Optimizing the investments of power utilities in smart grid by asset life-cycle cost model

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Optimizing the Investments of Power Utilities in Smart

Grid by Asset Life-cycle Cost Model

Tongyou (Sofia) Gu 11081821 Thesis Supervisor: Prof. Dennis Jullens

Master in International Finance

Amsterdam Business School, University of Amsterdam

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Abstract

As a capital-intensive industry, the investment on building Smart Grid consists of not only the initial cost on basic infrastructures such as power cables and substations, but also the monitoring/digitalizing and maintenance throughout the whole operational life of the assets. To optimize the investment strategy, it is important to consider all the costs during the life-cycle and the trade-off between the costs.

In this graduation study, an Asset Life-cycle Cost (LCC) model is built to calculate the total costs of the assets in electricity distribution grid during the whole life cycle. Different investment strategies are compared based on the model to assist the decision making on the allocation of the investments. Furthermore, sensitivity analysis is made to see which factors have most influence on the conclusion, and have most impact on decision making.

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As a capital-intensive industry, the investment on building Smart Grid consists of not only the initial cost on basic infrastructures such as power cables and substations, but also the monitoring/digitalizing and maintenance throughout the whole operational life of the assets. Considering all the cost factors relating to the asset during the life-cycle and optimizing the trade-off between those cost factors will give the minimum life cycle cost of the asset (Kite, 1995) (Korpi & Ala-Risku, 2008). This process involves estimation of costs on a whole life basis before making a choice of investment strategy from the various alternatives. Life cycle cost of an asset can, very often, be many times of the initial purchase or investment cost on the assets (Woodward, 1997) (Sherif & Kolarik, 1981).

It is important that management should realize the source and magnitude of lifetime costs so that effective action can subsequently be taken to control them. This approach to decision making encourages a long-term outlook to the investment decision-making process rather than focus only on the initial acquisition cost (Nilsson & Bertling, 2007).

Alliander, a Dutch grid operator, delivers electricity and gas to more than 1/3 of the customers in the Netherlands. Figure 1 shows the service area of Alliander. Figure 2 illustrate the electricity network from power plant to end customers. Electricity energy is transmitted to power substation via High Voltage (HV) network, distributed via Medium Voltage (MV) network of 20kV or 10kV, and further delivered to customers via Low Voltage (LV) network of 400V. Alliander is responsible for the energy distribution in MV and LV network. The vision of Alliander is to provide sustainable, reliable, affordable energy to customers.

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2 Figure 1 Alliander service area for electricity and gas delivery (Alliander, Kwaliteits- en

capaciteitsdocument elektriciteit, 2015)

Figure 2 Electricity energy distribution (Alliander, Automating the Distribution Grid, 2012)

With the development of Smart Grid, new technologies such as monitoring/digitalizing devices can reduce the number or the duration of power outages. The investment in these new techniques are aimed at lowering the failure cost and increasing reliability. In the past 10 years Alliander has invested approximately 450 to 700 million per year in the electricity grid. From now until 2055 the cumulative investment will be 17 to 27 billion.

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3 Examples of the monitoring/digitalizing devices are Smart Cable Guard, Global System for Mobile Communications (GSM) fault indicator and intelligent Ring Main Unit (iRMU). In this graduation study, an Asset Life-cycle Cost (LCC) model is built to calculate the total costs of the assets in electricity distribution grid during the whole life cycle, including the investments on monitoring/digitalizing and cost of power outages. Different investment strategies are compared based on the model to assist the decision making on the allocation of the investments, which could meet the vision of Alliander (Gomes & Michaelides, 2005) (Duran, Roda, & Macchi, 2016). In respect to company confidential regulation, all the data in this thesis are randomized and anonymized from the actual data.

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2 Research questions

Central question of the thesis:

Developing a framework for investment decisions based on Asset Life-cycle Cost model for (energy) utilities to meet their visions.

Sub-questions:

1. How to build an LCC model for (energy) utilities?

The scope of this question includes what variables should be taken into consideration in de model; which new techniques are going to be analyzed and how to translate their performance into costs; What will be de interesting scenarios to compare with each other.

2. How should social impacts e.g. power failures be evaluated?

The System Average Interruption Duration Index (SAIDI) is commonly used as a reliability indicator by electric power utilities. SAIDI will result in internal failure cost, financial compensations to customers, influence on the transport tariff thus the future income, impact on company image, etc. Therefore, the value of SAIDI contains direct cash outflow such as compensations, as well as non-direct cash flow regarding the social impact, which needs to be evaluated in a reasonable way.

3. What are the “actual earnings” and “reported earnings” if different techniques in Smart Grid are applied?

Define how the costs related to monitoring/digitalizing devices should be capitalized or expensed according to the accounting standards.

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5 Grid?

Compare the total life-cycle cost in different scenarios. Analyze the key factors that influence the decision making based on the model.

Figure 3 gives the relation of the four sub-questions in this study. The valuation of social impacts is one of the important inputs for the LCC model. Together with the impact from the recognition of CAPEX and OPEX, the LCC model can assist the decision making on the allocation of the investments.

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3 Theoretical framework

LCC model calculates the total cost for a technical system during its lifetime (Gluch & Baumannb, 2004). The total cost involves, purchase, operation and maintenance, and power failures. The goal is to minimize the total lifetime cost (van Casteren, Bollen, & Schmieg, 2000) (Clift & Bourke, 1999).

Within this study, it has been assumed that the total LCC (in euros) is defined as LCC = CINI + COP + CSAIDI

where

CINI: the initial cost of basic assets, e.g. power cables, cable joints, substations; the initial cost of the monitoring/digitalizing devices.

COP: the operational cost incl. the periodical cost of the monitoring/digitalizing devices in the grid operation;

CSAIDI: the cost of power failures (System Average Interruption Duration Index);

Figure 4 illustrates the trade-off of the costs during the life cycle. For many industries, increasing the initial investment to acquire assets with better quality will gain lower operational cost and failure rate. For electricity grid, most of the electrical infrastructures were built in the past decades, thus the initial cost (CINI) of the basic assets is almost fixed, or doesn’t vary greatly. The investments in monitoring/digitalizing devices (CINI and COP) for grid operation could resulted in lower failure rate of the basic assets thus lower failure cost (CSAIDI). The LCC model can give advices on how to achieve the optimal choice in the trade-off between the investment (increase in CINI and COP) and the benefit (reduce in CSAIDI).

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7 Figure 4Trade-off of the costs during the life cycle

Figure 5 shows the flowchart of the calculation of life-cycle cost each investment strategy. The horizon of the life-cycle is the technical lifetime of the basic assets, which could be approximately 100 years.

The costs are calculated by the present value method. The present value (PV) means the amount of money that should be deposited into the bank now at a certain rate d to pay for an outlay 𝐶𝑛 after n years. This means that all future payments are

re-calculated to the equivalent value for the present time. The present value of one outlay 𝐶𝑛 to be paid after n years is gained by multiplying it with the present value factor

𝑃𝑉𝑓(𝑛,𝑑) as

𝑃𝑉 (𝐶𝑛) = 𝐶𝑛∗ 𝑃𝑉𝑓(𝑛,𝑑) = 𝐶𝑛∗ (1 + 𝑑)−𝑛

where 𝐶𝑛 is the outlay in (euros), 𝑛 is the number of years from the present to the

date of the outlay, and 𝑑 is the discount rate, which is assumed to be the weighted average cost of capital (WACC) of Alliander in this study (Bogenstatter, 2000).

The PV of each outlay is further accumulated to obtain the total net present value (NPV) of the life-cycle.

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8 𝑁𝑃𝑉 = ∑ PV (Ck)

𝑛

𝑘=1

To gain a better insight about the yearly cost of each investment strategy, the average annual cost is calculated within the time horizon. The formula for annuity is applied for the calculation.

𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑎𝑛𝑛𝑢𝑎𝑙 𝑐𝑜𝑠𝑡 (𝑎𝑛𝑛𝑢𝑖𝑡𝑦) = 𝑁𝑃𝑉 ∗ 𝑑

1 − (1 + 𝑑)−𝑛

Sensitivity analysis can be made to see which factors (e.g. performance of the new techniques, valuation of power failures) have most influence on the conclusion, and have most impact on decision making (Gomes & Michaelides, 2005) (Slovic, 1972).

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4 Methodology

4.1 Asset Life-cycle Cost model

A model is developed to calculate and optimize the life-cycle cost of the assets in different scenarios. Three steps to build the model: (1) Design different scenarios based on the investment strategies; (2) Calculate the costs of new techniques for each scenario, incl. one-time cost (e.g. acquisition and installation) and periodical cost (e.g. maintenance, subscriptions of data communication); (3) Valuation of the impact of these new techniques (e.g. the reduction of power outage time), which is further discussed in 4.2.

Internal data and information of Alliander are basically used in building the model. The data and information can be obtained and gathered from different departments of Alliander. Due to company confidential regulation, all the data in this thesis are randomized and anonymized from the actual data.

Other utilities in the Netherlands and other countries may have different strategies than Alliander. However, utilities are in a capital-intensive industry, and the life-cycle of their assets are usually of long term. This research focuses on how to use a LCC model to assist on making investment decisions, thus it is assumed that the data and information of Alliander can be representative.

4.2 Valuation of power outages

4.2.1 Relevant techniques in this study

The following monitoring/digitalizing devices in Table 1 are analyzed in this study. For each device, the reduction of power outage time is estimated.

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10 Table 1 New techniques in Smart Grid

Technique Function Benefit

Smart Cable Guard

Pinpoint the weak points in electricity network

Prevent power outages, reduce power recovery time

GSM fault indicator

Indicate the location of power outages

Reduce power recovery time

iRMU Indicate the location of power

outages

Remote control of substations

Reduce power recovery time

4.2.2 Valuation of SAIDI

SAIDI commonly used as a reliability indicator by electric power utilities. In Netherlands, SAIDI is defined as the average duration (in minutes) of power outage per customer per year. The cost of SAIDI consists of direct and indirect cash flow.

• Direct cash outflow: internal failure cost, financial compensations to customers, influence on the transport tariff thus the future income

• Indirect cash outflow: impact on sustainability, customer comfort and company image

There is no standard valuation of SAIDI. In this research, the intuition in the valuation is studied, and the impact of the valuation is analyzed.

4.3 Decision making for investments in new techniques

Compare the total life-cycle cost in different scenarios. Make sensitivity analysis based on the model to analyze which factors influence the result most.

4.4 Recognition of CAPEX and OPEX by accounting standards

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11 as capital expenditure (CAPEX) or operating expense (OPEX). The “actual earnings” and “reported earnings” are compared. (Hamner & Stinson, 1995)

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5 Input data and model design

Internal data and information of Alliander are basically used in building the model. This section describes how the original data and information are formulated to create different scenarios, i.e. different investment strategies.

5.1 Original input data and information

The original data and information are obtained and gathered from different departments of Alliander. The data sources include the technical policies regarding how the electricity network should be build and operated, and the business cases for the implementation of monitoring/digitalizing devices.

5.1.1 Calculation of WACC

The method that Alliander uses for the calculation of WACC is based on the report of Authority for Consumers and Markets (ACM) (The WACC for the Dutch TSOs and DSOs, 2016). The WACC is expressed as real pre-tax, with the cost of equity calculated using the Capital Asset Pricing Model (CAPM).

Figure 6 The parameters for calculating WACC

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13 for some important parameters are as follows:

The risk-free rate is determined based on the historical yield on the 10-year Dutch and German government bounds, as shown in Figure 7.

The credit spread is assessed based on the daily interest rates of EURO denominated non-government bonds in three rating categories: BBB, AA, A and A Utility as an extra category, as in Figure 8.

The cost of equity is calculated by CAPM model. The market risk premium is based on the results of the research report (Dimson, Marsh, & Staunton, 2015), which is a widely-recognized report and illustrates the historical equity risk premium of Eurozone countries for the period 1900-2014, as shown in Table 2. The equity beta is estimated based on the regressed equity beta of comparable companies in Table 3. The group of comparable companies are selected by criteria related on the risk profile of the companies, such as size and liquidity of shares.

Figure 7 Historical nominal risk-free rate: Netherlands (NL) and Germany (DE) 10-year government bond (The WACC for the Dutch TSOs and DSOs, 2016)

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14 Figure 8 Historical credit spread 10-year non-government bounds (The WACC for the Dutch TSOs and

DSOs, 2016)

Table 2 Historical equity risk premium of Eurozone countries 1900-2014 (Dimson, Marsh, & Staunton, 2015)

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15 Table 3 Equity beta’s of comparable companies (The WACC for the Dutch TSOs and DSOs, 2016)

On the basis of the previous data sources the values of the parameters for calculating WACC can be estimated. The nominal pre-tax WACC is:

(1-Debt ratio)*Cost of equity/(1-tax rate)+Debt ratio*Cost of debt

Taken inflation into consideration, the real pre-tax WACC can be then calculated by:

(1+nominal pre-tax WACC)/(1+inflation)-1

5.1.2 Cost of basic assets

Most of the electrical infrastructures were built in the past decades. The initial cost of the basic assets, e.g. power cables, cable joints, substations, etc. is already spent and almost fixed. In some regions with new buildings, extended or new electricity networks are needed, but again the cost is almost fixed or does not vary significantly. In the LCC model, the initial cost of basic assets is assumed to be the same for all the scenarios.

For defect components, the replacement of new components is needed. The cost of acquisition of the new components is included in the cost of power failures. More explanation is in 5.1.4.

The quantity of some basic assets e.g. power cables, substations is important input data for the LCC model, because it determines how many monitoring/digitalizing

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16 devices are needed in the electricity network.

There are generally two types of power cables that are used in electricity network: the old type PILC (paper insulated, lead covered) and the new type XLPE (cross-linked polyethylene insulated). PILC cables have higher failure rate and need more monitoring devices such as Smart Cable Guard in comparison with XLPE cables. Therefore, the quantity of monitoring devices that are needed in the electricity network depends on the total lengths of these two types of cable. The total cable length of XLPE and PILC are important input for the LCC model.

Distribution power substations can be equipped with iRMU. Because of the high cost, the distribution substations in the top essential locations should become intelligent first. The total quantity of the current (non-intelligent) distribution substations is also an important base for the investment on iRMU.

5.1.3 Costs and benefits of the monitoring/digitalizing devices

5.1.3.1 Costs of the monitoring/digitalizing devices

• One-time cost

All the devices require one-time cost for acquisition and installation. Given the high quantity of devices and the large area of electricity network, the duration of the whole roll-out is usually around 10 years.

• Periodical cost

Periodical costs include costs on maintenance, operation of the devices, and the subscriptions of data communication. An indication of the one-time and periodical cost is shown in Table 4.

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17 technical lifetime of Smart Cable Guard and GSM fault indicator is 15 years. This means in the first 10 years Alliander needs to pay the one-time cost as well as the periodical cost, and in Year 11 to Year 15 only periodical cost is needed. From Year 16 the investment process will repeat and so on, until the horizon of the LCC model which is 90 years.

For iRMU, the technical lifetime is 50 year. Table 4 illustrates also the roll-out duration and technical lifetime of each device.

Table 4 Costs and technical life time of each monitoring/digitalizing device

Technique One-time cost Periodical cost Roll-out duration Technical lifetime

Smart Cable Guard Low Medium 10 years 15 years

GSM fault indicator Low Medium 10 years 15 years

iRMU High Low 10 years 50 years

5.1.3.2 The quantity of monitoring/digitalizing devices

Smart Cable Guard can be used for two purposes: 1, to detect the weak point in the cable thus to prevent cable defect/ power outage (by pro-active replacement); 2, to pinpoint the defect point of the cable thus to reduce the restoration time. For different use purposes, Smart Cable Guard can monitor different length of cable. The monitor length varies also with the cable types (XLPE or PILC).

If the monitor length is short such as for detecting weak point in PILC cable, more systems of Smart Cable Guard will be needed. Table 5 gives an indication of the quantity of Smart Cable Guard that are needed for each use purpose and each cable type.

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18 Table 5 Quantity of Smart Cable Guard needed for different use purposes and cable types

XLPE cable PILC cable

Detect weak point Medium Higher amount

Detect defect point Lower amount Medium

According to the technical policies, the minimal necessary quantity of GSM fault indicators is approximately proportional to the length of power cables.

As mentioned in 5.1.2, the cost of iRMU is extremely high and it is recommended to equip first for the distribution substations in top essential locations. Cost-benefit analysis by Alliander suggests that the optimal ratio of digitalizing is 25% of the distribution substations.

5.1.3.3 Benefits of the monitoring/digitalizing devices

The biggest benefit of applying the monitoring/digitalizing devices is the reduction of the total power outage time (SAIDI).

As mentioned in 5.1.3.2 Smart Cable Guard can be applied for two purposes. The first is to detect the weak point of a cable, which can prevent a power outage from happening. In this way, the total power outage time could be reduced greatly. The benefit that can be achieved depends also on the performance of Smart Cable Guard. Because this is a relative new technique which has not been applied in large-scale, the performance has not yet been precisely evaluated. In the LCC model the performance is designed as a parameter which can be typed in.

The second use purpose of Smart Cable Guard is to pinpoint the defect point of the cable, which saves much time for grid operators to find the defect location. GSM fault indicator works in a similar way. Both techniques can reduce the restoration time after the cable defect. An estimation can be made for the average power outage duration when these techniques are applied.

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19 With iRMU, the power recovery process can be acted by remote control and the power recovery time can be reduced to minimal.

Table 6 illustrates the average SAIDI without new techniques as well as an estimation of SAIDI if new techniques are applied.

Table 6 The power outage time (SAIDI) with and without new techniques

Without new techniques Smart Cable Guard GSM fault indicator iRMU

Power outage time High Low-Medium Medium Low

5.1.4 Valuation of SAIDI

SAIDI is commonly used as a reliability indicator by electric power utilities. In Netherlands, SAIDI is defined as the average duration (in minutes) of power outage per customer per year. The cost of SAIDI is usually calculated once per month and accumulated to a yearly cost. The calculation is as follows:

Cost of SAIDI = total power outage time (minute) * valuation of SAIDI per minute

The total power outage time is related to the frequency and the duration of power outages, as well as the size of the impact region of each power outage.

The valuation of SAIDI consists of direct and indirect cash flow.

• Direct cash outflow: internal failure cost, financial compensations to customers, and influence on the transport tariff thus the future income

• Indirect cash outflow: impact on sustainability, customer comfort, and company image

There is no standard method to valuate SAIDI. The research institute Blauw Research has developed a model to estimate the value of power failures, i.e. what compensations would a customer expect by different failure frequencies and durations of power outages (Bosma, Roose, & Heida, 2012). The research was based on

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20 surveys to household customers and business customers. The result of the research is that the value of power outages is a logarithmical curve. The value gets higher when the failure frequency and duration get higher. This model covers the customer compensation and comfort. However, the other aspects can still not be evaluated.

Grid operators have their records of their historical failure frequency and duration, and they can use this model to estimate the valuation of power outages related to customers. An extra internal valuation would be added to represent the impact on sustainability and company image. The internal valuation could be even higher than the part of valuation related to customers. Because the internal valuation is determined by each grid operator self, the final valuation of SAIDI varies greatly by different grid operators.

The valuation of SAIDI has large influence on the result of LCC model. In 6.2 sensitivity analysis is made to show how this valuation can affect decision making.

5.2 Design of the scenarios

The LCC model is designed based on the input data described in 5.1. Table 7 shows the model with three scenarios. The general input is how much percentage of the network will be installed with each type of monitoring/digitalizing device. Each scenario is defined by the combination of the percentages thus represents for the investment strategy. Because the three types of devices have large overlap in their functions, it is not necessary to apply more than one new technique in the same area of the network.

Cost of basic assets (CINI) is the cost for the acquisition of basic infrastructures such as power cables, substations, etc. This cost is assumed to be the same for all the scenarios. It doesn’t create a deviation in the total cost. It is mentioned in the LCC model to make the process of asset life-cycle complete, but it is not included in the calculation of total LCC. In this way, the model is relative and comparative, instead of an absolute model of life-cycle cost that refers to the total costs incurred during

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21 ownership.

Cost in grid operation consists of one-time cost (CINI) which is usually spread in 10 years, and periodical cost (COP) which is paid regularly during the technical lifetime of the device (15 years for Smart Cable Guard and GSM fault indicator, 50 years for iRMU). After the technical lifetime reinvestment on new devices is needed. Therefore, the one-time cost will be repeated in each 15 or 50 years.

Cost of SAIDI (CSAIDI) is the total cost of power outages in the network. The cost is calculated based on the ratios of network with each new technique, given that applying different techniques will result in different (reduction of) power outage time.

Asset Life-cycle Cost (LCC) is the sum of initial cost, operational cost and cost of

SAIDI. The net present value (NPV) and average annual cost are calculated for further comparison and analysis.

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22 Table 7 Asset Life-cycle Cost model with three scenarios

Scenario 1 Scenario 2 Scenario 3

% of the network with Smart Cable Guard X1% X2% X3%

% of the network with GSM fault indicator Y1% Y2% Y3%

% of the network with iRMU Z1% Z2% Z3%

Cost of basic assets (CINI) Fixed Fixed Fixed

Cost in grid operation

Smart Cable Guard

One-time cost (CINI) 10-year project in each 15 years 10-year project in each 15 years 10-year project in each 15 years

Periodical cost (COP) All the years All the years All the years

GSM fault indicator

iRMU

Cost of SAIDI (CSAIDI)

Calculated based on X1%, Y1%, Z1%

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6 Result analysis and decision making

6.1 Model results

The X, Y and Z in Table 7 need to be defined first. Three scenarios that represent different investment strategies are defined as in Table 8. In Scenario 1 no new technique is applied, which is the reference scenario. In Scenario 2 Smart Cable Guard (10% of the network area) and GSM fault indicator (60% of the network area) are applied while iRMU is still applied for 0% of the network area because of the high initial cost. In Scenario 3 the most optimal percentage of the network, 25%, is applied with iRMU, and the area with the other two techniques remain the same composition as in Scenario 2.

Table 8 Compositions of new techniques in three scenarios

Scenario 1 Scenario 2 Scenario 3

% of the network with Smart Cable Guard 0% 10% 10%

% of the network with GSM fault indicator 0% 60% 60%

% of the network with iRMU 0% 0% 25%

% of the network without new technique 100% 30% 5%

Figure 9 to Figure 11 illustrate the cash outflow of the initial cost, operational cost and cost of SAIDI for each scenario. Detail cashflow of the first five year is provided in Appendix. The time horizon of the LCC model is 90 year from 2017, to cover the whole technical lifetime of the basic assets. The cash amount is the price of 2017, without calculating to present value or taking inflation into consideration.

In Scenario 1 the initial and operational cost is around zero over time, and the cost of SAIDI is quite high.

In Scenario 2 Smart Cable Guard and GSM fault indicator are invested. The initial cost arises in the first 10 years of every 15 years, because that the rollout of these devices

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24 last usually 10 years and the technical lifetime of these devices is 15 years. The operational cost increases repetitively due to regular maintenance of the devices. The cost of SAIDI reduces remarkably in the beginning and then remains at the same level for the whole time.

In Scenario 3 it is obvious to see the high initial cost on iRMU, which is in the first 10 years of every 50 years, because its technical lifetime is 50 year. The maintenance of iRMU is also of high cost, which makes the operational cost higher than Scenario 2. The reduction of SAIDI is also higher, which indicates the benefit of this investment.

The results from Scenario 1 and 2 give that a relatively lower investment on Smart Cable Guard and GSM fault indicator could lead to a higher reduction of power outage cost. The result of Scenario 3 shows that investment on iRMU is a cost and high-benefit strategy.

Figure 9 Cash outflow for Scenario 1

-1,000,000 1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 Cas h o u tflow Year

Cash outflow for Scenario 1

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25 Figure 10 Cash outflow for Scenario 2

Figure 11 Cash outflow for Scenario 3

The NPV of the cashflow for the three scenarios is calculated based on the results above, as shown in Table 9. To gain a better insight on the cost of every year, the average annual cost is further calculated based on the NPV, as shown in Table 10. Both tables indicate that the investment on these new techniques will lead to a lower SAIDI and eventually a lower life-cycle cost. It is beneficial for energy utilities to apply these new techniques.

1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 1 4 7 101316192225283134374043464952555861646770737679828588 Cas h o u tflow (E U R) Year

Cash outflow for Scenario 2

Initial cost Operational cost Cost of SAIDI

1,000,000 2,000,000 3,000,000 4,000,000 5,000,000 6,000,000 1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 Cas h o u tflow (E U R) Year

Cash outflow for Scenario 3

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26 Table 9 NPV of the total life-cycle cost of the three scenarios

Initial cost € 1,060,900 € 2,069,746 € 20,355,836

Operational cost € 207,589 € 290,179 € 223,086

Cost of SAIDI € 121,312,991 € 79,573,641 € 58,561,047

LCC € 122,581,480 € 81,933,566 € 79,139,969

Table 10 Average annual cost of the three scenarios

Initial cost € 44,698 € 87,204 € 857,643

Operational cost € 8,746 € 120,095 € 117,268

Cost of SAIDI € 5,380,236 € 3,510,903 € 2,569,835

LCC € 5,433,680 € 3,718,201 € 3,544,747

6.2 Sensitivity analysis

Sensitivity analysis is made to examine the impact of the inputs on the final conclusions.

The scenarios in 6.1 are based on the fixed compositions of network area that Smart Cable Guard, GSM fault indicator and iRMU are applied, as in Table 8. To analyze the life-cycle cost in different compositions and to find the optimal composition, sensitivity analysis is made based on Scenario 2 and 3.

Table 11 shows the life-cycle cost when different ratio of the network is implemented with Smart Cable Guard and GSM fault indicator when no network is implemented with iRMU. To compare the outcome with different combinations, each ratio varies from 0% to 100% with a step of 10%. The life-cycle cost is always lower when any or both of these techniques are applied. For the same percentage of the network area, Smart Cable Guard delivers a lower total cost than GSM fault indicator. The lowest cost

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27 appears when the whole network is 100% monitored by Smart Cable Guard. The deviation between applying Smart Cable Guard and GSM fault indicator is not extremely large, thus it is encouraged that the grid operator should apply at least one of these two techniques. In Table 12 the composition of iRMU is changed to 25% the network, which means the composition of the other two techniques can be maximal 75%. Under the same percentages of Smart Cable Guard and GSM fault indicator, the total cost in Table 12 is always lower than in Table 11. Therefore, it can be concluded that the implementation of iRMU can reduce the total cost even further.

A global optimal composition of the techniques is difficult to find because there are other factors that may have influence on the result. Table 13 shows the sensitivity analysis for the performance of Smart Cable Guard. Green color is for lower cost and red is for higher cost. In 5.1.3.3 is mentioned that Smart Cable Guard can prevent power outages by detecting the weak points in the cables and taking actions proactively. In previous calculations, it is assumed that 30% of all the power outages can be prevented by Smart Cable Guard. If the performance can achieve a higher level, the total cost would be lower with the same quantity of Smart Cable Guard. In the contrast, if the performance is lower, it may be more beneficial to apply other techniques than Smart Cable Guard.

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28 Table 11 Sensitivity analysis for different combinations of Smart Cable Guard and GSM fault indicator in scenario 2 (0% iRMU)

Table 12 Sensitivity analysis for different combinations of Smart Cable Guard and GSM fault indicator in scenario 3 (25% iRMU)

######## 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% € 5,433,680 € 5,089,010 € 4,760,622 € 4,448,516 € 4,152,692 € 3,873,149 € 3,609,889 € 3,362,910 € 3,132,214 € 2,917,799 € 2,719,667 10% € 5,197,635 € 4,860,542 € 4,539,731 € 4,235,201 € 3,946,954 € 3,674,988 € 3,419,304 € 3,179,903 € 2,956,783 € 2,749,945 € 2,559,389 20% € 4,961,591 € 4,632,074 € 4,318,839 € 4,021,887 € 3,741,216 € 3,476,827 € 3,228,720 € 2,996,895 € 2,781,352 € 2,582,091 € 2,399,112 30% € 4,725,546 € 4,403,606 € 4,097,948 € 3,808,572 € 3,535,478 € 3,278,666 € 3,038,136 € 2,813,887 € 2,605,921 € 2,414,237 € 2,238,834 40% € 4,489,501 € 4,175,138 € 3,877,056 € 3,595,257 € 3,329,740 € 3,080,505 € 2,847,551 € 2,630,880 € 2,430,490 € 2,246,382 € 2,078,557 50% € 4,253,456 € 3,946,670 € 3,656,165 € 3,381,943 € 3,124,002 € 2,882,343 € 2,656,967 € 2,447,872 € 2,255,059 € 2,078,528 € 1,918,279 60% € 4,017,411 € 3,718,201 € 3,435,274 € 3,168,628 € 2,918,264 € 2,684,182 € 2,466,382 € 2,264,864 € 2,079,628 € 1,910,674 € 1,758,002 70% € 3,781,366 € 3,489,733 € 3,214,382 € 2,955,313 € 2,712,526 € 2,486,021 € 2,275,798 € 2,081,857 € 1,904,197 € 1,742,820 € 1,597,724 80% € 3,545,321 € 3,261,265 € 2,993,491 € 2,741,999 € 2,506,788 € 2,287,860 € 2,085,213 € 1,898,849 € 1,728,766 € 1,574,966 € 1,437,447 90% € 3,309,276 € 3,032,797 € 2,772,600 € 2,528,684 € 2,301,050 € 2,089,699 € 1,894,629 € 1,715,841 € 1,553,335 € 1,407,111 € 1,277,169 100% € 3,073,232 € 2,804,329 € 2,551,708 € 2,315,369 € 2,095,312 € 1,891,538 € 1,704,045 € 1,532,834 € 1,377,904 € 1,239,257 € 1,116,892

% of the network with Smart Cable Guard

% o f th e n etw o rk w ith G SM fa u lt in d ic ato r ######## 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 0% € 5,231,120 € 4,915,555 € 4,616,272 € 4,333,271 € 4,066,552 € 3,816,115 € 3,581,960 € 3,364,087 € 3,162,495 € 2,977,186 € 2,808,158 10% € 4,995,076 € 4,687,087 € 4,395,381 € 4,119,957 € 3,860,814 € 3,617,954 € 3,391,375 € 3,181,079 € 2,987,064 € 2,809,332 € 2,647,881 20% € 4,759,031 € 4,458,619 € 4,174,490 € 3,906,642 € 3,655,076 € 3,419,793 € 3,200,791 € 2,998,071 € 2,811,633 € 2,641,477 € 2,487,603 30% € 4,522,986 € 4,230,151 € 3,953,598 € 3,693,327 € 3,449,339 € 3,221,632 € 3,010,207 € 2,815,064 € 2,636,202 € 2,473,623 € 2,327,326 40% € 4,286,941 € 4,001,683 € 3,732,707 € 3,480,013 € 3,243,601 € 3,023,470 € 2,819,622 € 2,632,056 € 2,460,771 € 2,305,769 € 2,167,049 50% € 4,050,896 € 3,773,215 € 3,511,815 € 3,266,698 € 3,037,863 € 2,825,309 € 2,629,038 € 2,449,048 € 2,285,341 € 2,137,915 € 2,006,771 60% € 3,814,851 € 3,544,747 € 3,290,924 € 3,053,383 € 2,832,125 € 2,627,148 € 2,438,453 € 2,266,041 € 2,109,910 € 1,970,061 € 1,846,494 70% € 3,578,806 € 3,316,278 € 3,070,033 € 2,840,069 € 2,626,387 € 2,428,987 € 2,247,869 € 2,083,033 € 1,934,479 € 1,802,206 € 1,686,216 80% € 3,342,761 € 3,087,810 € 2,849,141 € 2,626,754 € 2,420,649 € 2,230,826 € 2,057,284 € 1,900,025 € 1,759,048 € 1,634,352 € 1,525,939 90% € 3,106,716 € 2,859,342 € 2,628,250 € 2,413,440 € 2,214,911 € 2,032,665 € 1,866,700 € 1,717,017 € 1,583,617 € 1,466,498 € 1,365,661 100% € 2,870,672 € 2,630,874 € 2,407,358 € 2,200,125 € 2,009,173 € 1,834,503 € 1,676,116 € 1,534,010 € 1,408,186 € 1,298,644 € 1,205,384

% o f th e n etw o rk w ith G SM fa u lt in d ic ato r

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29 Table 13 Sensitivity analysis for the performance of Smart Cable Guard

Table 14 Sensitivity analysis for the valuation of SAIDI

Table 15 Sensitivity analysis for WACC

######## 0% 10% 20% 0%€ 5,433,680 € 5%€ 5,433,680 € 10%€ 5,433,680 € 15%€ 5,433,680 € 20%€ 5,433,680 € 25%€ 5,433,680 € 30%€ 5,433,680 € 35%€ 5,433,680 € 40%€ 5,433,680 € 45%€ 5,433,680 € 50%€ 5,433,680 € 55%€ 5,433,680 € 60%€ 5,433,680 € 65%€ 5,433,680 € 70%€ 5,433,680 € 75%€ 5,433,680 € 80%€ 5,433,680 € 85%€ 5,433,680 € 90%€ 5,433,680 € 95%€ 5,433,680 € 100%€ 5,433,680 € 30% 40% 50% 60% 70% 80% 90% 100% 5,217,089 € 5,000,499 € 4,783,908 € 4,567,317 € 4,350,726 € 4,134,135 € 3,917,544 € 3,700,953 € 3,484,362 € 3,267,771 5,195,743 € 4,960,519 € 4,728,009 € 4,498,213 € 4,271,130 € 4,046,761 € 3,825,105 € 3,606,163 € 3,389,935 € 3,176,421 5,174,396 € 4,920,540 € 4,672,110 € 4,429,108 € 4,191,534 € 3,959,386 € 3,732,666 € 3,511,373 € 3,295,508 € 3,085,070 5,153,050 € 4,880,560 € 4,616,212 € 4,360,004 € 4,111,938 € 3,872,012 € 3,640,227 € 3,416,583 € 3,201,081 € 2,993,719 5,131,703 € 4,840,581 € 4,560,313 € 4,290,900 € 4,032,341 € 3,784,638 € 3,547,788 € 3,321,794 € 3,106,654 € 2,902,368 5,110,357 € 4,800,602 € 4,504,415 € 4,221,796 € 3,952,745 € 3,697,263 € 3,455,349 € 3,227,004 € 3,012,226 € 2,811,017 5,089,010 € 4,760,622 € 4,448,516 € 4,152,692 € 3,873,149 € 3,609,889 € 3,362,910 € 3,132,214 € 2,917,799 € 2,719,667 5,067,664 € 4,720,643 € 4,392,617 € 4,083,587 € 3,793,553 € 3,522,514 € 3,270,471 € 3,037,424 € 2,823,372 € 2,628,316 5,046,317 € 4,680,663 € 4,336,719 € 4,014,483 € 3,713,957 € 3,435,140 € 3,178,032 € 2,942,634 € 2,728,945 € 2,536,965 5,024,971 € 4,640,684 € 4,280,820 € 3,945,379 € 3,634,361 € 3,347,766 € 3,085,593 € 2,847,844 € 2,634,518 € 2,445,614 5,003,624 € 4,600,704 € 4,224,921 € 3,876,275 € 3,554,765 € 3,260,391 € 2,993,154 € 2,753,054 € 2,540,090 € 2,354,263 4,982,278 € 4,560,725 € 4,169,023 € 3,807,171 € 3,475,169 € 3,173,017 € 2,900,716 € 2,658,264 € 2,445,663 € 2,262,912 4,960,931 € 4,520,746 € 4,113,124 € 3,738,066 € 3,395,573 € 3,085,643 € 2,808,277 € 2,563,474 € 2,351,236 € 2,171,562 4,939,585 € 4,480,766 € 4,057,225 € 3,668,962 € 3,315,976 € 2,998,268 € 2,715,838 € 2,468,684 € 2,256,809 € 2,080,211 4,918,238 € 4,440,787 € 4,001,327 € 3,599,858 € 3,236,380 € 2,910,894 € 2,623,399 € 2,373,895 € 2,162,382 € 1,988,860 4,896,891 € 4,400,807 € 3,945,428 € 3,530,754 € 3,156,784 € 2,823,520 € 2,530,960 € 2,279,105 € 2,067,955 € 1,897,509 4,875,545 € 4,360,828 € 3,889,530 € 3,461,650 € 3,077,188 € 2,736,145 € 2,438,521 € 2,184,315 € 1,973,527 € 1,806,158 4,854,198 € 4,320,849 € 3,833,631 € 3,392,545 € 2,997,592 € 2,648,771 € 2,346,082 € 2,089,525 € 1,879,100 € 1,714,808 4,832,852 € 4,280,869 € 3,777,732 € 3,323,441 € 2,917,996 € 2,561,396 € 2,253,643 € 1,994,735 € 1,784,673 € 1,623,457 4,811,505 € 4,240,890 € 3,721,834 € 3,254,337 € 2,838,400 € 2,474,022 € 2,161,204 € 1,899,945 € 1,690,246 € 1,532,106 4,790,159 € 4,200,910 € 3,665,935 € 3,185,233 € 2,758,804 € 2,386,648 € 2,068,765 € 1,805,155 € 1,595,819 € 1,440,755

Pe rf o rm an ce o f Sm art C ab le G u ard ######## 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% € 0.00€ 53,445 € 104,332 € 155,378 € 206,583 € 257,946 € 309,467 € 361,147 € 412,985 € 464,982 € 517,137 € 569,450 € 0.10€ 591,468 € 602,800 € 615,903 € 630,776 € 647,420 € 665,835 € 686,021 € 707,977 € 731,705 € 757,203 € 784,472 € 0.20€ 1,129,492 € 1,101,268 € 1,076,427 € 1,054,969 € 1,036,895 € 1,022,203 € 1,010,895 € 1,002,970 € 998,428 € 997,269 € 999,494 € 0.30€ 1,667,515 € 1,599,736 € 1,536,951 € 1,479,163 € 1,426,369 € 1,378,572 € 1,335,769 € 1,297,963 € 1,265,151 € 1,237,335 € 1,214,515 € 0.40€ 2,205,539 € 2,098,203 € 1,997,476 € 1,903,356 € 1,815,844 € 1,734,940 € 1,660,644 € 1,592,955 € 1,531,874 € 1,477,402 € 1,429,537 € 0.50€ 2,743,563 € 2,596,671 € 2,458,000 € 2,327,549 € 2,205,319 € 2,091,308 € 1,985,518 € 1,887,948 € 1,798,598 € 1,717,468 € 1,644,558 € 0.60€ 3,281,586 € 3,095,139 € 2,918,525 € 2,751,743 € 2,594,793 € 2,447,676 € 2,310,392 € 2,182,940 € 2,065,321 € 1,957,534 € 1,859,580 € 0.70€ 3,819,610 € 3,593,607 € 3,379,049 € 3,175,936 € 2,984,268 € 2,804,045 € 2,635,266 € 2,477,933 € 2,332,044 € 2,197,600 € 2,074,602 € 0.80€ 4,357,633 € 4,092,075 € 3,839,573 € 3,600,129 € 3,373,742 € 3,160,413 € 2,960,140 € 2,772,925 € 2,598,767 € 2,437,667 € 2,289,623 € 0.90€ 4,895,657 € 4,590,542 € 4,300,098 € 4,024,323 € 3,763,217 € 3,516,781 € 3,285,015 € 3,067,918 € 2,865,491 € 2,677,733 € 2,504,645 € 1.00€ 5,433,680 € 5,089,010 € 4,760,622 € 4,448,516 € 4,152,692 € 3,873,149 € 3,609,889 € 3,362,910 € 3,132,214 € 2,917,799 € 2,719,667 € 1.10€ 5,971,704 € 5,587,478 € 5,221,146 € 4,872,709 € 4,542,166 € 4,229,517 € 3,934,763 € 3,657,903 € 3,398,937 € 3,157,865 € 2,934,688 € 1.20€ 6,509,728 € 6,085,946 € 5,681,671 € 5,296,903 € 4,931,641 € 4,585,886 € 4,259,637 € 3,952,895 € 3,665,660 € 3,397,932 € 3,149,710 € 1.30€ 7,047,751 € 6,584,414 € 6,142,195 € 5,721,096 € 5,321,115 € 4,942,254 € 4,584,511 € 4,247,888 € 3,932,383 € 3,637,998 € 3,364,731 € 1.40€ 7,585,775 € 7,082,881 € 6,602,720 € 6,145,289 € 5,710,590 € 5,298,622 € 4,909,386 € 4,542,880 € 4,199,107 € 3,878,064 € 3,579,753 € 1.50€ 8,123,798 € 7,581,349 € 7,063,244 € 6,569,482 € 6,100,065 € 5,654,990 € 5,234,260 € 4,837,873 € 4,465,830 € 4,118,130 € 3,794,775 € 1.60€ 8,661,822 € 8,079,817 € 7,523,768 € 6,993,676 € 6,489,539 € 6,011,359 € 5,559,134 € 5,132,866 € 4,732,553 € 4,358,197 € 4,009,796 € 1.70€ 9,199,845 € 8,578,285 € 7,984,293 € 7,417,869 € 6,879,014 € 6,367,727 € 5,884,008 € 5,427,858 € 4,999,276 € 4,598,263 € 4,224,818 € 1.80€ 9,737,869 € 9,076,753 € 8,444,817 € 7,842,062 € 7,268,488 € 6,724,095 € 6,208,882 € 5,722,851 € 5,266,000 € 4,838,329 € 4,439,839 € 1.90€ 10,275,893 € 9,575,221 € 8,905,342 € 8,266,256 € 7,657,963 € 7,080,463 € 6,533,757 € 6,017,843 € 5,532,723 € 5,078,395 € 4,654,861 € 2.00€ 10,813,916 € 10,073,688 € 9,365,866 € 8,690,449 € 8,047,438 € 7,436,832 € 6,858,631 € 6,312,836 € 5,799,446 € 5,318,462 € 4,869,883

V al u at io n o f SA ID I ######## 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1.0%€ 5,403,853 € 5,024,418 € 4,662,931 € 4,319,392 € 3,993,801 € 3,686,158 € 3,396,463 € 3,124,716 € 2,870,917 € 2,635,066 € 2,417,163 2.0%€ 5,413,195 € 5,044,229 € 4,692,709 € 4,358,635 € 4,042,008 € 3,742,828 € 3,461,093 € 3,196,805 € 2,949,964 € 2,720,569 € 2,508,620 3.0%€ 5,423,008 € 5,065,427 € 4,724,745 € 4,400,965 € 4,094,084 € 3,804,104 € 3,531,025 € 3,274,846 € 3,035,567 € 2,813,188 € 2,607,710 4.0%€ 5,432,730 € 5,086,885 € 4,757,378 € 4,444,209 € 4,147,378 € 3,866,886 € 3,602,731 € 3,354,915 € 3,123,437 € 2,908,297 € 2,709,496 5.0%€ 5,441,974 € 5,107,788 € 4,789,383 € 4,486,759 € 4,199,916 € 3,928,854 € 3,673,573 € 3,434,073 € 3,210,353 € 3,002,415 € 2,810,258 6.0%€ 5,450,534 € 5,127,661 € 4,820,030 € 4,527,641 € 4,250,494 € 3,988,590 € 3,741,927 € 3,510,506 € 3,294,328 € 3,093,391 € 2,907,696 7.0%€ 5,458,333 € 5,146,286 € 4,848,968 € 4,566,378 € 4,298,516 € 4,045,382 € 3,806,976 € 3,583,298 € 3,374,348 € 3,180,126 € 3,000,632 8.0%€ 5,465,374 € 5,163,610 € 4,876,088 € 4,602,808 € 4,343,769 € 4,098,972 € 3,868,417 € 3,652,103 € 3,450,031 € 3,262,201 € 3,088,612 9.0%€ 5,471,698 € 5,179,664 € 4,901,413 € 4,636,945 € 4,386,260 € 4,149,359 € 3,926,240 € 3,716,904 € 3,521,351 € 3,339,581 € 3,171,594 10.0%€ 5,477,366 € 5,194,523 € 4,925,031 € 4,668,890 € 4,426,101 € 4,196,663 € 3,980,576 € 3,777,841 € 3,588,457 € 3,412,424 € 3,249,743 11.0%€ 5,482,440 € 5,208,274 € 4,947,054 € 4,698,778 € 4,463,448 € 4,241,063 € 4,031,623 € 3,835,128 € 3,651,578 € 3,480,973 € 3,323,313 12.0%€ 5,486,980 € 5,221,009 € 4,967,600 € 4,726,755 € 4,498,472 € 4,282,752 € 4,079,594 € 3,888,999 € 3,710,967 € 3,545,497 € 3,392,590 13.0%€ 5,491,043 € 5,232,814 € 4,986,787 € 4,752,963 € 4,531,341 € 4,321,922 € 4,124,705 € 3,939,691 € 3,766,879 € 3,606,269 € 3,457,862 14.0%€ 5,494,681 € 5,243,770 € 5,004,722 € 4,777,537 € 4,562,215 € 4,358,756 € 4,167,160 € 3,987,427 € 3,819,557 € 3,663,550 € 3,519,406 15.0%€ 5,497,939 € 5,253,952 € 5,021,506 € 4,800,604 € 4,591,244 € 4,393,426 € 4,207,152 € 4,032,420 € 3,869,230 € 3,717,584 € 3,577,480 W A C C

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30 The valuation of power outage is another important factor that has impact on the result. In 5.1.4 it is explained that there is no standard method to valuate SAIDI, and the valuation of SAIDI varies greatly by different grid operators. Table 14 gives the sensitivity analysis of the valuation of SAIDI (euro per minute per customer) from €0.00 to €2.00. The percentage of network with Smart Cable Guard is used as the other dimension of the data table to study the effect on the investment. When the valuation of SAIDI is rather low, around €0.00 to €0.10 per customer per minute, it is not encouraging for the grid operators to apply any new techniques, because that the total cost of investing on new techniques is approximately the same as or even higher than applying nothing. When the valuation of SAIDI is high, especially above €1.00, it is greatly recommended to use new techniques which can reduce the power outage time, thus reduce the high cost of SAIDI effectively.

Finally, the value of WACC is analyzed to see its impact. Table 15 shows that under 20% of network with Smart Cable Guard, less investment of capital is needed (the recognition of CAPEX and OPEX will be discussed in 6.3). Thus, the total cost does not vary greatly with the change of WACC. If the application of Smart Cable Guard is extended to a larger area of the network, the investment in capital will be a larger part of the total cost. The total cost will become more sensitive to the change of WACC, and the value of WACC would have a great impact on decision making.

6.3 Impact of the recognition of CAPEX and OPEX

According to IFRS it is difficult to distinguish the recognition of CAPEX and OPEX for the new techniques used in utility sector. The instructions in International Accounting Standard (IAS) 16 Property, Plant and Equipment (IFRS standard IAS 16) are:

The cost of an item of property, plant and equipment shall be recognized as an asset if, and only if:

(a) it is probable that future economic benefits associated with the item will flow to the entity; and

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31 (b) the cost of the item can be measured reliably.

The monitoring/digitalizing devices can bring benefits to the energy utility by reducing the power outages and improving the service to customers, which means it could be recognized as CAPEX. However, these devices are used for grid operation which could also be recognized as operational expense. Thus, the initial cost of the devices could be either capitalized or expensed. The periodical cost of the devices is mostly for maintenance which usually includes the replacement of components. Technically the periodical cost could also be recognized as CAPEX or OPEX.

Intuitively the initial cost (CINI) is recognized as CAPEX and operational cost (COP) is recognized as OPEX. This is also the approach that Alliander currently uses. Other approaches will result in changes in pretax income.

Table 16 shows the impact on pretax income if CINI is expensed rather than capitalized. The large investment in the beginning years (2017-2021) with a small part of depreciation leads to a remarkable decrease in pretax income. After year 10 (2027-2031) the roll-out of the devices is finished, and only depreciation continues, which results in a positive change in pretax income.

Table 16 Impact on pretax income if the initial cost is expensed rather than capitalized

2017 2018 2019 2020 2021

Capitalized initial cost (CAPEX) € 2,267,650 € 2,217,650 € 2,217,650 € 2,217,650 € 2,217,650

Depreciation of capitalized cost € 151,177 € 299,020 € 446,863 € 594,707 € 742,550

Change in pretax income if expensed -€ 2,116,474 -€ 1,918,630 -€ 1,770,787 -€ 1,622,944 -€ 1,475,100

2027 2028 2029 2030 2031

Capitalized initial cost (CAPEX) € 0 € 0 € 0 € 0 € 0

Depreciation of capitalized cost € 1,481,767 € 1,481,767 € 1,481,767 € 1,481,767 € 1,481,767

Change in pretax income if expensed € 1,481,767 € 1,481,767 € 1,481,767 € 1,481,767 € 1,481,767

Table 17 shows the change in pretax income if the periodical cost is capitalized rather than expensed. The change is always positive because of the less expense in financial

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32 report.

Table 17 Impact on pretax income if the periodical cost is capitalized rather than expensed

2017 2018 2019 2020 2021

Expensed periodical cost € 33,373 € 66,746 € 100,119 € 133,492 € 166,865

Change in pretax income if capitalized € 33,373 € 66,746 € 100,119 € 133,492 € 166,865

Inflation and price increase of the devices is neglected in the analysis’s above.

For energy utilities, the advantage of more OPEX is the tax benefit from less pretax income. While the advantage of more CAPEX is that the investment on new techniques and innovations brings positive impact on the key performance of the company as well as the company image.

The trend of applying these new techniques is that the supplier provides an application as a service, and the energy utility pays a subscription to supplier. In this way, the cashflow of the cost will be smoothed, thus less deviation in the change of pretax income when the cost is capitalized or expensed.

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33

7 Conclusion

As a capital-intensive industry, the investment on building Smart Grid consists of not only the initial cost on basic infrastructures such as power cables and substations, but also the monitoring/digitalizing and maintenance throughout the whole operational life of the assets. The Asset Life-cycle Cost model is an effective approach to gain an overview of the total cost. Different investment strategies can be compared based on the model to assist the decision making on the allocation of the investments. Instead of suggesting the financially optimal strategy, the LCC model provides an overview of the initial cost, operational cost and failure cost for each given strategy. The model presents the trade-off between the investment and the benefit, as well as the factors that may have influence on the results. Therefore, the (energy) utilities can choose the investment strategies that are most appropriate to meet their visions.

In this graduation study, an LCC model is built to calculate the total costs of the assets in electricity distribution grid during the whole life cycle. Three types of monitoring/digitalizing devices are included in the model: Smart Cable Guard, Global System for Mobile Communications (GSM) fault indicator and iRMU. The costs on these devices are analyzed and cost of power outages is estimated. Three scenarios are designed which represent three different investment strategies. The results of LCC show that a relatively lower investment on Smart Cable Guard and GSM fault indicator will lead to a higher reduction of power outage cost. The implementation of iRMU requires higher costs. However, it also results in a higher reduction of the power outage time. Therefore, investment on these new techniques would lead to a lower SAIDI and eventually a lower life-cycle cost. It is beneficial for energy utilities to apply these new techniques.

Furthermore, it is difficult to find the optimal (composition of) techniques because there are other factors that may have influence on the result. Sensitivity analysis is made for several essential input parameters.

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34 The performance of Smart Cable Guard has a great influence on whether it is the best cost-benefit efficient choice. If the performance achieves a higher level, the total cost would be lower with the same quantity of Smart Cable Guard. In the contrast, if the performance is lower, it may be more beneficial to apply other techniques than Smart Cable Guard.

The valuation of SAIDI has also large impact on decision making. When the valuation of SAIDI is rather low, around €0.00 to € 0.10 per customer per minute, it is not encouraging for the grid operators to apply any new techniques. When the valuation of SAIDI is high, especially above €1.00, it is greatly recommended to use new techniques which can reduce the power outage time, thus reduce the high cost of SAIDI effectively.

The last factor that analyzed in this study is the value of WACC. The result will be more sensitive to the value of WACC if more investment in capital is required in the strategy.

From the scenarios and sensitivity analysis in this study, it can be concluded that investment on digitalizing/monitoring devices could potentially lower the LCC cost of the electricity network. The optimal investment strategy depends on the devices and their performance, as well as the valuation of SAIDI and WACC.

Finally, the recognition of CAPEX and OPEX is studied and its impact on pre-tax income is analyzed. IFRS provides a guideline but not detail instructions on the recognition, especially for the implementation of new techniques for Smart Grid. For energy utilities, the advantage of more OPEX is the tax benefit from less pretax income. While the advantage of more CAPEX is that the investment on new techniques and innovations brings positive impact on the key performance of the company as well as the company image.

Alliander is now implementing the LCC model in the decision making of investment on Smart Grid. Future research could include the impact of the increasing decentralized

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35 generation e.g. solar panels and energy consumption e.g. electrical vehicles on electricity grid.

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36

Acknowledgement

I would like to express my greatest appreciation to my supervisor prof. Dennis Jullens for his guidance and help.

My gratitude goes also to Alliander N.V. for making this company project possible, especially those who directly supported me. I want to thank Peter van der Graaf, Ihsan Karakoc and Koen Verstappen for providing help and the essential technical information.

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37

Appendix

Table 18 Cashflow of Scenario 1 in the first five years

2017 2018 2019 2020 2021 Initial cost of Smart Cable Guard (SCG) - - - - - Installation and configuration SCG - - - - - Initial cost of GSM fault indicator - - - - - Inspection of fault indicator 125,500 125,500 125,500 125,500 125,500 Initial cost of iRMU - - - - -

Implementation -

Total Initial cost 125,500 125,500 125,500 125,500 125,500

Maintenance of Smart Cable Guard - - - - - Operational cost of Smart Cable Guard - - - - - Communication of Smart Cable Guard - - - - - Communication of GSM fault indicator - - - - - Reset of fault indicator (saved cost) - - - - - Communication cost of iRMU - - - - - Operational cost of iRMU - - - - - Total operational cost - - - - - Cost of SAIDI 5,380,236 5,380,236 5,380,236 5,380,236 5,380,236

2017 2018 2019 2020 2021 Initial cost of Smart Cable Guard (SCG) 18,531 18,531 18,531 18,531 18,531 Installation and configuration SCG 5,189 5,189 5,189 5,189 5,189 Initial cost of GSM fault indicator 85,513 85,513 85,513 85,513 85,513 Inspection of fault indicator 114,000 114,000 114,000 114,000 114,000

Implementation 50,000

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Maintenance of Smart Cable Guard 429 858 1,287 1,715 2,144 Operational cost of Smart Cable Guard 2,843 5,686 8,529 11,372 14,216 Communication of Smart Cable Guard 1,811 3,621 5,432 7,243 9,054 Communication of GSM fault indicator 10,662 21,325 31,987 42,650 53,312 Reset of fault indicator (saved cost) -1,000 -2,000 -3,000 -4,000 -5,000 Communication cost of iRMU - - - - - Total operational cost 14,745 29,490 44,235 58,981 73,726

Cost of SAIDI 5,158,739 4,937,242 4,715,745 4,494,248 4,272,751

2017 2018 2019 2020 2021 Initial cost of Smart Cable Guard (SCG) 18,531 18,531 18,531 18,531 18,531 Installation and configuration SCG 5,189 5,189 5,189 5,189 5,189 Initial cost of GSM fault indicator 85,513 85,513 85,513 85,513 85,513 Inspection of fault indicator 85,250 85,250 85,250 85,250 85,250 Initial cost of iRMU 2,023,168 2,023,168 2,023,168 2,023,168 2,023,168

Implementation 50,000

Total Initial cost 2,267,650 2,217,650 2,217,650 2,217,650 2,217,650

Maintenance of Smart Cable Guard 429 858 1,287 1,715 2,144 Operational cost of Smart Cable Guard 2,843 5,686 8,529 11,372 14,216 Communication of Smart Cable Guard 1,811 3,621 5,432 7,243 9,054 Communication of GSM fault indicator 10,662 21,325 31,987 42,650 53,312 Reset of fault indicator (saved cost) -1,000 -2,000 -3,000 -4,000 -5,000 Communication cost of iRMU 18,628 37,256 55,884 74,511 93,139 Total operational cost 33,373 66,746 100,119 133,492 166,865

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