University of Groningen
Distributed Control, Optimization, Coordination of Smart Microgrids
Silani, Amirreza
DOI:
10.33612/diss.156215621
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.
Document Version
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Publication date: 2021
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Silani, A. (2021). Distributed Control, Optimization, Coordination of Smart Microgrids: Passivity, Output Regulation, Time-Varying and Stochastic Loads. University of Groningen.
https://doi.org/10.33612/diss.156215621
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Summary
Microgrids are power distribution systems which are typically classified by Direct Current (DC) and Alternating Current (AC) networks and are interconnected clusters of Distributed Generation Units (DGUs), loads and energy storage devices. Nowa-days, renewable generation sources and new loads such as Electric Vehicles (EVs) are largely used in power systems due to the technological developments and politics for environmental protection. Renewable generation sources generally reduce the cost of electricity generation and provide clean energy for customers. However, renewable generation sources are uncontrollable and should be managed as the uncertainty of generation side in addition to the uncertainty of load side. Power networks tradi-tionally tackled the uncertainty of loads via adjusting the controllable generations. However, thanks to the increased share of renewable generations and large scale introduction of new loads such as EVs, new control strategies are required to address the uncertainties of power networks. The integration of smart sensors and meters, advanced two-way communication technologies, distributed control strategies, and IT-infrastructures can be utilized to promote the control strategies to address the uncertainties of power networks.
Since the ever increasing electrification of transportation (e.g., plug-in electric vehicles) and buildings (e.g., heating/cooling) may increase the demand fluctuations and put a strain on the system stability, the resilience and reliability of the power grid may benefit from the design and analysis of control strategies that theoretically guarantee the system stability in presence of stochastic or time-varying loads. Therefore, due to the random and unpredictable diversity of load patterns, it is more realistic to consider dynamical or stochastic differential load models. In DC networks, in order to guarantee a proper and safe functioning of the overall network and the appliances connected to it, the main goal is the voltage regulation. Thus, we propose controller schemes achieving voltage regulation and ensuring the stability of the overall DC network. Moreover, an important operational objective of AC networks is frequency regulation. Hence, we propose controller schemes achieving frequency regulation and ensuring the stability of the overall AC network. Indeed, in both AC and DC
214 Summary networks, we use output regulation methodology for control design when we model the loads as dynamical systems and we use Ito calculus framework when we model the loads by stochastic processes.
Furthermore, we propose an Energy Management Strategy (EMS) taking into account the load, power flow, and system operational constraints in a distribution network such that the cost of the Distributed Generations (DGs), Distributed Storages (DSs) and energy purchased from the main grid are minimized and the customers’ demanded load are provided where the loads are considered stochastic generated by time-homogeneous Markov chain. Finally, we solve a microgird optimal con-trol problem with taking into account the social behavior of the EV drivers via a corresponding real data set.
