2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies (DRF'T2004) April 2004 Hang Kong
Improvement of reliability in active networks with intentional islanding F. Pilo, Member, IEEE, G. Celli, Member, IEEE and S . Mocci
Abstract-DERs are gaining more and more importance in distribution and they are predicted to drastically change the whole distribution system. Distribution network will be no longer a passive termination of transmission network and the concept of active network has been recently introduced to indicate a new kind of distribution with DERs actively involved in system management and operation. Intentional islanding, i.e. the use of DG to supply portions (cells, microgrids) of distribution network during upstream line faults and scheduled interruptions, can be a valuable option to reduce the number of service interruptions. In the paper, an algorithm for the optimal allocation of automatic sectionalizingswitching devices has been improved for the maximum exploitation of intentional islanding. Line faults and overloads have been considered as causes of interruptions. Stochastic models have been adopted to assess the probability of overloads and of properly functioning intentional islands. The application to real world case studies has highlighted the benefits achievable with intentional islanding as well as the inability of common reliability indexes (e.g. SAIFI, SAIDI) to properly perceive advantages that are inherently local. Index Terms-Distributed Generation, Distributed Energy Resources, Distribution Network, Optimization, Reliability Indexes
I. INTRODUCTION
T
HE predicted massive penetration of Distributed Generation . . (DG) will inevitably lead to a new approach in the distribution system. The concept of active distribution networks has been introduced to describe the distribution of the future that probably will be subdivided into self-managed, interconnected small cells (microgrids) with many generators. Active networks will make a large use of ICT and automatic control systems to control loads and generators, to allow the participation of DERs to the energy and services market and to maintain a sufficient level ofreliability [1-4]. Intentional islanding, the ability of managing an unfaulted portion of the network by using DG to enhance the service provided thereby, will play a key role in active networks. Intentional islanding is not a common practice at the moment but, as DERs become more integrated into the distribution system, it will be possible to break up the distribution system into islands that are also self
regulating, providing high levels of reliability to critical loads [5,6].In this case the Local Distribution Company (LDC) will have to perform studies for each intentional island including, but not limited, to the followings: 1 Planning studies to verify that the entire island will operate within required voltage and frequency for each island configuration. They will also determine whether there is a requirement for upgrading or replacing LDC equipment or conductors in order to accommodate the anticipated load flows in the islanded condition; 1 Stabilitv studies to check generator-generator and generator-load interactions and verify that the island will be stable; Fault studies to ensure the protective relaying functions located at the generator will be able to properly detect faults at all parts of the island. These fault studies will determine what new protection will be required. The paper deals with planning studies and uses a methodology proposed by the authors for the optimal allocation of Automatic Sectionalizing Switching Devices (ASSDs) in a MV distribution network [7,8]. The optimal number and position of ASSDs is determined considering the existence of distributed generators able to carry the load on islanded sections by maintaining suitable voltage and frequency levels at all islanded loads. The main novelty of the paper is the integration between probabilistic methodologies, used to deal with the inherent randomness of DG power production and load demand, with the original deterministic algorithm. Two causes of power interruption have been considered line faults and overloads. In the first case calculation are performed on annual basis considering the failure rate of lines and substations, in the second one individual hourly characteristics are included in the power flow; DG availability is considered in both cases. Overload costs have been estimated with the EENS unitary cost, which is much more higher than the retail sales rate. Investments decisions are made and timed such that they tend to emphasize the reliability of the system in areas where the value of service is higher [9].
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11. IMPACT OF DER IN FUTURE DISTRIBUTION SYSTEM
A . Distribution of the future A massive penetration of DERs will inevitably lead to a G. Celli, S . Macci and F. Pilo are with the Department of Elechical new approach in the Distribution System. Until now, and Electronic Engineering, University of Caglian, Piazza d ' h i 09123 ITALY (email:
[email protected],
[email protected], distribution networks are regarded as a passive termination
[email protected]) of the transmission network, having the goal of supplying
0-7803-8237-4/04/$17.00C22004IEEE
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2004 IEEE International Conference on Electric Utility Deregulation, Restruchlring and Power Technologies (DRPT2004) April 2004 Hong Kong
reliably and efficiently end-customers. According to this scheme, distribution networks are radial, with unidirectional power flows and with a simple and efficient protection scheme. A greater penetration of DERs will change completely this well consolidated environment: definitely. distribution networks will be no longer passive and it has been foreseen a gradual, but ineluctable, changing towards a new kind of active networks [1-4]. Active networks will be strongly interconnected (no radial scheme, no unidirectional power flow) and subdivided into small cells, locally managed by a power controller, which controls power flow among local generators, loads and adjacent cells. System services will be attributes of a connection, charged to individual customers. Automation, control systems and ICT will be widely used in active networks to manage local cells or non autonomous microgrids, to control generated and absorbed power, to manage congestions and prevent propagation of overloads and faults by isolating the affected part of the network. The final result of this development is a distribution system that provides connectivity between points of supply and consumption [Z]. Intentional islanding (Fig. 1) plays a key role in the active networks and microgrids development and requires new control algorithms for a rapid network reconfiguration, new communication protocols, for data exchange between generators and loads, and simple and reliable communications systems [ 1,4]. According to this vision, DG can be a valuable and cheap option to reduce the number and duration of interruptions for the most sensitive customers and to feed them in the event of an outage in the line or in the primary substation or during scheduled interruptions [2,5]. On the other hand, it should be recognized that intentional islanding could easily lead to safety and power quality problem that will affect the utility system and loads. Islanding increases the likelihood that DG sources may be allowed to subject the island to out of range voltage and frequency conditions during its existence. Moreover, it can pose a serious safety threat during downed conductors and utility repair operations since the public and utility workers may be exposed to circuits that otherwise would be de-energized. Finally, islanding can hinder service restoration by requiring line crews to spend extra time disabling the island conditions. For these reasons, intentional islanding is not a common practice at the moment and economic drivers and political decisions are necessary to convince DISCOS to leave the present well consolidated operation practice in order to develop a new and expensive one. Anyway, DERs are becoming more and more integrating into the distribution system and the first signs of changing are becoming evident: e.g., IEEE 1547 standard does not forbid islanding and leave to distributors, power producers and customers the task of finding technical solutions and economic agreements to implement islanding [ 10,l I].
B. Intentional islanding and network architechwe Intentional islanding occurs when a distributed generator is used to supply loads during upstream utility source outages (Fig.1). For this approach to work the switch must open during upstream faults and the generators must be able to carry the load on the islanded section maintaining suitable voltage and frequency levels at all islanded loads. Unless a static switch is employed, this scheme would usually result in a momentary interruption to the island since the DG would necessarily trip during the voltage disturbance caused by the upstream fault. A DG assigned to carry the island must be able to restart and pickup the island load after the switch has opened. The DG unit must be able to load follow during islanded operation and the switch will need to sense if a fault current has occurred downstream of the switch location and send a signal to block islanding if a fault has occurred within the island zone. When utility power is restored on the utility side, the switch must not close unless the utility and “island” are tightly in synchronism. This requires measuring the voltage on both sides of the switch and transmitting that information to the DG unit supporting the island so that it can “synchronize” with the utility and allow reconnection. Overall, this is complicated but new automated switch technologies and communications approaches make this scheme much more practical than in past years [5,6]. It is opportune to notice that the advantages produced by the “intentional islanding’’ approach depend on the network architecture. In radial MV distribution network a single failure will cause service interruptions to all customers downstream. Significant improvements in total reliability can be achieved with automatic reclosers, which reduce the extent of an outage’s impact on service. To reduce the duration of interruption for costumers downstream the faulted branch, emergency connections can be employed to provide alternative supply routes. In many cases customers are subdivided between trunk and lateral ones. The most important customers (trunk nodes) are fed by an open loop network that allows trunk nodes to be supplied in the event of line or substation faults and scheduled intermptions. If the open loop network is designed to supply all loads in the event of a service interruption, intentional islanding is not able to improve reliability as much automation and protection coordination can do (but DG still remains an option to
S”blllti0“
Sublfntbn
Fig. I . lntentional islanding: portions of the distribution network are supplied by the DG unit in case of upstream faults (cases a) and bjj.
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2004 IEEE International Conference on Electnc Utility Deregulation, Reshuctunng and Power Technologies (DRPT2004) Apnl2004 Hong Kong
defer investments). Less important customers (lateral nodes) are supplied by pure radial networks with no alternative routes to supply loads during interruptions. Lateral customers have really poor quality of service, both in absolute value and in comparison with the top priority customers. Intentional islanding could be a valuable option to improve reliability to these customers and should be compared with the alternative solution of building new emergency connections. 111. STOCHASTIC MODELS
knowledge of generator and load pdfs in the examined island. The combination of all random variables in the island, performed taking into consideration all kinds of correlations, allows determining a resulting random function, which represents the balance between generated and absorbed power. Its pdf can be used to evaluate the probability to have a sufficient power production to supply insulated loads. Only islands with a sufficient probability of good working are accepted with the consequence of an improvement in node reliability indexes.
B. Probabilistic evaluation
The most general analysis employed in power system engineering is the load flow calculation. However, the quality of results depends on the knowledge of the input variables, which are almost always unidentified, but estimated on some past and present data. In the case of statistical uncertainty this problem can be overcome with the stochastic approach, by using random variables and applying methods from the probability theory to solve the Probabilistic Load Flow (PLF) [ 12-15]. Considering that DG introduces many new uncertainties in distribution studies, the adoption of probabilistic models is becoming more and more important in distribution modeling and planning. The PLF takes into account the probability density function @dfl of the loads and of the annual power production associated to each generating unit. To achieve good quality results, random variables cannot be regarded as independent because in power system considerable correlations can exist between the various nodal powers. Omission of correlation can lead to misleading results and create a resulting density function of the output parameters that is either narrower or broader than the true density function. On the other side, the solution of PLF considering correlation can ofien be a difficult task that requires a considerable computational effort. Fortunately, distribution systems have particular characteristics that allow simplifymg the assessment of correlation by hypothesizing only linear correlations [IZ]. In the paper probabilistic procedures have been used to evaluate the probability of overloads and of intentional islands. A . Probabilistic evaluation of island sustainabilify
During faults or interruptions the distribution network
can be subdivided automatically in some small island having power generation. The problem is simply to evaluate the probability that DG can be in service at that time and can produce sufficient power to carry the load maintaining suitable voltage and frequency levels at all islanded customers. In planning studies the first question can be addressed considering the generators annual failure rate; line faults and generator outages are regarded as independent events and the resulting probability can be simply assessed by multiplying the respective probabilities [ 161. The second point has been solved starting from the
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of overloads
The second case of power interruption considered is line overload. This problem can be correctly evaluated by resorting to a more accurate representation of loads and generators: both have been considered in the power flow calculation through their daily load (generation) curves. By so doing, the maximum continuous line current at the time of peak load can be assessed, and also the advantage introduced by DG to reduce this current can be taken into account. Moreover, the possible overload current that could appear at the time of minimum load due to the simultaneous high generation may be estimated. To perform these evaluations, the daily load (generation) curves have been discretized into 24 intervals (each one of the duration of 1 h) as shown in Fig. 2. For each interval, the uncertainties on the loads (generators) power have been considered by using suitable pdfs: typically, a normal distribution has been applied to the loads, while for DG the pdf depends on the type of generator considered. Then, a Monte Carlo approach has been applied to solve repeatedly the network equations:
v.-v where [U is the admittance matrix, [VI and [r] are the nodal voltage and current vectors, I , is a generic branch current, ig is the longitudinal impedance of the branch between nodes i and j , and Eq. (2) is solved for each branch of the distribution network. The dot over each symbol means that the variable considered is complex. Possible existing correlations have been also included during the Monte Carlo calculation. Summing up for all intervals the number of branch current samples that exceed a prefixed capacity limit, the yearly average number of interruptions suffered by the customers due to overloads has been evaluated as follow:
where NS is total number of simulation used to perform the Monte Carlo procedure. Regarding the duration of interruption, each overload has been supposed to last for
2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies (DRF’T2004) April 2004 Hong Kong
P [MWI
IIIIIIIIIIIIIIIIIIIIIIIII 12
01
b
24
t [hl Fig. 2. Generic daily load curve discretized into 24 intervals, with uncertainties in the power absorbed (uncertainty band). the whole duration of the interval (1 h). Referring to the Italian distribution network protection scheme, it has been supposed that when an overload occurs, the breaker at the beginning of the overloaded feeder is opened, extending the interruption to all the nodes supplied by that feeder. Therefore, overload events have been included into the ASSDs optimal allocation procedure by simply increasing the fault rate of the first feeder branch and, consequently, the overload costs have been evaluated by using the EENS unitary cost. IV. ASSDs OPTIMAL ALLOCATION The optimal allocation of ASSDs have attracted many researches during the last years due to the growing importance of service quality and the difficult to solve a typical combinatorial optimization problem. Some authors have resorted to heuristic algorithms, some others to genetic algorithms [17-191. An algorithm to find the solution of this problem for both radial and meshed networks resorting to dynamic programming has been proposed in [7,8]. The application of some logic rules allows applying the algorithm in planning studies with an acceptable computational effort. The objective function to be minimized for the optimal allocation of ASSDs is the following: 5w= C, (XI + CA, (4 (4) where x is a vector having a number of elements equal to the number of nodes in the network (xj=l if nodej has an ASSD, xj=O if it does not have), C, is the cost of interruptions calculated with Eq. (2) and CO,,, is the cost of ASSDs installed. Furthermore, in order to overcome problems related to average customer indexes, the algorithm has to guarantee some prefixed minimum reliability levels to trunk nodes.
A . FauN models The procedures normally adopted when a fault occurs on a MV network branches are recalled here. The duration of the fault is usually divided into two phases: fault location and fault repair. Automatic sectionalizers and reclosers can restrict the area of influence of fault, reducing the number of customers affected by long-term interruptions during the fault location phase. In this phase
intentional islanding can be used to supply unfaulted portions of the network automatically separated by the faulted section with an improvement of reliability indexes. The repair stage consists of the time required to isolate the faulted branch, connect any emergency ties and repair the fault. It is in this phase that the presence of DG units, that enable power to be restored to the nodes downstream the sectionalized branch, becomes extremely important due to the duration. For a generic combination of ASSDs, the service disruption cost can be evaluated by using Eq. (5).
j=,
Where: Nb = Number of branches in the network I, = Number of faults for every 100 km of feeder L, = Branchlength(km) Ckmr = Cost of EENS ($/kWh) N,, = Number of nodes isolated during fault location N, = Number of nodes isolated during fault repair Pi = Node power (kW) tloc = Duration of the fault location (h) kc, = Duration of the fault repair (h) NI,, is the number of the nodes downstream the first ASSD upstream the faulted branch and N,, is the number of the nodes directly supplied by the faulted branch. N,, depends on the presence of throwover feeders, while N,,, decreases with the number of ASSDs and their coordination with emergency connections. Besides, the greater ASSDs number, the smaller q,, because the fault location becomes easier. The application of Eq. (5) in passive radial networks does not require the analysis of the network transient behaviour, which is negligible for the assessment of the cost of not supplied energy, and does not involve the check of the electrical constraints that are automatically satisfied in the rescheduled network. If DG units exist and intentional islanding is allowed, it is necessaty to perform load flow studies in both the islanded portion of the network and the remaining one to check that voltages and currents are within their operative ranges. Thus, the proposed methodology checks all these technical aspects and the intentional islanding is allowed only if the voltage in all the nodes of the network is maintained within operative ranges and DG units are able to pick up the loads in the islanded network. v . RESULTS AND DISCUSSION In order to highlight the potential benefits of intentional islanding a small portion of real Italian distribution network constituted by 25 MV/LV trunk nodes, 117 MV/LV lateral nodes, 6 DG units and 2 primary substations has been considered (Fig. 3). The period taken into consideration for the planning study is 20 years long, with all nodes existing at the beginning of the period. The
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2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies (DRPT2004) April 2004 Hong Kong
annual medium active power delivered to MV nodes is, at the beginning of the planning period, 9.1 MW. For each MViLV node, a constant power demand growth rate of 3% per year has been assumed. Different sizes of DG generators (200-400-600 kW) have been considered. The majority of the branches are of the overhead type, but some buried cables exist. Firstly, the general effect of overload outages reduction due to the presence of DG has been examined. Without DG, the feeder supplied by the primary substation PS2 is subjected to 3.285 intemptions per year and 3.796 h of interruption per year due to overloads. Considering that there is only a circuit breaker at the beginning of each feeder and supposing that no network reconfiguration and load shedding are implemented, these outages are suffered by all the nodes of the feeder. The ability of DG to reduce the branch current, particularly at the peak load, is resulted manifest in the drastic reduction of these reliability indexes, becoming 0.073 interruptions per year and 4.38 minutes of interruptions per year. Secondly, the influence of intentional islanding on network reliability has been investigated. The following values have been assumed: -Cost of EENS: 6 $kWh -Cost of one ASSD: 9,100 $ (50% amortizable during the study period). -Number of faults: 0.15(year.h)-' (overhead), O.lO(yewkm~' (buried cables) -Outage duration due 9 h (1 h to locate the faulted to buried cables: branch and 8 h to repair it.). -Outage duration due 6 h (1 h to locate the faulted to overhead lines: branch and 5 h to repair it.). All the customers in the trunk are completely resuppliable, in emergency condition, from one HViMV substation. Generally, the ASSDs in the network reduce the time to locate the faulted branch proportionally to their number, but in the paper a simplified model has been assumed, considering a fixed reduction of 30% for both buried and overhead lines. ASSDs are located and coordinated with existing generators by using the above described algorithm, outages due to overloads and generator reliability are also considered. In Table I reliability indexes are reported considering the possibility of intentional islanding. The remarkable impact of ASSDs on the reliability improvement of the distribution network is well known and discussed in literature [6-8,17-191, and it is confirmed by the comparison of the results reported in rows 1 and 3 of Table I. Despite the good values of SAlFI and SAIDI, many lateral nodes still suffer of poor reliability compared to the trunk ones. If intentional islanding is allowed and well coordinated with ASSDs, an additional melioration of the reliability indexes can be attained. As it was predictable, the step up on the global SAIFI and SAIDI indexes has been relatively small, because intentional islanding has mainly a local effect. However, the reliability for some lateral
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Fig. 3. M V lest network and some self sustaining islands during fault location and repair stages.
nodes bas been drastically improved, as reported in the third row of Table 1. Two test lateral nodes have been examined, shown in Fig. 4. Both of them have exhibited a high reduction in their values of interruption duration: hut, while test node 1 has gained also a great decrement of the interruption number, test node 2 maintains its previous value. This happens because it still remains unsupplied during location phase of the same faults that affect its reliability indexes in the case of intentional islanding not permitted, while it is re-supplied by generators DG1 and DG2 only during the repair phase of many of those faults. Instead, the service of test node 1 is interrupted only for the faults downstream the ASSD 1. For all the other faults, it is sustained by the generator DG2 during both fault location and fault repair phases. This discussion emphasizes the importance of the correct location of ASSDs to exploit to the utmost the potentiality offered by intentional islanding when DG is installed on a distribution network. VI. CONCLUSIONS Distribution network will experience in the hture a drastic change due to the growing penetration of DG. Among the many new features of new active networks, the possibility of using DG to supply loads in self-sustaining islands seems to have a real interest for LDCs. Planning studies performed by the authors have highlighted the potential benefits of intentional islanding, especially if DG is coordinated with ASSDs. The most important results are that the practice of intentional islanding can be really useful for those nodes that have low reliability (lateral nodes). Furthermore, it bas been underlined that average indexes (e. g. SAIFI, SAIDI) are not significantly improved by islanding that have only a local influence [20,21]. But customers are not really interested to have a network with a good or acceptable level of reliability, they want to have a service quality
2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies (DRPT2004) April 2004 Hong Kong
no.3,pp.1167-1172,July 1999. G. Celli, F. Pilo, “Intentional Blanding and Automation to Improve Service Quality in MV Networks”, in Proc. ofSC12001, pp. 7-12, [9] R. C. Dugan, T. E. McDemott, G. I. Ball, “Planning for Disnibuted Generation”, IEEE Industry Applicotiom Magazine, Vol. 7, No. 2, pp. 80-88, April 2001 [IO] E E E Standard for Interconnecting Distributed Resources with Electric Power Systems, IEEE Std 1547-2003.2003. [II] Requirements for Connecrion of Disnibuted Energy Resource Facilities to LI LDC Distribution Svstem, [Online]. Available: w.in.govliurclutilitiesienerW/di~trib~t~~~p~~ttB.d~~ [I21 G. Celli, S. Macci, F. Pilo, R. Cicoria. “Probabilistic Optimilation of MV Distribution Network in Presence of Distributed Generation”, in Proc. 2002 PSCC ConJ 1131 R. N. Allan, M. R. G. AI-Shakarchi, “Linear dependence between nodal powers in probabilistic a. c. load flow”, Proe I€€, vol. 124, No. 6, lune 1977, pp. 529-534. [I41 A. Dimitravski, R. Ackovski. “Probabilistic Load Flow in Radial Distribution Networks”, T&D Conference. 1996. Proc. IEEE, 1996, pp. 102-107. (151 G. Carpinelli, G. Celli, F. Pilo, A. Russo, “Embedded Generation Planning under Uncertainty Including Power Quality Issues”, ETEP, to be appear. [I61 H. L. Willis, W. G. Scott, Distributed Power Generation. New York: Marcel Dekker, 2000. [I71 Sh. Levitin, Mazal-Tav and D. Elmakis. ‘Y)ptimal sectianalizers allocation in electric distribution systems by genetic algorithm”, Elecnicpowers~,~temsresearch, vol. 31, 1994, pp. 97.102. [I81 R. Billinton and S. laannavithula, “Optimal switching device placement in radial distribution system“, IEEE Trans. on Power Delivery, vol. II,No. 3, 1996, pp. 1646-1651. 1191 . . Tsai Li-Hui. “Network recanfimration to enhance rehbiliw of electric distribution systems”, Electric power system rtreorch, vol. 27, 1993, pp. 135-140. 1201 T. McDmott. R. C. Dupan, “Distributed Generation lmmct on Reliabili- and Power OuaiiN Indexes”. in Proc. 2002 IEEE Rural Electric Power CO@,pp. D3 -D3-7. [2l1 R. E. Brown, M. W. Marshall, ‘‘The cost reliability”, T&D World, vol. 53, December2001, pp. 13-20
[8]
Fig. 4. Intentional islands formed during the fault location and repair stages: enlargement of a portion of the MV test network.
proportioned to their specific exigencies. Thus a customer supplied by a lateral can be available to pay for a premium quality contract and is not really interested about the good medium quality of its network [2 11. The results presented and discussed in the paper have proved that DG could be a valid option to be compared with the other available for the planner (i.e. building new alternative routes for lateral nodes), but many challenges have to he faced in order to transform a theoretical possibility in a real practical application. In particular, there is the need of new standards, new smarter protections, efficient communication systems and, most important, customers have to participate more actively to energy market.
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VIII. BIOGRAPHIES
VII. REFERENCES
N.
Jenkins, R. Allan, P. Crossley, D. Kirschen, G. Stcbac, Embedded Gmerotion, London: IEE Publisher, 2000. SUSTELNET, “Review of Technical Options and Constraints for Integration of Distributed Generation in Electricity Networks”, [Online]. Available: htrp:llw.sustelnet.net. C.E.R.T.S, “Grid of the future white paper on interconnection and controls for reliable, large scale integration of Distributed Energy Resources”, LBNL-45274, [Online]. Available: http://certs.lbl.gov. V. Roberts, A. Callinson, A. Beddoesa, F. van Overbeeke, “Active networks for the accommodation of dispersed generation”, in Proc. ofCIRED 2003 Con/. Sess. 4, paper n.51 P. P. Barker, R. W. de Mello, “Determining the Impact of Distributed Generation on Power Systems: Part 1- Radial Distribution Systems”. in Pruc. IEEE PES Swnmer Meering 2000, vol. 3, pp. 1645-1656. S. Banali, G. Celli, M. Ceraolo, R. Giglioli, P. Pelacchi, F. Pila, ”Operating and planning issues of distribution grids containing Diffuse Generation”, in Proc. 2001 CIRED Con/ G. Celli, F. Pilo, “Optimal Sectionaliring Switches Allocation in Distribution Networks”, IEEE Tram on Power Delivery, vol. 14,
Gisnni Celli was bom in Cagliari, Italy, in 1969. He graduated in Electrical Engineering at the University of Cagliari in 1994. He became Assistant Professor of Power System in 1997 at the same university. Current research interests are in the field of MV distribution network planning optimization, Power Quality and Neural Networks. He is author of several papers published on intemational joumals or presented in various intemational conferences. He is E E E and AEI member.
Fabrina Pllo was bam in Sassari, Italy, 1966. He graduated in Electrical Engineering at the University of Cagliari in 1992 and eamed the Ph.D. from the University of Pisa in 1998. Since 2001 he has been Associate Professor of Electrical Power Systems at the University of Cagliari. His research activity is mainly focused on distribution planning and optimization. He is author of more than 60 papers published on intemational joumals or presented in various intematianal conferences. He is an E E E and AEI member.
Susanna Morci was born in Cagliari, Italy, 1973. She graduated in Electrical Engineering at the University of Cagliari in 2001 and currently is a Ph.D. student. Her research activity is focused on EG and distribution system. She is AEI member.
TABLE I
EFFECTSOF ASSD AND INTENTIONAL ISLANDING ON R E L I A B I L ~ MDEXES Y AND COSTOF WTERRUPTIONS.
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