for the energy transition and will reflect on opportunities on how to optimize the flexibility creation and provision process.
5.1 Relevant actors involved in the flexibility creation
The results reveal three main actors in the flexibility creation process, namely the aggregator, the flexibility asset owner and user. The asset owner can also be the user but a clear distinction is suggested. Other actors as charging station operators, providing the infrastructure for flexibility provision, can also be involved but have less influence on the actual flexibility creation process. Flexibility asset owner: The owner determines if the flexibility asset can be used for flexibility services and can set boundaries on various flexibility characteristics as the physical features or flexibility form. E.g., leasing companies of EVs or stationary battery storages have to authorize the usage of the flexibility asset for flexibility services since the provision can influence the condition of the asset (e.g. charging cycles). In addition, OEMs can be involved as the guarantee on flexibility assets might not cover the usage for flexibility services. Furthermore, the owner is responsible for the investment decision of the flexibility asset.
Flexibility asset user: The user of a flexibility asset can have a significant influence on the operational flexibility available, depending on the degree of automation and flexibility asset used. Flexibility provided by EVs is heavily correlated with the need for mobility of the driver (user), affecting the available capacity (kWh) and the available time (h). The location of the EV is only relevant if the flexibility is provided e.g. to DSOs for local grid balancing services. The flexibility characteristics of stationary battery storages are usually less affected by the user due to the lower dependency concerns as range anxiety. Only if the user is highly dependent on the stored energy, the flexibility characteristics as the capacity (kWh) and the available time (h) can be limited. If the flexibility creation process is highly automated, the influence of the user decreases. From an aggregator perspective, a high automatization and less influence of the user in the flexibility process is positively linked to a more reliable flexibility provision.
2.3, offer algorithms for optimal usage of flexibility assets (Marra et al., 2011; Al-Awami and Sortomme, 2012; Al-Al-Awami and Sortomme, 2012). The more control aggregators hold in the flexibility creation process, meaning de- and activation of flexibility assets and precise information on flexibility characteristics, the better they can apply such algorithms to optimize the flexibility provision and subsequently the profit.
Figure 10 displays an overview of the
relevant actors in the flexibility creation process and their main tasks. Normally, the flexibility owner is only involved in the start-up phase, since the acquisition of the flexibility asset and the authorization to provide flexibility within predefined boundaries (e.g. only in- or outfeed flexibility, maximal number of charging cycles per day, etc.) is usually a one-time process. The provision of flexibility information (capacity (kWh), available time (h) and location (only EV)) by the user and the control (activation and deactivation) of the asset by the aggregator is a continuous process. The degree of automation in the flexibility creation process can lower the influence of the user and the aggregator on the final flexibility provision. Additionally, charging station operators can be involved in the flexibility provision by EVs. Since they are only enabling the connection to the grid and the control over the charging process, they are not separately included as an actor in the basic flexibility creation process.
Based on the findings of the multiple case studies, it can be concluded that the model of the flexibility service system provided by van der Burg et al. (2018) addresses all relevant actors in the flexibility creation process. However, the results of this thesis imply that additional findings can be added to this model. In the flexibility creation process, multiple actors might be involved depending on the flexibility asset(s) used. A clear distinction between the flexibility asset owner and user is recommended, since their roles differ substantially. Dependently on the individual case, other actors in charge for providing the needed infrastructure and control between the aggregator and the flexibility asset(s) need to be considered as well.
5.2 Constraints influencing the flexibility creation
The constraints influencing the flexibility creation are depending on the flexibility asset used. The cases under investigation used either EVs or stationary battery storages to provide flexibility on the market. Thus, the following insights are limited on stationary or mobile batteries as flexibility asset. Technical constraints: Generally,
technical constraints are permanent and can only be influenced by changing the relevant component (hardware and/or software). Technical constraints have their origin directly in the characteristics of the flexibility asset or in the infrastructure enabling the flexibility creation and/or provision. Beside the general capacity (kWh) of a battery, the capacity (kWh) is affected by the sensitivity to outdoor temperature (especially during the winter), by conversion loss/storage loss and by the maximum amount of
charging cycles (will lower the capacity (kWh) on the long term). The maximum ramp-up/ramp-down rate (kW/h) can be neglected since batteries usually don’t have any technical difficulties related to this subject. The power provision capability (kW) varied between 11 kW (EV charging station) and 33 kW (stationary home storage). As a result of batteries running DC (direct current) and the public grid uses AC (alternating current), a converter is needed. Tomić and Kempton (2007) show in their paper that this limitation can reduce profit by 75% of what they could gain using bidirectional charging. First pilot projects are investigating the approach of DC grids but until they are commonly applied, a converter is needed for optimal usage of batteries as flexibility assets (Stieneker and De Doncker, 2016). Relating to the infrastructure needed, authorized smart meters are required to measure and invoice the amount of provided flexibility. Because it is rarely feasible for RFS to manually provide flexibility according to signals, aggregators need to have control over the flexibility asset to steer the flexibility provision within the communicated boundaries by the RFS (start and end time, capacity (kWh)). Results clearly indicate that RFS are often confronted with problems concerning the needed technical infrastructure and devices. Constraint Influence on flexibility Capacity of battery Capacity (kWh) Conversion loss of battery Capacity (kWh) Temperature sensitivity of battery Capacity (kWh) Charging station Power provision (kW) Control over flexibility provision Authorized smart
meter Needed to measure and invoice the provided flexibility
Converter Needed to provide infeed
flexibility Flexibility asset
control system
Start and end flexibility provision
Comfort constraints: EVs and stationary storages differentiate in their primary operational area. Stationary batteries are used for optimal energy management. EVs are in the first place acquired for mobility. This need for mobility highly effects physical features as the capacity (kWh) and the available time. Range anxiety, especially with smaller batteries, can further decrease the available flexibility (capacity (kWh) and available time) although technically more
flexibility would be available. Another constraint relating to EVs is the higher effort required to provide flexibility. Beside the connection to the grid, drivers of EVs have to communicate the required battery charging level and the departure time in consultation with other potential drivers of the EV. Especially, ambiguity in time of departure or need for capacity (kWh) will lead to a further decrease in flexibility provision since mobility is usually more important than the provision of flexibility. The effort to provide flexibility can be significantly reduced by offering convenient customer solutions. OEMs can implement hard- and software needed (e.g. converter or communication software) in their flexibility assets. A high degree in automation will further decrease the effort. Stationary battery storages are linked with less comfort constraints, since their main field of application is energy management. Interesting findings revealed case D. Here, the aggregator has the unlimited control over a predefined capacity of the storage and can use it for flexibility services. The RFS are not financially compensated for every exact amount of flexibility. Hence, the invoicing process between the aggregator and the RFS is simplified and the aggregator has more certainty about the actual available flexibility. The effort to provide flexibility in this case is also limited to a minimum for the RFS. Energy literature provides few information on comfort constraints affecting the flexibility provision. The results of the investigated cases revealed that especially comfort constraints can significantly reduce the flexibility provision and should gain more interest in literature.
Financial constraints: Financial constraints are primarily linked with the low market prices for flexibility. Additionally, the prices for flexibility assets are at a high level and are not expected to significantly decrease in the near future. Flexibility assets as storages have a low cost-benefit ratio for RFS as the price per kWh capacity is decreasing for larger storage systems. Furthermore, those low market prices often can’t justify investments in infrastructure enabling flexibility provision (e.g. smart meter or converter). The financial constraint to provide flexibility for RFS is often insufficiently
Constraint Influence on flexibility Need for mobility Capacity (kWh) Available time (h) Range anxiety Capacity (kWh) Available time (h) Effort to provide
flexibility General willingness of RFS to provide flexibility Level of
automation General willingness of RFS to provide flexibility
discussed in energy literature. Most studies analysing the financial perspective of RFS (e.g. Thimmapuram and Kim, 2013 or Moshari et al., 2010) are using smart grid environments. The investment needed in smart grid infrastructure and the corresponding devices is not taken into account in the financial calculation and with the current market prices it remains unclear if the investment will pay off for RFS. Hence, the results within this thesis show that RFS will benefit more by using their storages to first satisfy their personal need for electricity before providing their capacity (kWh) for flexibility services.
Market constraints: The market constraints can generally be divided into three parts. Firstly, the rules at the energy market make it very complicated for smaller parties as RFS to actively participate at the energy market. The provision of electricity to the grid is principally reserved for energy producers or balancing responsible parties. This is aggravated by the fact that the minimum
capacity and the time frame for flexibility services (e.g. 1 MW for 1 week at the FCR market) is often much higher than the physical features and available time that RFS can supply. This makes it very complicated for aggregators to create products for RFS. Secondly, to create these products for RFS to supply flexibility to the market, various parties are involved. Starting with the OEMs, technically enabling the flexibility creation, different actors as the DSOs, TSOs, BRPs, governments and aggregators have to communicate their ideas and concepts and align them. The third constraint is the bureaucracy incurred for RFS. Due to the fact that RFS are generating income with their flexibility assets, tax payments and other bureaucratic efforts occur (e.g. registration as a small business owner).
Summary constraints: The results within this thesis reveal that various constraints can affect the flexibility creation and provision by RFS. These constraints are not solely restricted to ‘internal constraints’ between the actor(s) and flexibility asset(s), e.g. need for mobility affecting the capacity (kWh), additionally ‘external constraints’ as regulations on the energy market are
Constraint Influence on flexibility Rules at energy
market General permission to provide flexibility Create products
for RFS Enable RFS to offer flexibility at the energy market Bureaucracy General willingness of RFS to
provide flexibility
Table 11: Overview market constraints
influencing the flexibility provision as well. E.g. if RFS want to provide flexibility with their EVs at a public charging station, RFS can experience difficulties with invoicing their provided flexibility because they are not allowed to use the data from their EV or public charging stations (often only authorized smart meters are allowed). External constraints as low market prices for flexibility can also effect the general willingness to provide flexibility and influence indirectly the comfort level of RFSs. Figure 11 displays an adapted overview of a flexibility supplier by van der Burg et al. (2018).
5.3 Opportunities to optimize the flexibility creation
Facilitate the technical flexibility creation: Results reveal that flexibility assets frequently don’t offer the technical possibility to provide and monetize the available flexibility. In particular, OEMs have to include the technical requirements in their products (e.g. EVs). If the technical ability to provide flexibility is a fixed component, results indicate an increase in flexibility provision by RFS. Additionally, supportive infrastructure as public charging stations can further enhance the flexibility creation. He et al. (2015) and Shahraki et al. (2015) are investigating the potential of smart deployment of charging stations but focus only on optimal recharging solutions and ignore the potential of (additional) flexibility provision by EVs.
Facilitate the provision of flexibility: The provision of flexibility to the regular energy market is rather limited for smaller parties as RFS. A promising approach is that RFS are helping to balance the grid on a local level. Firstly, for RFS it is more manageable to contribute with smaller amounts of flexibility to the grid stability. Secondly, the implementation of required regulations is more realizable on a local perspective thus simplifying the accessibility to the energy grid. E.g., the implementation of a flexibility component in the energy contract (e.g. ‘time of use tariff’, see appendix D) will attract more RFS, as they will benefit immediately for providing their flexibility (de Sá Ferreira et al., 2013). Additionally, local energy co-operations or initiatives can provide the aforementioned benefits for RFS to optimally use their flexibility. Studies by Schreuer et al. (2010) and Van Der Schoor et al. (2015) indicate the various benefits of local energy co-operations. Energy literature with a focus on flexibility provision by RFS in local energy cooperatives is completely lacking.
flexibility with their assets and subsequently optimise the utilization of their assets. E.g., stationary storages are usually linked with storing energy but the information on the potential of providing flexibility is commonly lacking. Additionally, OEMs of stationary storages or EVs are often not informing their customers about the opportunity of providing flexibility with their assets thus resulting in wasting a lot of potential flexibility by RFS. Energy literature is clearly lacking studies on the marketing perspective of flexibility and how to optimal inform and target potential RFS. Further research on how to optimally activate potential RFS can help to increase the flexibility provision substantially.
5.4 Practical implications
Beside the theoretical contributions discussed in the previous sub-chapters, this study reveals practical implications that can be used by various parties to optimise the flexibility creation and provision.
In theory, the paper on energy system flexibility provided by van der Burg et al. (2018) addresses all relevant actors involved in the flexibility provision process. The results within the case studies of this thesis indicate that, beside the aggregator and flexibility asset owner and user, additional actors can be involved. Actors providing the necessary infrastructure or flexibility information need to be taken into consideration to create a complete supply chain. Furthermore, these actors need to be (financially) compensated.
Secondly, the results clearly show that various constraints can limit the flexibility creation and provision by RFS. These constraints have different roots and subsequently have to be optimized by different parties. Technical constraints can be most optimally solved by OEMs by integrating the technical abilities in their assets to provide flexibility. Comfort constraints can be lowered by developing suitable solutions and products for RFS and subsequently decrease the effort needed to provide flexibility. The financial constraint of the low market prices of flexibility is very difficult to address since the only feasible solution is an environmental driven tax system supporting RES and subsequently flexibility services. These market constraints seem to be the most difficult obstacle. The evolution from a centralized towards a decentralized energy market threatens the traditional energy suppliers since they will lose influence and might be confronted with lower profit. Accordingly, the implementation of rules and products enabling smaller, decentralized parties as RFS is often out braked by parties who feel offended by a more decentralized energy market.
