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Distribution Planning With reliability Options for Distributed Generation

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How to delay investments in distribution grids thanks to DG

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Distribution Planning With reliability Options for Distributed Generation

  1. 1. ARTICLE IN PRESS G Model EPSR 2930 1–8 Electric Power Systems Research xxx (2009) xxx–xxx 1 Contents lists available at ScienceDirect Electric Power Systems Research journal homepage: www.elsevier.com/locate/epsr F 1 Distribution planning with reliability options for distributed generation David Trebolle a,∗ , Tomás Gómez b , Rafael Cossent b , Pablo Frías b OO 2 a 3 Unión Fenosa Distribución, C/Antonio López, 19, 28026 Madrid, Spain b 4 Instituto de Investigación Tecnológica, Escuela Técnica Superior de Ingeniería, Universidad Pontificia Comillas, C/Quintana 21, 28008 Madrid, Spain 5 6 a r t i c l e i n f o a b s t r a c t PR 7 8 Article history: The promotion of electricity generation from renewable energy sources (RES) and combined heat and 9 Received 14 December 2007 power (CHP) has resulted in increasing penetration levels of distributed generation (DG). However, large- 10 Received in revised form 30 March 2009 scale connection of DG involves profound changes in the operation and planning of electricity distribution 11 Accepted 2 September 2009 networks. Distribution System Operators (DSOs) play a key role since these agents have to provide flex- Available online xxx ibility to their networks in order to integrate DG. Article 14.7 of EU Electricity Directive states that DSOs 12 should consider DG as an alternative to new network investments. This is a challenging task, particu- 13 Keywords: 14 15 16 Distributed generation Distribution planning Reliability options D larly under the current regulatory framework where DSOs must be legally and functionally unbundled from other activities in the electricity sector. This paper proposes a market mechanism, referred to as reliability options for distributed generation (RODG), which provides DSOs with an alternative to the TE 17 Firmness investment in new distribution facilities. The mechanism proposed allocates the firm capacity required to DG embedded in the distribution network through a competitive auction. Additionally, RODG make DG partly responsible for reliability and provide DG with incentives for a more efficient operation taking into account the network conditions. © 2009 Published by Elsevier B.V. EC 18 1. Introduction Distribution networks were not originally designed to accom- 37 modate generation. Hence, increasing penetration levels of DG are 38 19 In the context of the European Energy Policy, ambitious tar- causing profound changes in the planning, operation and mainte- 39 RR 20 gets have been set concerning improvements in energy efficiency nance of distribution networks. In order to integrate DG effectively 40 21 and the use of renewable energy sources (RES) [1]. The electric- and efficiently, the electricity distribution networks should no 41 22 ity sector is meant to play a major role in the achievement of the longer be passive elements that transmit electricity in one direc- 42 23 aforementioned goals. Different economic support schemes for the tion. They should become active elements where control, safety and 43 24 production of electricity from RES and combined heat and power flexibility are very relevant factors. 44 25 (CHP) have been implemented at national level. As a consequence The impact of DG immersed in distribution networks is currently 45 CO 26 of these support schemes, new generation technologies have been being analysed in detail. Various aspects are being considered: 46 27 developed over the last years. Several of these technologies are gen- network planning [3], operation and maintenance [4], ancillary ser- 47 28 erally applied on medium and small-scale installations. This fact vices [5,6], quality of service [7] and regulatory aspects [8]. 48 29 has brought about a new concept in the context of electricity pro- This paper focuses on the possibility to substitute new network 49 30 duction called distributed generation (DG). Other terms used with investments thanks to the contribution of DG to meet peak demand. 50 31 similar meanings are embedded generation, distributed energy Article 14.7 of the European Electricity Directive [9] states that 51 UN 32 resources, dispersed generation or decentralised generation. DSOs shall consider DG as an alternative to network upgrading or 52 33 The definition of the term DG has been analysed in detail [2]. In replacing network elements. However, this challenge is not exempt 53 34 this paper, DG will be considered as electricity generation systems of difficulties. In some countries, DSOs may own DG. Therefore 54 35 connected to distribution networks, characterized by their reduced they have the possibility of installing either new network elements 55 36 size and located near consumption points. or new generation units [10,11]. Nevertheless, under the current 56 European regulatory framework, DSOs must be at least legally and 57 functionally unbundled from other activities in the electricity sec- 58 tor. Electricity distribution remains a regulated activity, whereas 59 generation has become a liberalised one. Therefore, DSOs have no 60 ∗ Corresponding author. Tel.: +34 91 2015361. direct control over the location and operation of DG. 61 E-mail addresses: dtrebolle@unionfenosa.es (D. Trebolle), Tomas.Gomez@iit.upcomillas.es (T. Gómez), Rafael.Cossent@iit.upcomillas.es Two main problems are derived from this situation. On the one 62 (R. Cossent), Pablo.Frias@iit.upcomillas.es (P. Frías). hand, the responsibility of continuity of supply resides 100% on 63 0378-7796/$ – see front matter © 2009 Published by Elsevier B.V. doi:10.1016/j.epsr.2009.09.004 Please cite this article in press as: D. Trebolle, et al., Distribution planning with reliability options for distributed generation, Electr. Power Syst. Res. (2009), doi:10.1016/j.epsr.2009.09.004
  2. 2. ARTICLE IN PRESS G Model EPSR 2930 1–8 2 D. Trebolle et al. / Electric Power Systems Research xxx (2009) xxx–xxx 64 DSOs. Thus if DG is not producing during hours of peak demand, 2.1. The electricity distribution business 128 65 then DSOs are made responsible for possible interruptions. On the 66 other hand, DG perceives no incentives to guarantee production The electricity distribution business is a natural monopoly 129 67 during high demand periods. Therefore, specific mechanisms that because it presents decreasing average costs and strong economies 130 68 ensure DG production during key system periods and allow DSOs of scale. Due to its natural monopoly characteristic, the electricity 131 69 to consider DG as an alternative to new facilities are deemed nec- distribution business is regulated in terms of pricing and network 132 70 essary. access. 133 71 Several schemes of this kind, such as capacity payments or After the recent vertical disintegration movements and mar- 134 72 reliability options, have been developed concerning large-size gen- ket deregulation, traditional regulation of distribution, known as 135 73 eration connected to the transmission grid [12,13]. These have cost of service or rate of return regulation, has evolved towards 136 74 three main objectives: ensure the existence of sufficient power incentive regulation. Cost of service regulation is based on remu- 137 F 75 generation installed to provide a suitable reserve, achieve a stable nerating DSOs according to their costs, thus ensuring profitability 138 76 income for existing generators and new market entrants, and guar- of new network investments. On the other hand, incentive regu- 139 77 antee that generation may meet demand at all times. Nonetheless, lation pays special attention to increasing efficiency by lowering 140 OO 78 these mechanisms generally do not take into account the grids. It costs, while reducing energy losses and improving quality of ser- 141 79 is assumed that the network is not an obstacle to achieve this bal- vice. The most common incentive regulation approaches used to 142 80 ance, since transmission grids are deemed to be sufficiently robust regulate European distribution utilities are price cap and revenue 143 81 and meshed. cap. These formulas establish a 4–5 year regulatory period that 144 82 However, balancing DG and local demand in distribution net- decouples actual costs from regulated revenues. This is the basis 145 83 works is a very different situation. Distribution networks are of the incentives for DSOs to reduce costs [16]. 146 PR 84 generally either radial or operated this way. Hence, the network Once the distribution remuneration mechanism has been estab- 147 85 plays a key role within the generation-demand balance, as the pres- lished, network tariffs are designed. These allow collecting from 148 86 ence and/or absence of this generation may cause overloads in the customers the costs recognized by the regulator, which constitute 149 87 distribution network. the revenues of DSOs. In this regulatory framework, the primary 150 88 The contribution of DG to cover peak load of distribution facil- mission of a DSO as owner and operator of the distribution net- 151 89 ities has already been assessed by some authors [14,15]. These work system consists of transporting energy from the transmission 152 90 studies perform probabilistic analyses over DG production profiles. grid border points to the end consumers. This mission involves the 153 ED 91 The diverse nature of DG (base generation, intermittent genera- operation and maintenance of the network together with deciding 154 92 tion, etc.) is taken into account. The most probable net demand, and carrying out new network investments. 155 93 i.e. gross demand minus DG production, is obtained. In order to 94 do this, the impact of vegetative increases of demand and DG pro- 2.2. Deciding new investments with DG 156 95 duction profiles on the system load duration curves is assessed. CT 96 Net demand, together with the probabilities of failure of network One of the most important activities that DSOs perform is the 157 97 facilities and generators, permit computing the effective capac- planning of the grid, by identifying new investments required. DSOs 158 98 ity of distribution assets and the expected non-supplied energy typically analyse load duration curves of distribution facilities and 159 99 (ENS). The former information allows DSOs to take more efficient verify that no overload occur (Fig. 1). Furthermore, DSOs assess the 160 100 investment decisions. However, these approaches do not encour- reliability of the network and dimension so that the failure of an 161 age active DG involvement in covering peak demand in order to RE 101 element does not cause long duration supply interruptions. If addi- 162 102 avoid overloads. tional network capacity is required, new investments are made. 163 103 This paper proposes a market mechanism based on annual auc- However, DSOs must now face the fact that, when they have 164 104 tions, called reliability options for DG (RODG). This mechanism aims large amounts of DG embedded in distribution network, net 165 105 at achieving an active participation of DG in avoiding overloads and demand (computed as gross demand minus DG production) is low- 166 106 substituting new network investments. RODG make DG partially ered. DSOs have to decide whether to consider this generation to 167 R 107 responsible for interruptions and, at the same time, provides effi- offset existing demand, hence not investing in new facilities, or not 168 108 cient economic signals for the operation and localization of DG in to consider it and build new network elements. Moreover, DSOs are 169 109 the distribution network. Benefits are shared between DSOs, who fully responsible for continuity of supply, whereas DG perceives no 170 CO 110 obtain the firm power offered by DG as an alternative to new net- incentives to guarantee firm capacity during peak demand peri- 171 111 work investment, and DG, which is compensated for the provision ods. Therefore, DSOs tend not to rely on DG and size distribution 172 112 of this service. networks as if no DG was present, which is not efficient. 173 113 The remainder of this article is organised as follows. Section 2 Throughout the remainder of this article, for illustrative pur- 174 114 analyses the current incentives perceived by DSOs when deciding poses, we shall base our considerations on the basic distribution 175 115 whether to invest in new network facilities. Moreover, the condi- UN 116 tions that DG ought to fulfil in order to be considered as an alter- 117 native to new network investments are identified. Next, Section 3 118 describes the RODG mechanism proposed, and assesses this mecha- 119 nism from the perspectives of DSOs and DG. In Section 4, additional 120 factors that may shape or influence the mechanism proposed are 121 analysed. An illustrative example is provided in Section 5. Finally, 122 the most relevant conclusions of this paper are drawn in Section 6. 123 2. Distribution planning with DG in a liberalised context 124 This section presents the alternative mechanisms to remunerate 125 distribution companies, their consequences on distribution net- 126 work planning, and the requirements to be fulfilled by DG so that 127 DSOs can consider it as an alternative to new network investments. Fig. 1. Generic load duration curve. Please cite this article in press as: D. Trebolle, et al., Distribution planning with reliability options for distributed generation, Electr. Power Syst. Res. (2009), doi:10.1016/j.epsr.2009.09.004
  3. 3. ARTICLE IN PRESS G Model EPSR 2930 1–8 D. Trebolle et al. / Electric Power Systems Research xxx (2009) xxx–xxx 3 F OO Fig. 3. Capacity auction. Fig. 2. Distribution network. rated capacity of the facilities and their load duration curves are 218 176 network represented in Fig. 2. In this distribution network, given known, it is possible to identify the areas that may suffer over- 219 177 the demand and the rated capacity of the transformer, the DSO has loads. Given the areas with problems and the amount of firm power 220 PR 178 the dilemma of installing a second transformer, or somehow using needed (C), it is possible to assess the contribution of DG embed- 221 179 the necessary generation capacity, which would avoid overloading ded in those areas. It will be assumed that the transformer from the 222 180 the existing transformer (DG1, DG2 or DG3) [14]. example shown in Fig. 2 will suffer overloads due to the estimated 223 gross demand. 224 181 2.3. DG as an alternative to network investment Secondly, the DSO would identify the DG embedded in the net- 225 work where the overloaded facilities are located. The DSO must 226 182 The former subsection identified the problems that DSOs must ensure that there is enough DG capacity to provide the firm power 227 ED 183 face to execute new investments. In this subsection, the require- required (C). After this analysis the DSO shall convene an auction in 228 184 ments DG ought to fulfil so as to become an investment alternative year n − 1 for year n in each area (Fig. 3). The DSO shall convene as 229 185 are identified. These requirements must ensure that the reliabil- many auctions as electrical areas with capacity shortage problems 230 186 ity of supply does not worsen when compared to investing in new to supply local demand have been identified. 231 187 network facilities. The firm capacity required for each auction (C) is then published. 232 CT 188 The requirements proposed in this paper are firmness, reliability This capacity should be calculated to offset ENS plus a specific secu- 233 189 and sufficiency of DG. With regard to firmness, it is necessary that rity margin. Hence, the facilities would be loaded at a certain level 234 190 DG is producing energy at times when gross demand would over- (Ov) below their rated capacity (100%) (Fig. 4). 235 191 load the distribution facilities. This is the most important aspect DG bids, consisting of a certain amount of firm capacity and a 236 192 of all since the DSO must perceive the same firmness as the one price, would be sorted from the lowest to the highest price, i.e. 237 provided by network facilities. This requirement may represent according to their merit order. PF is the price of the last firm MW 238 RE 193 194 considerable difficulties for some types of generation technologies, that satisfies the required capacity C. Using once again the example 239 195 particularly if their production depends on intermittent resources. from Fig. 2, it is shown in Fig. 3 how the capacity offered by DG1 and 240 196 This is the situation faced by solar photovoltaic (PV), flowing mini- part of the capacity offered by DG2 would satisfy the required firm 241 197 hydraulics or wind farms. power (C) and receive a premium (PF). Payment of the resulting 242 198 The reliability of DG is also a very important requirement. The premium (PF) to DGs would be performed by the DSO. This pre- 243 R 199 goal is for DG not to disconnect from the network in the event of mium could have a maximum value or cap established by the DSO. 244 200 disturbances (voltage gaps, short periods of overcurrent or subfre- The computation of this cap is explained in Section 3.2. 245 201 quency, etc.) and ensure that demand is met at all times. The involvement by the DG would be voluntary due to the nature 246 CO 202 Finally, sufficiency refers to the fact that DG is able to offer the of DG technologies. Not all DG units would have a production profile 247 203 firm power necessary to avoid loading distribution facilities above similar to that of local demand in the area being analysed, nor would 248 204 a suitable security margin [17]. all technologies have a controllable primary resource, e.g. solar or 249 wind. Therefore, not all generators would be able to provide the 250 205 3. Distribution planning with reliability options UN 206 In order to consider DG as an alternative to traditional invest- 207 ment and achieving a more active involvement of DG, this paper 208 proposes a market mechanism, defined as RODG, which seeks to 209 obtain the guaranteed firm power necessary from DG in order 210 to avoid overloading distribution facilities. Along this section, the 211 most relevant features of the proposed reliability mechanism are 212 described together with the perspective of agents involved: DSO 213 and DG. 214 3.1. Reliability options with DG 215 Firstly, the DSO must identify the areas with possible overload 216 problems one year in advance. This paper proposes calculating the 217 load duration curve of gross demand in a future scenario. Once the Fig. 4. Periods of DG firm power. Please cite this article in press as: D. Trebolle, et al., Distribution planning with reliability options for distributed generation, Electr. Power Syst. Res. (2009), doi:10.1016/j.epsr.2009.09.004
  4. 4. ARTICLE IN PRESS G Model EPSR 2930 1–8 4 D. Trebolle et al. / Electric Power Systems Research xxx (2009) xxx–xxx 251 guaranteed firm power service. The RODG mechanism shall pro- 3.5. DG perspective and penalties 310 252 duce a localization signal for the technologies with a generation 253 profile similar to the local demand profile, encouraging DG to be From the DG perspective, there are two key questions to answer: 311 254 installed in areas where they can achieve greater efficiency. how should DG bid in the auction? And, how much should be the 312 penalty in the event of not fulfilling their commitment? For exam- 313 255 3.2. DSO perspective ple, in Fig. 4, what would happen if during period t4 both DG1 and 314 DG2 were unavailable? 315 256 The best form of understanding the perspective of DSOs is to Both questions have an intimately related answer. On the one 316 257 analyse the cost and income structure of DSOs in a simplified hand, the value of the penalty would be indexed to the cost of ENS 317 258 manner and to interpret the potential benefits of using DG as an that would be incurred by the DSO as a result of the DG not gen- 318 259 alternative to network investment. erating during the required periods. Therefore, the generators bid 319 F 260 As previously mentioned in Section 2.1, the DSO perspective would depend on that penalty and the risk of the generator related 320 261 may vary depending on the remuneration mechanism: incentive to its probability of failure or lack of availability of the primary 321 regulation or cost of service regulation. In the former case, the DSOs resource (1). 322 OO 262 263 revenues are limited. Thus if it can use DG as an alternative to tradi- PFi = i p 8760 PEN (1) 323 264 tional investment, it could delay network investments and increase 265 its earnings. In the latter case, if the rate of return of the invest- where PFi is the price of annual firm capacity bid by ith DG 324 266 ments is high, then the DSO would not be interested in delaying (D /MWfirm); i the rate of unavailability of ith DG (including pri- 325 267 investments through the proposed market mechanism. mary resource shortage); p the rate of the annual hours during 326 268 DSOs may establish a maximum price (PFmax) of the premium which firm capacity is required and the total number of hours in 327 PR 269 that they would be willing to pay. This value would offset the the year. PEN the penalty applied to DG for not fulfilling its firm 328 270 benefit to be obtained by DSOs on engaging firm power from the power commitment. This penalty would be indexed to the cost of 329 271 DG instead of investing in new network assets. Furthermore, a ENS used to penalize DSOs. 330 272 cost/benefit analysis may be performed by the DSO in order to The bids of each DG would depend on its reliability and produc- 331 273 take into account the variation of operation and maintenance costs tion availability. Less reliable generators or those of intermittent 332 274 of facilities, the variation of network losses, and the variation of nature would bid at a higher price, whereas most reliable DGs 333 ED 275 quality of supply indices associated to the firmness of DG. would bid at lower prices. Therefore, the allocation of the payments 334 is in accordance with efficiency criteria. 335 276 3.3. Requirements and compensations of DG 4. Other aspects to consider 336 277 Compensation to DG in exchange for service provision would be 278 performed through the premium (PF), paid by the DSO, and whose There are several aspects to highlight that can influence the CT 337 279 value is determined through the described market mechanism. proposed market mechanism. 338 280 DG units voluntarily participating in the auction would assume From the DSO viewpoint, the decision whether to consider the 339 281 the obligation of producing during the periods when DSOs foresee firm power offered by DG as an alternative would depend on the 340 282 that additional capacity is required. In addition, the DG would coor- potential benefit to be obtained when comparing the cost of both 341 283 dinate its protection and control systems with the corresponding alternatives: new network or firm DG potential. Contrary to a cost 342 RE 284 DSO in order to not provoke undesired disconnections in the event of service approach, incentive regulation fosters DSOs to reduce 343 285 of network disturbances. costs. Hence, DSOs would be more willing to implement a RODG 344 286 The mandatory service provision periods would be published mechanism under this type of regulation. 345 287 during the year n − 1 for year n, although the DSO could have to Considering the perspective of the DG, and assuming that the 346 288 make adjustments that would not exceed a certain percentage of mechanism is voluntary; the price of the RODG should represent 347 R 289 the defined hours, for instance 5%. a reasonable amount compared to the rest of the income obtained 348 by DG, including the support payments generally received by these 349 290 3.4. Periods of firmness generators (feed-in tariffs, feed-in premiums, tradable green cer- 350 CO tificates, etc.). The market value of the RODG should be sufficiently 351 291 The periods that require firm capacity from DG coincides con- significant in order to fulfil two objectives: to obtain location and 352 292 ceptually with the strike price concept in the reliability options operational signals for DG and to ensure that they voluntarily par- 353 293 market mechanism defined in [12]. The difference in the mecha- ticipate in the proposed mechanism. 354 294 nism defined in [12] is that the market determines supply problems Regarding the computation of penalties, ENS is deemed as a suit- 355 295 through its price, whereas in the proposed method this is known able index for the cases in which DG has not fulfilled its firmness 356 UN 296 one year in advance thanks to the predictable nature of demand commitment. However, there can be a situation in which a DG has 357 297 behaviour. Moreover, the key decision of generators in [12] was not fulfilled its commitment but there is no ENS. This situation is 358 298 the estimation of the number of hours per year that market price possible if there are other generators that have not participated in 359 299 exceeds the strike price. Within the RODG mechanism, the key deci- the RODG mechanism, but are generating during critical periods. In 360 300 sion of DG is to determine their availability rate during the periods this case, DG units that have not fulfilled their commitments would 361 301 specified by the DSO. have to pay for unsupplied committed power. 362 302 In order for the mechanism to be transparent, stable and not to 303 determine these moments in the short term, the annual required 5. Case study 363 304 firm capacity (C) interval is defined when gross demand represents 305 a degree of load of facilities equal to or greater than the Ov (%) of its The following example illustrates the proposed mechanism of 364 306 load. In Fig. 4, the obligation to generate firm capacity would only distribution network planning with RODG. 365 307 be required during the periods t2, t4 and t5. Hence, in the example, In this case study, it will be assumed that the transformer 366 308 DG1 and the share of DG2 which is committed would have to be depicted in Fig. 2 is located within a 45/15 kV distribution sub- 367 309 generating firm capacity engaged during periods t2, t4 and t5. station. The actual load curve during year 2008 of a real 45/15 kV 368 Please cite this article in press as: D. Trebolle, et al., Distribution planning with reliability options for distributed generation, Electr. Power Syst. Res. (2009), doi:10.1016/j.epsr.2009.09.004
  5. 5. ARTICLE IN PRESS G Model EPSR 2930 1–8 D. Trebolle et al. / Electric Power Systems Research xxx (2009) xxx–xxx 5 F OO PR ED CT RE Fig. 5. Load duration curve of gross demand at the distribution substation. R CO UN Fig. 6. Load profile of the distribution substation. Please cite this article in press as: D. Trebolle, et al., Distribution planning with reliability options for distributed generation, Electr. Power Syst. Res. (2009), doi:10.1016/j.epsr.2009.09.004
  6. 6. ARTICLE IN PRESS G Model EPSR 2930 1–8 6 D. Trebolle et al. / Electric Power Systems Research xxx (2009) xxx–xxx F OO PR Fig. 7. Load profile of the distribution substation in a winter working day. 369 substation has been considered. This substation is located in a sub- Table 1 DG bids. 370 urban area, where demand corresponds mainly to domestic con- 371 sumers. DG in the area comprises solar PV plants, CHP generators DG unit Rated capacity Capacity auctioned Availability Bid [D /MW] 372 and a mini-hydro plant. Assumptions regarding the characteristics [MW] [MW] rate [%] ED 373 of DG or the cost of non-served energy have been made. CHP1 2 2 97 11,250 4 2.5 98 7,500 374 5.1. Capacity to auction and periods requiring DG firm power CHP2 1.5 90 37,500 1.5 1 99 3,750 375 The substation considered in this case study has one trans- Mini-hydro 0.5 95 18,750 CT 376 former with a capacity of 22 MW. A security margin of 2 MW will 1 0.2 60 150,000 377 be required (Ov = 91%). Hence, the obligation of DG to offer firm PV 0.8 20 300,000 378 capacity will be required when demand at the substation exceeds 379 20 MW. Total capacity auctioned amounts to 4 MW. 380 The load duration curve of gross demand at the selected substa- ity rates for different segments of the rated capacity of their plants. 404 tion is displayed in Fig. 5. Peak demand is around 24 MW. During RE 381 This may be caused by the existence of different units within an 405 382 375 h/year ( p = 4.28%), demand at the substation is higher than installation, e.g. CHP, or the uncertainties in the production of inter- 406 383 20 MW. mittent DG, e.g. solar PV. Hence, each generator may submit several 407 384 The load profile of the distribution substation (Fig. 6) shows that bids with different prices. 408 385 the aforementioned value of 20 MW is exceeded during 7.5 h/day, Table 1 shows that less reliable (intermittent) generators bid at 409 386 on working days for 10 weeks in winter. higher prices than most reliable (controllable) ones. 410 R 387 The load profile of the substation in a typical winter working 388 day is shown in Fig. 7. The 7.5 h/day when demand exceeds 20 MW 5.3. Capacity auction clearing 411 389 correspond to the morning hump, between 8:30 and 13:30; and the CO 390 evening hump, from 18:45 to 21:15. The results from the auction are shown in Fig. 8 and detailed in 412 Table 2. 413 391 5.2. Computation of bids 392 The bids made by DG plants have been computed as stated in (1). 393 The penalty will be considered as the cost of ENS for domestic loads. UN 394 Herein, a value of 1 D /kWh will be considered.1 DG unavailability 395 rates comprise maintenance, primary resources shortages and the 396 risk perceived by the producers. These rates correspond solely to 397 the periods when firm capacity is required. 398 In this example, no maximum price or cap will be set to the 399 auction. The computation of a cap and the viability of these auc- 400 tions under the perspective of DSOs and DG promoters will be later 401 discussed. 402 Two CHP units, a mini-hydro plant and a solar PV installation 403 will be considered. DG operators may compute different availabil- 1 This is the penalization for DSOs set in the Spanish regulation (OM 3081/2008) for each kWh of consumption interrupted. Fig. 8. Auction clearing. Please cite this article in press as: D. Trebolle, et al., Distribution planning with reliability options for distributed generation, Electr. Power Syst. Res. (2009), doi:10.1016/j.epsr.2009.09.004
  7. 7. ARTICLE IN PRESS G Model EPSR 2930 1–8 D. Trebolle et al. / Electric Power Systems Research xxx (2009) xxx–xxx 7 Table 2 Firm capacity assigned to DG. DG unit Capacity auctioned [MW] Assigned firm capacity [MW] Income [D /MW year] Total Income [D /year] CHP1 2 0.5 11,250 5,625 2.5 2.5 11,250 28,125 CHP2 1.5 0 – – 1 1 11,250 11,250 Mini-hydro 0.5 0 – – 0.2 0 – – PV 0.8 0 – – F 414 In this case study, firm capacity is supplied by CHP units and energy losses or continuity of supply will not be considered in this 453 415 the mini-hydro plant owing to the fact that they present higher example. 454 OO 416 availability rates at the periods specified. PV solar bids are far above Table 3 provides the computation of the cap for the previous 455 417 those of the remaining technologies since it may difficultly provide situation. It was assumed that useful life for transformers is 30 456 418 firm capacity in the evening hours of winter days. Nonetheless, in a years and that the existing transformer has been working for 18 457 419 tourist area, where peak demand occurs in summer during midday years. The rate of return was fixed at 8%, which a typical value 458 420 hours when air conditioning devices are working, PV solar could used for distribution assets. The cap in this case would amount 459 421 actively participate in these auctions. to 13,768 D /MVA-auctioned, whereas the price resulting from the 460 PR 422 DG will be paid the amount of capacity assigned in the auction auctions was 11,250 D /MW. 461 423 at the clearing price, which in this case amounted to 11,250 D /MW, Regarding the participation of DG in the auctions, in theory, the 462 424 regardless of their actual production. However, they will be penal- bids by themselves suffice to manage it. However, it is arguable 463 425 ized according to the non-supplied committed firm capacity in whether DG owners would be really interested in participating if 464 426 every hour this situation occurs. the net income they perceive from the RODG is extremely low when 465 compared to their income from producing energy. Moreover, some 466 427 5.4. Discussion ED DG units may require additional investments in order to be able to 467 provide firm capacity in the periods specified, such as storage not 468 428 The viability of the proposed mechanism of RODG lies on two justified only by arbitrage strategies.2 These additional costs should 469 429 fundamental questions: Is it worthwhile for DSOs? Are DG owners be incorporated to the bids. 470 430 interested in participating? Only when the answer to these two 431 questions is affirmative, may RODG be used. 6. Conclusions 471 CT 432 The first question is intimately related with the alternatives to 433 the RODG and the regulatory framework in place. This mechanism Over the last years, growing penetration levels of DG have 472 434 may only be applied under an incentive regulation scheme since it occurred in distribution networks. In order to efficiently and effec- 473 435 provides DSOs with explicit incentives to reduce their costs. Being tively integrate DG, DSOs would be obliged to provide more 474 436 this the case, DSOs would find RODG attractive as long as the cost of flexibility and controllability to their networks. In this regard, one 475 RE 437 upgrading network assets, herein a substation, is higher than that of of the most important challenges faced by the DSO is how to con- 476 438 the RODG. The annualized cost per MVA of additional capacity could sider DG when performing new investments in the distribution 477 439 be used as cap for the auctions. Should there not be enough capacity network. 478 440 offered in the market below the cap, the auction would be cancelled The European Electricity Directive mandates that DSOs must 479 441 and the network reinforced. Otherwise, the firm capacity offered by be legally and functionally unbundled, hence they cannot have 480 DG in the market plus the one provided by network assets would direct control over DG siting and operation. Consequently, DSOs 481 R 442 443 not suffice to meet the expected demand. have traditionally neglected the contribution of DG. This led to an 482 444 The lumpiness of network investments may play a key role inefficient surplus of network capacity. However, most European 483 countries have implemented incentive regulation for distribution. 484 CO 445 in determining the alternatives to RODG. A typical value for a 446 45/15 kV transformer investment costs is 30–40 kD /MVA. How- Hence, DSOs may achieve higher revenues if they could integrate 485 447 ever, it is not generally possible to install a transformer of only the contribution of DG in network planning. 486 448 4 MVA, as required in this case study. Thus, a real alternative could This paper has proposed a market mechanism based on annual 487 449 be to install a 30 MVA transformer that substitutes the existing auctions, called RODG, which allows DSOs to consider DG in net- 488 450 22 MVA one. The cap in this case would be the annualized value work planning. This mechanism permits sharing benefits between 489 DSOs and DG. DSOs may benefit from the use of DG as alternative to UN 490 451 of the cost associated with the new transformer minus the residual 452 value of the existing one. The impact of the RODG mechanisms on traditional network investments whereas DG receives a fixed pay- 491 ment in exchange for the provision of firm capacity. Overall, greater 492 efficiency for the system can be attained by properly assigning the 493 Table 3 resources available. 494 Computation of the auction cap. The RODG mechanism represents a realistic alternative to new 495 Cost of 22 MVA transformer [D ] 700,000 network investments, as it provides firmness to the generation 496 Useful life [years] 30 presence during the periods required by the power system. On the 497 Remaining life [years] 12 other hand, the RODG mechanism provides DG with an incentive 498 Residual value (linear depreciation) [D ] 280,000 Cost of 30 MVA transformer [D ] 900,000 to place itself in areas of the network where its generation profile 499 Difference [D ] 620,000 Interest rate 8% Depreciation time [years] 30 2 Herein, the term arbitrage strategy refers to the storage of energy at low price Annualized cost [D ] 55,073 periods in order to sell it when high prices occur. This strategy might be particularly Annualized cost [D /MVA-auctioned] 13,768 interesting for intermittent DG. Please cite this article in press as: D. Trebolle, et al., Distribution planning with reliability options for distributed generation, Electr. Power Syst. Res. (2009), doi:10.1016/j.epsr.2009.09.004
  8. 8. ARTICLE IN PRESS G Model EPSR 2930 1–8 8 D. Trebolle et al. / Electric Power Systems Research xxx (2009) xxx–xxx 500 is similar to the zonal demand profile. In this manner, the various [15] R.N. Allan, G. Strbac, P. Djapic, K. Jarret, Developing the P2/6 Methodology, 545 501 technologies would perceive adequate locational signals. Department of Trade and Industry (DTI), 2004. 546 [16] J. Roman, T. Gomez, A. Munoz, J. Peco, Regulation of distribution network busi- 547 ness, IEEE Transactions on Power Delivery 14 (1999) 662–669. 548 502 Acknowledgment [17] J.I.P. Arriaga, M. Rivier, C. Batlle, C. Vázquez, P. Rodilla, White Paper on the 549 Reform of the Regulatory Framework of Spain’s Electricity Generation, Instituto 550 de Investigación Tecnológica, Universidad Pontificia de Comillas, 2005. 551 503 The authors would like to thank Marta Olascoaga of Unión 504 Fenosa Distribución for her cooperation. David Trebolle received the degree in Electrical Engineering at the Universidad Pon- 552 tificia Comillas, Madrid, Spain, in 2001 and his Master in Economics and Regulatory 553 Framework of the electrical business at the Universidad Pontificia Comillas, Madrid, 554 505 References Spain, in 2005. David also received a Manager Developing Program (PDD) at the 555 Instituto de Empresa Business School, Madrid, Spain in 2008. From 2001 to 2002 556 506 [1] L. Mantzos, P. Capros, N. Kouvaritakis, M. Zeka-Paschou, European Energy and he worked as a planning engineer at the control room centre of National Grid Com- 557 507 Transport Trends to 2030, European Communities, 2003. F pany in Wokingham, United Kingdom. Since 2002 he has been working at Union 558 508 [2] T. Ackermann, G. Andersson, L. Soder, Distributed generation: a definition, Fenosa Distribución and he has also been studying for his Ph.D. in Ingeniero Indus- 559 509 Electric Power Systems Research 57 (2001) 195–204. trial at the Universidad Pontificia Comillas. At present day David is the head of 560 510 [3] V.H. Mendez, J. Rivier, J.I. de la Fuente, T. Gomez, J. Arceluz, J. Marin, A. Madurga, OO innovation and new technologies department in Union Fenosa Distribución. His 561 511 Impact of distributed generation on distribution investment deferral, Interna- 512 tional Journal of Electrical Power & Energy Systems 28 (2006) 244–252. interests include distribution planning, the operation of electrical power systems, 562 513 [4] V.H. Mendez, J. Rivier, T. Gomez, Assessment of energy distribution losses for power quality assessment, distributed generation and the regulatory framework in 563 514 increasing penetration of distributed generation, IEEE Transactions on Power transmission and distribution businesses. 564 515 Systems 21 (2006) 533–540. 516 [5] V. Van Thong, J. Driesen, R. Belmans, Benefits and impact of using small gen- Tomás Gómez received his Doctorate in Ingeniero Industrial from the Universidad 565 517 erators for network support, in: 2007 IEEE Power Engineering Society General Politécnica, Madrid, Spain, in 1989, and the degree of Ingeniero Industrial in Electri- 566 518 Meeting, vols. 1–10, 2007, pp. 2880–2886. cal Engineering from the Universidad Pontificia Comillas (UPCO), Madrid, in 1982. He 567 PR 519 [6] B. Meyer, Distributed generation: towards an effective contribution to power joined the Instituto de Investigación Tecnológica in 1984 where he served as direc- 568 520 system security, in: 2007 IEEE Power Engineering Society General Meeting, tor from 1994 to 2000. From 2000 to 2002, he was the vice chancellor of Research, 569 521 vols. 1–10, 2007, pp. 1758–1763. Development and Innovation at UPCO. He has significant experience in industry and 570 522 [7] P. Frias, T. Gomes, J. Rivier, Regulation of distribution system operators with in joint research projects in the field of electrical energy systems in collaboration 571 523 high penetration of distributed generation, IEEE Lausanne Powertech 1–5 with Spanish, Latin American, and European utilities. His areas of interest include 572 524 (2007) 579–584. the operation and planning of transmission and distribution of electrical systems, 573 525 [8] R. Cossent, T. Gomez, P. Frias, Towards a future with large penetration of dis- power quality assessment and regulation, and economic and regulatory issues in 574 526 tributed generation: is the current regulation of electricity distribution ready? the electrical power sector. 575 527 Regulatory recommendations under a European perspective, Energy Policy 37 ED 528 (2009) 1145–1155. Rafael Cossent received the Ingeniero Industrial degree, majoring in Electrical Engi- 576 529 [9] Directive 2003/54/EC of the European Parliament and of the Council of 26 neering, from Universidad Pontificia Comillas-ICAI, Madrid, Spain, in 2007. He is 577 530 June 2003 concerning common rules for the internal market in electricity and currently an assistant researcher at the Instituto de Investigación Tecnológica at 578 531 repealing Directive 96/92/EC, 2003. Universidad Pontificia de Comillas, where he is pursuing a Ph.D. degree in Ingeniero 579 532 [10] R.C. Dugan, T.E. McDermott, G.J. Ball, Planning for distributed generation, IEEE Industrial. He has worked in several EU-funded projects concerning the integration 580 533 Industry Applications Magazine 7 (2001) 80–88. of renewables and distributed generation in electric power systems. His areas of 581 534 [11] W. El-Khattam, M.M.A. Salama, Distribution system planning using distributed CT 535 generation, in: CCECE 2003: Canadian Conference on Electrical And Computer interest are the regulation of distribution utilities and distributed generation. 582 536 Engineering, vols. 1–3, Proceedings, 2003, pp. 579–582. Pablo Frías received the M.S. degree and the Ph.D. degree in electrical engineering 583 537 [12] C. Vazquez, M. Rivier, I.J. Perez-Arriaga, A market approach to long-term from the Universidad Pontificia Comillas, Madrid, Spain, in 2001 and 2008, respec- 584 538 security of supply, IEEE Transactions on Power Systems 17 (2002), PII S0885- 539 8950(02)03834-8. tively. He is currently a researcher at the Instituto de Investigación Tecnológica at 585 540 [13] C. Batlle, C. Vazquez, M. Rivier, I.J. Perez-Arriaga, Enhancing power supply ade- Universidad Pontificia Comillas, where he also teaches at the Power System Depart- 586 541 quacy in Spain: migrating from capacity payments to reliability options, Energy ment of the Engineering School (ICAI). He has participated in many international 587 RE 542 Policy 35 (2007) 4545–4554. projects and in several consultancy projects with electricity utilities in Spain. His 588 543 [14] R.N. Allan, P. Djapic, G. Strbac, Assessing the contribution of distributed gener- interests are ancillary services in power systems, distributed generation, and elec- 589 544 ation to system security, in: International Conference on Probabilistic Methods trical machines. 590 Applied to Power Systems, vols. 1 and 2, 2006, pp. 524–529. R CO UN Please cite this article in press as: D. Trebolle, et al., Distribution planning with reliability options for distributed generation, Electr. Power Syst. Res. (2009), doi:10.1016/j.epsr.2009.09.004

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