Costs and Benefits of DG Connections to Grid System

Transcription

1 Costs and Benefits of DG Connections to Grid System D.M. Cao, D. Pudjianto, G. Strbac, A. Martikainen, S. Kärkkäinen, J. Farin (Imperial College London, UK and VTT Technical Research Centre of Finland, Finland) With contributions from Pablo Frias Tomás Gómez San Román Martin J.J. Scheepers Research Project supported by the European Commission, Directorate-General for Energy and Transport, under the Energy Intelligent Europe (EIE) Report no. Dec 26

2 Acknowledgement This document is a result of the DG-GRID research project and accomplished in Work package 3 - Analysis of DG costs and benefits and the development of grid business models - of the project. The DG-GRID research project is supported by the European Commission, Directorate-General for Energy and Transport, under the Energy Intelligent Europe (EIE) Programme. Contract no. EIE/4/15/S The sole responsibility for the content of this document lies with the authors. It does not represent the opinion of the Community. The European Commission is not responsible for any use that may be made of the information contained therein. Project objectives The objectives of the DG-GRID project are to: - To review the current EU MS economic regulatory framework for electricity networks and markets and identify short-term options that remove barriers for RES and CHP deployment. - To analyse the interaction between economic regulatory framework, increasing volume share of RES and CHP and innovative network concepts in the long-term. - To assess the effects of a large penetration of CHP and RES by analysing changes in revenue and expenditure flows for different market actors in a liberalised electricity market by developing a costs/benefit analysis of different regulatory designs and developing several business models for economic viable grid system operations by DSOs. - To develop guidelines for network planning, regulation and the enhancement of integration of DG in the short term, but including the opportunity for new innovative changes in networks in the long-term Project partners - ECN, NL (coordinator), - Öko-Institut e.v., Institute for Applied Ecology, Germany - Institute for future energy systems (IZES), Germany - RISØ National Laboratory, Denmark - University of Manchester, United Kingdom - Instituto de Investigación Tecnológica (ITT), University Pontificia Comillas, Spain - Inter-University Research Centre (IFZ), Austria - Technical Research Centre of Finland (VTT), Finland - Observatoire Méditerranéen de l'energie (OME), France For further information: Martin J.J. Scheepers Energy research Centre of the Netherlands (ECN) P.O. Box 1, NL-1755 ZG Petten, The Netherlands Telephone: , Telefax: , scheepers@ecn.nl, Project website: 2

3 Table of contents Acknowledgement...2 Table of contents...3 Glossary...5 Introduction Effect of DG connections on UK distribution network Presentation of the case studies Network description Percentage of lines and substations to be upgraded in rural networks Upgrade cost in rural networks Costs associated with active management Energy costs due to curtailment Implementation cost Benefits of active management in rural networks Benefits of active management in urban networks Effect of DG on distribution losses and distribution network capex Distribution losses and DG at 11kV Distribution network capex and DG Reduction of losses and provision of network capacity from micro generation Micro CHP Photovoltaics Summary of the effect of DG connections on UK networks Effect of DG connections on Finnish distribution network Finnish generic distribution network models kV network model kV network models Load profiles DG data Description of case studies DG penetration levels Allocation of DG Application of suitable network models for addressing different issues Operation philosophies used in the studies Modelling of intermittent and non intermittent DG Benefits and costs of DG connections Benefits of active management Studies on the generic rural network Studies on the generic urban network Additional cost associated with active management Costs and benefits of active management on Finnish networks Effect of DG on distribution network losses Effect of DG on distribution network Capex Effect of micro or mini generation on Finnish distribution network losses reduction and network capacity replacement Summary of the effect of DG connections on Finnish distribution networks

4 3 Summary References

5 Glossary AM Capex CHP DG DSO F&F FL GSP OH O&M PM PV UG Active Management Capital expenditure Combined Heat and Power Distributed Generator Distribution System Operator Fit and forget approach (or passive management approach) Fault level or a short circuit capacity Grid Supply Point. A point of supply from the national transmission system to the local system of the distribution network operator. Overhead (lines) Operation and maintenance Passive Management Photovoltaic Under-ground cables Currencies: Great Britain Pound ( ) and Euro ( ) are used in this report. One GBP is approximately equal to

6 Introduction This report describes the cost and benefits of DG to distribution networks. The analyses are based on the reference network models and evaluation methodology described in the report D7 Method for Monetarisation of Cost and Benefits of DG Options, D. Pudjianto, D.M. Cao, S. Grenard, G. Strbac, DG-Grid, Jan 26, Case studies were performed on the generic distribution network models which uses UK and Finnish network parameters to evaluate the impact of DG on network losses, voltage, fault level / short circuit power and investment schemes. The evaluation was carried out considering different DG technologies such as PV, CHP and small hydro. The impact of two different operating regimes namely passive and active network management has also been assessed. The results cover UK and Finnish cases based on rural and urban networks considering different characteristics of these two networks. Analyses of the results are presented in this report in details. The following three main sections of this report are summarised as below: 1. Section 2: UK distribution network model based on UK network characteristics is described. The results of several case studies in which the effect of DG on distribution network losses, reinforcement costs and capacity replacement values were analysed are presented and discussed. The benefit of active management on distribution network is evaluated comparing with traditional passive management policy. The results of the conducted research investigating the effect of different micro generation technologies (PV and CHP) connected at UK lower voltage network on network losses reduction and capacity replacement are also presented and discussed in this section. 2. Section 3: Finnish distribution network model based on Finnish network characteristics is described. Various impacts of DG on network costs and benefits have been investigated and analysed for Finnish network. The benefits of small hydro power generation connected at Finnish lower voltage network on network losses reduction and capacity replacement have also been quantified and the results of these studies are presented and discussed in this section. 3. Section 4: Conclusion is given deriving from the results of UK and Finnish networks. Various key factors which influence the effect of DG on network are summarised. 6

7 1 Effect of DG connections on UK distribution network 1.1 Presentation of the case studies The average generic distribution network which captures both rural and urban networks characteristics and is described in report D7 has been used to model 2 Grid Supply Points (GSPs) in the UK. Driven by the need for using renewable energy sources due to environmental concern, it can be foreseen that the penetration of DG in the UK distribution network will increase. However, the views on the UK picture of DG capacity, and DG location in the future are not yet clear. For that reason, four different penetrations of DG in the UK distribution network at 11kV were studied: 2.5GW; 5GW; 7.5GW and 1GW. Considering maximum load of total system is about 5GW, the ratio of DG s capacity to peak load capacity are 5% 1%, 15% and 2%. It is expected that these high penetrations of DG will lead to technical problems especially when DG is connected to a weak distribution network, which is the case of the 11kV voltage level in the UK, particularly in rural areas. Therefore, for each of the penetrations chosen above, four different allocation scenarios were assumed and investigated: DG connected over 5% of GSPs and 2/3 of the 11kV feeders (L) DG connected over 5% of GSPs and 1/3 of the 11kV feeders (LM) DG connected over 25% of GSPs and 2/3 of the 11kV feeders (HM) DG connected over 25% of GSPs and 1/3 of the 11kV feeders (H) Scenario L can be explained as follows. For 2.5 GW DG penetration, DG will be installed in 5% of GSPs, which is around 1 GSPs considering the total GSPs are around 2. For each GSP which has DG, DG will be connected at 2/3 of the 11 kv feeders. Other scenarios can be explained in the similar manner using the data above. For each scenario, active management is applied in each 11kV module of the GSP model, and DGs are assumed to have a unity power factor. In the case of the fit and forget philosophy (i.e. passive management), the distribution feeders are upgraded so that they can accommodate the full DG capacity without encountering any voltage or thermal issues. In the case of active management, two cases are studied for network reinforcement: Non-intermittent case : a flat output is used for all DGs installed in the UK. This profile was derived from the output profile of industrial medium/large size CHP. Reinforcement of equipment attached to a generator is required if more than.5% of the energy delivered is curtailed. Intermittent case : The DG profile was derived from the wind generation output profile which has around 3% load factor. It is observed that the energy curtailed is equal to 1% of the energy curtailed in the non-intermittent case. Investment is required if more than 2.5% of the energy delivered is curtailed. These two cases are described in this section as non-intermittent and intermittent generation respectively. 7

8 The study compares the incremental cost of upgrading feeders and substations under the fit and forget design and under active management of the network. However, implementing the latter comes at a cost. Therefore, under active management, to the incremental cost of upgrading feeders and substations must be added the cost of generation curtailment, and also the cost of implementing active management which includes investment cost in voltage measurement units and investment cost in control and communication systems. Even though the average GSP network was used, the costs due to voltage rise and thermal problems are defined as the costs in rural system because these problems occur typically in the weak 11kV rural feeders characterised by long and thin diameter of overhead line sizes. On the other hand, the costs associated with fault level issues are linked with urban networks where short cables are required. 1.2 Network description The generic distribution network models used for the different case studies presented in this chapter mimic the average characteristics of one GSP UK distribution networks in general with regard to the number, the length and the impedance of circuits and also the capacity and characteristics of transformers at each voltage level. The model is composed of a single 132kV module, one kind of 33kV module, two kinds of 11kV modules, a high loaded module and a low loaded module, and four different.4kv modules. The GSP substation is composed of 2 24MVA transformers. Eight 132kV overhead lines with an average length of 17 km connect the GSP substation to the 33 kv modules which are composed of 2 65MVA transformers. Each 33kV module includes 12 overhead lines of different lengths, varying between 1 and 2km, and connected to both high loaded and low loaded 11kV modules. The low loaded 11kV modules are composed of 2 7.5MVA transformers, whereas the high loaded 11kV modules are composed of MVA transformers. All these modules are built with eight 11kV overhead lines of different lengths, varying between 8 km and 25 km, and different loading conditions. The.4kV modules are designed as follows: the first one has a transformer capacity of 1kVA and two feeders with different loadings, the second one has a transformer capacity of 25kVA and two feeders with different loadings, the third one has a transformer capacity of 25kVA with four feeders connected, while the last one has a transformer capacity of 63kVA and four feeders connected. The average length of the.4 kv feeders is.35km, and in all cases the load and the distribution transformers are uniformly distributed along the.4kv and 11kV feeders respectively. Urban and rural networks tend to have different network characteristics. In order to be comparable, it is supposed that both networks are composed of the same number of circuits and transformers at each voltage level and of the same loading conditions as the current average GSP networks. Rural and urban network models data are listed in Table 1-1 to Table 1-5, where OH and UG for circuit type stand for overhead and underground respectively. 8

9 .4kV Module Table 1-1 Number and capacity of transformers in different voltage level subsections Voltage Number capacity of transformers level Model 1 Model 2 Model 3 Model 4 11kV/.4kV 2 x 1kVA 25 x 25kVA 25 x 25kVA 25 x 63kVA 33kV/11kV 12 x 2 x 7.5MVA 12 x 2 x 17.5MVA 132kV/33kV GSP substation Circuit 4 x 2 x 66MVA MVA Table 1-2 Circuit parameters for UK.4kV network model Type Size (mm 2 ) Length(km) % of load Load distribution 1 Rural Urban Rural Urban Rural Urban Rural Urban Module Circuit 1 UG 5 7/ L.I. U.D. 1 Circuit 2 UG 185/95 95/ U.D. U.D. Module Circuit 1 UG / L.I. U.D. 2 Circuit 2 UG 3 3/ U.D. U.D. Module 3 Module 4 Circuit 1 UG L.I. U.D. Circuit 2 UG 185/95 95/ U.D. U.D. Circuit 3 UG 185/95 185/ L.I. U.D. Circuit 4 UG 3/95 185/ U.D. U.D. Circuit 1 UG 185/5 185/ L.I. U.D. Circuit 2 UG 3/95 3/ U.D. U.D. Circuit 3 UG 3/95 3/ L.I. U.D. Circuit 4 UG 3 185/ U.D. U.D. 1 Load distribution types: U.D: Uniformly distributed; L.I.: Linearly Increasing 9

10 11kV module Module 1 Module 2 Circuit Table 1-3 Circuit parameters for UK 11kV network model Type Size(mm 2 ) Length(km) % of load Load distribution Rural Urban Rural Urban Rural Urban Rural Urban Rural Urban Circuit 1 OH UG 5 7/ L.I. U.D. Circuit 2 OH UG 3/ L.I. U.D. Circuit 3 OH UG 5 7/ U.D. U.D. Circuit 4 OH UG 3/ U.D. U.D. Circuit 5 OH UG 5 7/ L.I. U.D. Circuit 6 OH UG 3/ U.D. U.D. Circuit 7 OH UG 5 7/ U.D. U.D. Circuit 8 OH UG 3/ L.I. U.D. Circuit 1 OH UG 95/5 185/ U.D. U.D. Circuit 2 OH UG 3 185/ U.D. U.D. Circuit 3 OH UG 95/5 185/ L.I. U.D. Circuit 4 OH UG 3/95 185/ U.D. U.D. Circuit 5 OH UG 95/5 185/ L.I. U.D. Circuit 6 OH UG 3/95 185/ L.I. U.D. Circuit 7 OH UG 95/5 185/ U.D. U.D. Circuit 8 OH UG 3/5 185/ U.D. U.D. Table 1-4 Circuit parameters for UK 33kV network model 33kV Size(mm 2 ) Length(km) Type Module Rural Urban Rural Urban Circuit 1 OH 3 3/ Circuit 2 OH Circuit 3 OH 3 3/ Circuit 4 OH Circuit 5 OH Circuit 6 OH Table 1-5 Circuit parameters for UK 132kV network model 132kV Size(mm 2 ) Length (km) Type Module Rural Urban Rural Urban Circuit 1 OH Circuit 2 OH Circuit 3 OH Circuit 4 OH

11 It is assumed that all demand customers are connected at.4kv and is composed of 7% of residential customers without electrical heating, 1% of residential customers with electrical heating, 1% of commercial customers and 1% of industrial customers. The annual total load has a maximum of 225MW, a load factor of.55, and a power factor of.98. Figure 1-1 below shows typical annual load profiles in nine characteristic days used in the studies. Hourly and seasonal load variations were captured and used for load flow analysis. This figure is obtained by aggregating different type of loads, i.e. residential, industrial and commercial loads in the network. Distribution of the loads along feeders was also modelled. 25 MW Load Winter days Winter Saturday Winter Sunday Autumn/Spring days Autumn/Spring days Autumn/Spring Sunday Summer days Summer Saturday Summer Sunday Time Figure 1-1 Annual load profiles 1.3 Percentage of lines and substations to be upgraded in rural networks Figure 1-2 to Figure 1-4 present the percentage of 11kV and 33kV lines and 33/11kV substations that need to be upgraded for the different penetration scenarios of DG and for both types of management philosophy: fit and forget (F&F) and active management (AM). The case of 2.5GW penetration is not presented since none of the penetration scenarios of DG triggers any reinforcement costs. For capacities of 5GW and 7.5GW of DG installed over 5% of the GSPs in the UK, less lines require upgrade when DGs are allocated along 2/3 of the circuits than over 1/3 of the circuits, because the capacity of DG installed per line in the first case is low enough to not require reinforcement, whereas when the concentration increases a larger number of reinforcements are required. On the other hand, as the installed capacity of DG increases to 1GW in the UK, it is the opposite case. The capacity of DG installed per line is such that most of the lines where DG is installed require an upgrade, whatever the penetration density of DG. The higher the density of DG as in scenario H, the lower the number of 11kV lines which need to be upgraded. For the same reasons, when DG is installed over 5% of the GSPs, the number of lines to be reinforced for any penetration of DG is higher for high-density allocation of DG. Similar comments can be made for 33/11kV substations and 33kV lines: for high 11

12 penetration of DG, the higher the generators concentration in the GSP network, the lower the number of equipment to upgrade. However, the capacity upgrade required is higher for high density of DG and the costs associated are higher, as will be shown in the next sub-section. Percentage of scheme to be replaced (%) L (F&F) L (AM) LM (F&F) LM (AM) HM (F&F) HM (AM) H (F&F) H (AM) Penetration scenario (Management policy) 11kV lines 33/11kV transformers 33kV lines Figure 1-2 Percentage of lines and substations to be upgraded in the UK for a DG penetration of 5GW and for different penetration scenarios Percentage of scheme to be replaced (%) L (F&F) L (AM) LM (F&F) LM (AM) HM (F&F) HM (AM) Penetration scenario (Management policy) H (F&F) H (AM) 11kV lines 33/11kV transformers 33kV lines Figure 1-3 Percentage of lines and substations to be upgraded in the UK for a DG penetration of 7.5GW and for different penetration scenarios 12

13 Percentage of scheme to be replaced (%) L (F&F) L (AM) LM (F&F) LM (AM) HM (F&F) HM (AM) Penetration scenario (Management policy) H (F&F) H (AM) 11kV lines 33/11kV transformers 33kV lines Figure 1-4 Percentage of lines and substations to be upgraded in the UK for a DG penetration of 1GW and for different penetration scenarios The results obtained with this study also indicate that reinforcement of 11kV lines is driven by voltage constraints as 11kV feeders are characterised by long overhead lines, while the reinforcement of 33/11kV substations and 33kV lines is driven by thermal constraints. As described in the figures above, active management has a positive impact on the percentage of 11kV lines that need upgrading. 1.4 Upgrade cost in rural networks Figure 1-5 to Figure 1-7 illustrate the total UK upgrade capital costs disaggregated per voltage level and per scenario, and for both passive and active management. They reveal that upgrading 11kV lines is the main cost for all scenarios of penetration of DG. Nevertheless, the cost of upgrading 33/11kV substations increases with the capacity and the density of penetration of DG, and forms a large part of the reinforcement cost in scenario H, and for a penetration of 1GW. These figures also demonstrate how the upgrade costs can be reduced by using active management in 11kV modules. Since the unit cost of various assets is different, it is possible that the upgrade cost for different cases are different although the percentage of circuits to be upgraded in the associated cases are the same as presented in Figure 1-2-Figure 1-4. It can be concluded that if passive approach remains to be used, it will drive more capital investment and increase the cost for integrating DG. 13

14 Upgrade cost (M ) L (F&F) L (AM) LM (F&F) LM (AM) HM (F&F) HM (AM) Penetration scenario (Management policy) H (F&F) H (AM) 11kV lines 33/11kV transformers 33kV lines Figure 1-5 Upgrade costs for a DG penetration of 5GW 3 25 Upgrade cost (M ) L (F&F) L (AM) LM (F&F) LM (AM) HM (F&F) HM (AM) Penetration scenario (Management policy) H (F&F) H (AM) 11kV lines 33/11kV transformers 33kV lines Figure 1-6 Upgrade costs for a DG penetration of 7.5GW 14

15 Upgrade cost (M ) L (F&F) L (AM) LM (F&F) LM (AM) HM (F&F) HM (AM) Penetration scenario (Management policy) H (F&F) 11kV lines 33/11kV transformers 33kV lines H (AM) Figure 1-7 Upgrade costs for a DG penetration of 1GW In order to determine the operation and maintenance (O&M) cost, 1.4% is applied as the standard annual O&M rate at extra high voltage levels (United Utilities, 25). This value is assumed for assets at each voltage level for UK distribution networks. Using 7% rate of return and 2 years capital investment time scale, Table 1-6 shows the annuatised upgrade costs and O&M costs for UK rural networks with various DG penetration levels and management policies considering intermittent (I) and nonintermittent (NI) cases. DG capac ity 2.5 GW 5GW 7.5 GW 1 GW Table 1-6 Annuatised reinforcement cost and O&M cost in UK rural network (M /year) L LM HM H Cost AM AM AM AM AM AM AM type PM PM PM PM NI I NI I NI I NI Reinf O&M Reinf O&M Reinf O&M Reinf O&M Costs associated with active management AM I Curtailment cost The first cost associated with active management is the cost of curtailing output of distributed generator, in order not to violate voltage or thermal constraints in times of low demand. This cost can be associated to the opportunity lost of DG due to network constraints. Figure 1-8 shows the energy curtailed for each scenario of nonintermittent DG penetration. The cost associated is obtained by multiplying the amount of energy curtailed by the cost of electricity, which is assumed to be 2 /MWh in this study. 15

16 Energy custailed (GWh/year DG penetration (GW ) L LM HM H Figure 1-8 Energy curtailed for non-intermittent generation Implementation cost The second cost associated with active management is its implementation cost. Implementation of generation curtailment necessitates the installation of voltage measurement schemes at the generator point of connection as described in (Liew, S.N., 22). A reliable communication link between the terminal of the DG and the DSO centre is also required. Besides, in a coordinated area-based voltage control, measurements and communication are also required between a 33/11kV substation and the DSO centre. In this study we suppose that the cost of active management is flat irrespective of the considered level of DG penetration. This is because the cost of active management is assumed for simplicity to be fixed, irrespective of the number of feeders with voltage rise problems as long as there is at least one problem feeder. In rural areas, the cost of implementing active management is therefore supposed to be 1, per DG. In urban areas, the cost of implementing active management is assumed 1, per substation. However, in practice, the cost of active management has variable cost components and depending on the number of problem feeders, the cost of enabling active management varies. 1.6 Benefits of active management in rural networks Table 1-7 and Figure 1-9 compare the range of reinforcement and capitalised operation costs for different penetrations of DG in the UK distribution between passive management and active management with all its associated costs described above: energy reduction cost due to curtailment, cost of implementing active management and cost of reinforcement if required. In Table 1-7, the first row in the active management column corresponds to the reinforcement costs for the intermittent case while the second row corresponds to the non-intermittent case. The underlined figures correspond to the cost of implementing active management. 16

17 Table 1-7 Reinforcement cost (RC) of upgrading feeders and substations in rural system (in M ) for Passive (PM) and Active (AM) management (considering the intermittent and non-intermittent cases) and cost of implementing (CoI) active management Scenario L LM HM H DG capacity PM AM PM AM PM AM PM AM RC RC CoI RC RC CoI RC RC CoI RC RC CoI 2.5GW 5GW 7.5GW 1 1GW Cost (M ) Installed capacity (GW) Passive rural network Active rural network Figure 1-9 Ranges of reinforcement cost of upgrade in rural areas The benefits of active management are clearly illustrated in Figure 1-9 for each penetration of DG. For an installed capacity of 5GW, up to 5% of the cost of upgrading the system could be saved by applying active management, while this figure varies between 15 and 4% for a penetration of 1 GW. 17

18 Table 1-7 also suggests that reinforcement costs required in the intermittent case are smaller than for the non-intermittent case. This is due to the lower occurrence of the worst-case situation of high output of DG at times of low demand in the intermittent case. 1.7 Benefits of active management in urban networks In most cases a rise in system fault level requires the switchgear to be replaced with equipment of a higher fault rating. In the developed UK model, the entire switchboard of a substation is replaced if the fault rating at that location is exceeded. The costs of new switchboards used for each voltage level are presented in Table 1-8. Table 1-8 New switchboard cost Substation GSP 132/33kV 33/11kV New switchboard cost ( ) 3,146, 1,79, 497,35 Average system fault levels are assumed at each voltage level; 35MVA at 11kV and 1,MVA at 33kV, and two different fault level headrooms available at each voltage level are examined. The headroom is used to determine how much DG can be added to various parts of the DSO networks before switchgear fault ratings are exceeded. The two following cases are investigated: % headroom; in this case the introduction of DG at 11kV requires the upgrade of the switchgear in the 33/11 kv substation. 1% headroom; in this case the introduction of DG at 11kV requires the upgrade of the switchgear in the 33/11 kv substation only if its contribution to fault level is superior to 1% of the switchgear rating. Table 1-9 and Figure 1-1 provide the range of full cost of upgrading switchboards in all the penetration scenarios of DG in urban systems. For active management, the cost of implementing an active managed network is added to the cost of upgrading switchboards. As for rural systems, the benefits of active management can be clearly identified. For low DG penetration, more than half of reinforcement costs could be saved by applying active management. 18

19 Table 1-9 Reinforcement cost of switchboards (RC) for two different headrooms for passive (PM) and active (AM) management in urban system (in M ) and cost of implementing (CoI) active management Scenario L LM HM H DG capacity 2.5GW 5GW 7.5GW 1GW Head- room PM RC AM RC CoI PM RC AM RC CoI % % % % 398 % % % % PM RC RC AM CoI PM RC RC AM CoI Cost (M ) Installed capacity (GW) Passive urban network Active urban network Figure 1-1 Ranges of reinforcement costs in urban areas Using the same assumption as for rural network, 1.4% is applied as the standard operation and maintenance (O&M) rate. The annuatised upgrade costs and O&M cost for urban network with % and 1% headrooms are listed in Table 1-1 and Table

20 Table 1-1 Annuatised reinforcement cost and O&M cost in urban network with % headroom (M /year) Cost GW L(PM) L(AM) LM(PM) LM(AM) HM(PM) HM(AM) H(PM) H(AM) type 2.5 Reinf O&M Reinf O&M Reinf O&M Reinf O&M Table 1-11 Annuatised reinforcement cost and O&M cost in urban network with 1% headroom (M /year) Cost GW L(PM) L(AM) LM(PM) LM(AM) HM(PM) HM(AM) H(PM) H(AM) type 2.5 Reinf O&M 5 Reinf O&M Reinf O&M Reinf O&M Effect of DG on distribution losses and distribution network capex Distribution losses and DG at 11kV Quantifying the variation in annual energy losses due to the introduction of DG with constant output in the UK distribution network is the objective of this section. Due to lacking the number of GSPs for rural and urban networks for the UK, the corresponding results shown below were conducted using average network model, which captures the average characteristics of the UK rural and urban distribution networks, rather than rural and urban network models themselves. And the results are believed to be appropriate enough to show the effect of DG on losses. Since losses at.4 kv are not influenced by the connection of DG at 11kV, the different results and figures of this section present the annual energy losses in the entire UK distribution network apart from the low voltage level. The presence of DG at 11kV changes the flow patterns and therefore the losses incurred in transporting electricity through transmission and distribution networks. The first thought is that DG contributes to power loss reduction as the generation energy flow is generally against the major net flow. This is, however, normally but not necessarily true. The impact of DG on losses depends on the penetration and the location of DG in the network as described in Figure 1-11 to Figure Low penetration of DG reduces the losses, as the generation is absorbed by local load, 2

21 which then reduces the flow in the 11kV feeder and in the voltage levels above. However, as the penetration of DG increases, generation starts to exceed local demand, particularly in low loaded lines and at time of low demand, leading to a reverse flow in the 11kV feeders. This reverse flow increases the losses at 11kV and in some cases at higher voltage levels too. Figure 1-11 describes the behaviour of annual energy losses for the penetration scenario where DG is allocated to 2/3 of the 11 kv circuits of 5% of the GSPs in the UK. In that case, for any penetration of DG, the losses in the UK distribution network are lower than when no DG is connected to the network, and a minimum in energy losses is obtained for a DG penetration of 5GW. For low penetration of DG, active management is not required since the system does not need any reinforcement. However for high penetration of DG, the use of active management tends to increase the losses since feeders have smaller sizes than for passive management. For a penetration of 1GW, the corresponding increase in cost of losses is about 3M /year in the UK network assuming the electricity cost is 2 /MWh. 2 Losses (%) Penetration of DG (GW) Passive management Active management Figure 1-11 Losses in UK s distribution network (except for LV) for scenario L Figure 1-12 and Figure 1-13 represent the losses for the penetration scenarios where DG is allocated to 1/3 of the 11 kv circuits of 5% of the GSPs in the UK and DG is allocated to 2/3 of the 11 kv circuits of 25% of the GSPs in the UK respectively. The comments are generally similar to before: the losses for low penetrations of DG (2.5GW and 5GW) are smaller than if no DG is connected to the network. However, as the penetration increases the losses tend to increase in the UK distribution network. Moreover, the losses in these two cases are higher than in the case with a less dense penetration of DG. Similarly to the previous case, active management has a negative impact on losses: energy losses increase by about 15% in the case of high penetration of DG when active management is applied. However the corresponding increases in cost of losses (about 15M /year for a penetration of 1GW in scenario HM) do not question the benefits of applying active management. 2 Cost of losses is calculated from the annual energy losses multiplied by the specified energy cost. 21

22 Losses (%) Penetration of DG (GW) Passive management Active management Figure 1-12 Losses in UK s distribution network (except for LV) for scenario LM 6 5 Losses (%) Penetration of DG (GW) Passive management Active management Figure 1-13 Losses in UK s distribution network (except for LV) for scenario HM Figure 1-14 depicts the losses for the penetration scenario where DG is allocated to 1/3 of the 11 kv circuits of 25% of the GSPs in the UK, which corresponds to a highdensity penetration. In this scenario, any penetration of DG increases the losses in the network. This rise can reach 1% when 1GW of DG is connected to the network. 22

23 Losses (%) Penetration of DG (GW) Passive management Active management Figure 1-14 Losses in UK s distribution network (except for LV) for scenario H Distribution network capex and DG Because distributed generators are located near to consumers, the net demand to be supplied from transmission and distribution networks can decrease, postponing the need to reinforce the system in case of load growth or to reduce the investment required in case of equipment replacement. (Mendez, V.H., et al., 23) assessed the investment deferral in radial distribution networks with distributed generation based on a part of a semi-rural distribution model. However the methodology presented above enables us to study the impact of DG with a flat output on investment deferral in the entire distribution network of the UK for different penetration scenarios (and therefore on security). Table 1-12 presents the maximum flow in the Grid Supply Point of networks where DG is connected. The low-density penetration of DG corresponds to the scenarios L and LM presented above while the high density corresponds to the scenarios HM and H. The maximum flow when no DG is connected to the network is 225MVA in the GSP. The DSO could therefore benefit in the case of a low-density penetration of DG, as the capacity required in the GSP is 2 198MVA instead of 2 225MVA. The minimum flow is obtained for a high density penetration of 7.5GW of DG. It is interesting to note that for high and dense penetrations of DG, the maximum flow in GSPs occurs in times of low demand when power is exported from the distribution network to the transmission network. Similarly, the introduction of DG at 11kV in the network changes the flow in the 132/33kV substations. Table 1-13 describes the maximum flow in each 132/33kV substation when DG is introduced at 11kV. When no DG is installed in the network, the maximum flow is 55MVA. 23

24 Table 1-12 Maximum flow (in MVA) in GSP substations for GSPs with DG DG scenario DG penetration Maximum flow (in MVA) in GSP substations Low density High density 2.5GW GW GW GW Table 1-13 Maximum flow (in MVA) in 132/33kV substations for GSPs with DG DG scenario DG penetration Maximum flow (in MVA) in 132/33kV substations Low density High density 2.5GW GW GW GW 3 35 Using the figures in Table 1-12 and Table 1-13, one can derive the potential value (in M) of DG in replacing distribution network assets in the entire UK. These potential benefits are presented in Table 1-14 in capitalised value. Table 1-14 Potential value of DG in replacing distribution network assets ( M) DG scenario DG penetration Replacement value of DG ( M) Low density High density 2.5GW GW GW GW For low densities of DG penetration at 11kV, the benefits obtained in asset replacement cost increase with the penetration of DG. However the high density scenario, combined with very high penetration of DG tends to decrease these benefits since a high capacity is required at the substations for the upward transfer of power from the 11kV voltage level to the transmission network in times of low demand. 24

25 1.9 Reduction of losses and provision of network capacity from micro generation The Engineering Recommendation G83/1 (ER G.83/1, 23) defines the capacity constraints recommendations for the connection of small scale embedded generators in parallel with public low-voltage distribution networks up to 16A per phase, equating 3.68kVA for a 23V single phase connection. Electricity from microgeneration is both produced and consumed on the premises by technologies such as micro wind, micro hydro, fuel cells, photovoltaics (PV) or micro combined heat and power (micro CHP). In this research only micro CHP and photovoltaics were studied because typical daily and seasonal energy outputs can be used for these two technologies. In the working paper (Distributed Generation Coordination Group, 24) the different economic benefits delivered by micro generation are summarised as follows: It will reduce emissions of COx, SOx, NOx and particulates It will reduce the total capacity needed within networks It will reduce the need for peak provision in electricity networks It will reduce power system losses It will deliver major energy efficiency gains It will reduce the amount of large-scale centralised generating capacity The results presented below quantify the reduction of distribution energy losses and the reduction in total capacity needed for different penetration scenarios of micro CHP and PV in the UK distribution network. Therefore cases studies with 2.5%/5%/7.5%/1% of all UK customers with micro generation over 2%/5% of GSPs in the UK are displayed Micro CHP Combined Heat and Power (CHP) is the simultaneous production of electrical power and useful heat. In the case the electrical power of domestic micro CHP is consumed inside the host premises although any surplus or deficit is exchanged with the utility distribution system. The heat generated by micro CHP is used for space heating inside the host premises. Therefore the electrical energy output of micro CHP is driven by the heat requirements of consumers. Figure 1-15 illustrates the normalised generation profile of micro CHP used in this study where it was assumed the output of micro CHP is nil during the summer. Furthermore, it was assumed that 25% of the customers with micro CHP had a technology with a capacity of 3kW and 75% with a capacity of 1.1kW. 25

26 1.2 Micro CHP electric generation (pu) Time (Hr) Figure 1-15 Normalised output of micro CHP Table 1-15 gives the annual energy losses and the maximum flow entering in the distribution network for different proportion of customers with micro CHP allocated to 5% of the GSPs in the UK, while Table 1-16 gives the same features when micro CHP is allocated amongst only 2% of the GSPs in the UK. The increase in the proportion of customers with micro CHP leads to a significant reduction in energy losses (from 6.1% to 4.39% in the average network). This reduction is important because the maximum output of micro CHP occurs at time of high customers demand decreasing the transfer of power in the distribution network in times of high demand. For the same reasons the maximum flow entering the GSP network decreases as the capacity of micro CHP increases up to a point where the maximum flow entering the network occurs in at a time when no electricity is produced by micro CHP (like in summer for instance). Similarly to the comments made in section 2.8.2, and since micro CHP generation coincides with peaks of demand, adding micro CHP generation capacity at the low voltage end of the power system defers or removes the need for new network capacity and reduce the utilisation of existing network. This leads therefore to benefits to DSOs. Table 1-15 Losses and maximum flow when micro CHP is allocated to 5% of GSPs in the UK Proportion of Losses in GSP with generation (%)/Losses in the customers entire UK network (%) Maximum flow entering the GSP (in MVA) Average network Rural network Urban network % % 5.6 / % 5.16 / % 4.75 / % 4.39 /

27 Table 1-16 Losses and maximum flow when micro CHP is allocated to 2% of GSPs in the UK Proportion of customers Losses in GSP with generation (%)/Losses in the entire UK network (%) Maximum flow entering the Average Rural network Urban network GSP (in MVA) network % % 4.93 / % 4.5 / % 3.48 / % 3.18 / Photovoltaics Photovoltaic generation corresponds to the direct conversion of sunlight to electricity. Interest is now focused on incorporating the photovoltaic modules into buildings and houses. Thus these small PV installations would be connected directly into customers circuits and so interface with the low-voltage distribution network. Figure 1-16 describes the normalised energy profile used in this study based on (Jenkins, N., 1995) to model the output of PV. It is assumed that customers would have a module with a capacity of 1kW. Normalised electric generation of PV (pu) Time (Hr) Summer Autumn/Spring Winter Figure 1-16 Normalised output of PV Similarly to Table 1-15 and Table 1-16 for micro CHP, Table 1-17 and Table 1-18 describe the distribution losses for different penetrations of PV at.4kv. The impact of PV on losses and on the provision of network capacity is less significant then the impact of micro CHP. Indeed, PV in the UK produce electric energy in times of low demand (during summer daytime), but not during peak demands such as the evening of winter weekdays. Therefore the maximum flow entering the distribution network is not affected by the installation of PV (251.3MVA in this example), and even if losses decrease with higher penetrations of PV, the reduction is not significant. 27

28 Table 1-17 Losses and maximum flow when PV is allocated to 5% of GSPs in the UK Losses in GSP with generation (%)/Losses in the entire UK network (%) Proportion of customers with PV Maximum flow entering the GSP (in MVA) Average network Rural network Urban network % % 5.93 / % 5.74 / % 5.57 / % 5.41 / Table 1-18 Losses and maximum flow when PV is allocated to 2% of GSPs in the UK Losses in GSP with generation (%)/Losses in the entire UK network (%) Proportion of customers with PV Maximum flow entering the GSP (in MVA) Average network Rural network Urban network % % 5.65 / % 5.26 / % 4.95 / % 4.71 / Summary of the effect of DG connections on UK networks Corresponding to Table 1-7 and Table 1-9, Table 1-19 and Table 1-2 show the incremental cost ( /kw) for network assets reinforcement in rural and urban networks respectively. The second columns in active management case show the incremental implementation cost of active management. In Table 1-19 for rural networks, the first row in active management case is for intermittent case and the second row is for nonintermittent case. In Table 1-2 for urban networks, the first row corresponds to % headroom case and the second row corresponds to 1% headroom case. From Table 1-19 and Table 1-2, we can see that for each DG capacity, in the low and medium DG penetration density cases, the incremental cost can be reduced significantly if active network is applied. While with high penetration level, e.g. for 1GW H penetration scenario, the incremental cost is similar or larger in active management comparing with passive management taking into account the implementation cost of active management. 28

29 Table 1-19 Incremental cost for assets reinforcement with passive (PM) and active (AM) management for various DG penetration scenarios for rural networks ( /kw) Scenario L LM HM H DG capacity PM AM PM AM PM AM PM AM IC IC CoI IC IC CoI IC IC CoI IC IC CoI 2.5GW 5GW GW GW Table 1-2 Incremental cost for assets reinforcement with passive (PM) and active (AM) management for various DG penetration scenarios for urban networks ( /kw) Scenario L LM HM H DG capacity Head- PM AM PM AM PM AM PM AM room IC IC CoI IC IC CoI IC IC CoI IC IC CoI % GW 1% 32 % GW 1% % GW 1% % GW 1% Table 1-21 gives the incremental benefit of DG on network capacity replacement, the value is on average around 76 /kw for all the cases except the case of 1GW penetration with high density level due to large reversed power flow. Table 1-21 Incremental replacement benefit of DG ( /kw) DG scenario Incremental replacement value of DG DG penetration Low density High density 2.5GW GW GW GW Incremental value of Micro-CHP on network capacity replacement is shown as Table The value is from /kw to 83.6 /kw. Since the reason mentioned in 29

30 section 2.9.2, the maximum power flow does not change with PV installation to the network for each scenario. The incremental value of PV on network capacity replacement is zero and the table is ignored here. Table 1-22 Incremental benefit of Micro-CHP on replacing distribution network assets ( /kw) Proportion of customers Incremental benefit ( /kw) Generator allocated to 5% of GSPs Generator allocated to 2% of GSPs 2.5% % % %

31 2 Effect of DG connections on Finnish distribution network 2.1 Finnish generic distribution network models In order to estimate the costs and benefits of DG connections to Finnish distribution grid, a number of analysis have been conducted for various DG penetration and concentration levels. Studies were performed on generic one-gsp distribution network models. These generic models use several typical circuit parameters, e.g. conductor sizes, lengths, impedances, costs etc. In developing the generic models, different characteristics of networks for different voltage levels and for different network types (rural and urban) are considered, in which the parameters of the networks are obtained from VTT (Technical Research Centre of Finland). Finnish distribution networks comprise three operating voltage levels: 11kV, 2kV and.4kv. In developing the generic network models, 11kV networks are excluded from the model for simplicity. Focus of the studies was on the 2 kv and.4 kv networks where a number of technical issues will arise with high DG penetrations. It is envisaged that less effect of technical issues DG will bring to the 11 kv networks. Finnish distribution networks are a mix of urban and rural type networks including both short 2 kv feeders in city areas and long overhead line feeders in surrounding areas. In deriving the parameters for the generic models, the Southern Finland is considered as urban area and the rest of Finland as rural. In total, there are 32 GSPs for rural and 14 GSPs for urban networks respectively. In the next sections, models for.4kv and 2kV networks are described in more details kV network model There are six typical.4kv network models in a rural GSP network and five.4 kv models in an urban GSP network. A single transformer is installed in each 2kV/.4kV substation. The total number of transformers installed and their capacity used in our models are listed in Table 2-1. Table 2-1 Models for 2/.4kV rural and urban substations Network Number capacity of transformers area Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 2 x 64 x 96 x 64 x 64 x 12 x Rural 16kVA 3kVA 5kVA 1kVA 16kVA 315kVA 35 x 18 x 11 x 15 x 12 x Urban 3kVA 5kVA 63kVA 8kVA 1MVA In total there are 1,4.4kV circuits included for the rural model and all of them are Aerial Cables (AC) lines with an average length of.5km for each circuit. For the urban network model, there are 3135 circuits with an average length of.3km for each circuit, among which 2885 circuits are underground (UG) cables and the rest are AC lines. 31