A. Panagoda, K.T.M.U. Hemapala and N. De Silva

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1 Annual Sessions of IESL, pp. [ ], 2016 The Institution of Engineers, Sri Lanka Distribution System Fault Localization, Fault Restoration and etwork Reconfiguration using Multi Agent Based System A. Panagoda, K.T.M.U. Hemapala and. De Silva Abstract: Power distribution networks reduce their reliability during the fault localization, isolation and network reconfiguration. The fault localization of High voltage and medium voltage systems consumes more time and network reconfiguration get complex when there are more interconnections. Multi Agent System is simply developed based on the one important component named as agent and the system comprises of more than one agent is named as the multi agent system. There are various definitions for the multi agent system. The agent is the most important concept of the multi agent system and agent is defined as a software component having special features to bring its autonomy. With its special features agent can act as a human agent and it helps to model complex system and introduce the possibility of having common or conflicting goals. The agent comprises with the main special features of autonomous, social, reactive and proactive. Therefore the objective of the study is to provide a methodological approach to manage the fault restorations of power distribution system in Sri Lanka using a de-centralized technique. Agent based solution was implemented with Multi Agent System (MAS). The system comprises with Application layer, Interface layer and communication layer. The application layer was developed using Java Agent Development Environment (JADE). Keywords: Multi Agent System (MAS), Java Development Environment (JADE), Layered Architecture 1. Introduction The national grid comprises of generation stations and high voltage transmission lines. The transmission network in Sri Lanka is solely owned by Ceylon Electricity Board (CEB) and it operates at 220kV and 132 kv voltage levels. Transmission line bring the power generated at power stations to the primary substations where it starts the power distribution. The power distribution network in Sri Lanka is owned by CEB and Lanka Electricity Company (LECO). The scope of a power distribution network is spread from primary substation level to household consumer level. The feeder arrangement of Kolonnawa primary substation owned to LECO Kotte branch area is shown in figure 1. There are seven feeders indicated in the figure. The number of feeders starting from a primary substation is depending upon the power requirement of feeding area. Figure 1 - Feeder arrangement of Kolonnawa Primary Substation. Mr. A. Panagoda, B.Sc. Eng., M.Sc., Airport & Aviation Services Sri Lanka Limited. Eng. (Dr.) K.T.M.U. Hemapala, B.Sc.Eng., AMIE (Sri Lanka) Ph.D., Senior Lecturer Department of Electrical Engineering, University of Moratuwa. Dr..De. Silva, B.Sc.Eng., Ph.D., Lanka Electricity Company PVT Ltd. 135

2 Power switching breakers used in power distribution networks are in different types according to their applications such as Load Break Switch (LBS), Isolator, Sectionalizer, Auto Reclosure (AR). There exist interconnections between feeders to provide more alternative routes; which make it easy for the feeder management Fault Restoration Conventional Method The switching arrangement of each feeder is set by the control center of either CEB or LECO. The control center has a greater responsibility to keep the power distribution system alive. When a fault occurred at distribution system it get tripped off from the primary substation bringing darkness to the entire area. There are several methods to localize such fault as mentioned below, I. Based on consumer complains Power consumers complain with eye witness of the fault event. II. Prior Experience of the Operation team- Operation team guess from their experience and visited those places directly. III. Route Inspection- Inspection on HV line whether it is touched with tree leaves or any other fallen things on the HV line. (E.g.: Vehicle accidents damaging the HV line). IV. Energize the feeder- Feeder is energize section by section starting from Primary end isolating remote sections. This helps to find out faulty section. V. Finer fault finding- This method started if above attempts did not provide any noticeable fault on the high tension line. This step is executed by climbing to the every HV pole of the faulty section. In the conventional methods, even the easiest step also consumes time in hours Multi Agent System Multi Agent System is simply developed based on the one important component named as agent and the system comprises of more than one agent is named as the multi agent system. There are several illustration given for the multi agent system. In [1], the MAS is defined as a system with component level intelligence. Those intelligent components are named as an agent and system with a group of agents is named as a MAS. In [2], the agent is introduced as a software entity exist in some environment having sense on the changes and ability to react on them autonomously and goal directed manner. In a multi agent system, tasks are carried out by interacting agents that can cooperate with each other. The agent is the most important concept of the multi agent system and agent is defined as a software component having special features to bring its autonomy. With its special features agent can act as a human agent and it helps to model complex system and introduce the possibility of having common or conflicting goals. The agent comprises with the main special features of autonomous, social, reactive and proactive [3]. 2. Literature Review There are several approaches to address the distribution network fault isolation and network reconfiguration. Each of study has developed a power restoration model. Objective Function is maximizing the power to the loads as much as possible with the following constraints: I. Generation limits: Total power required should be below the generation capacity II. Feeder limit: Power flow at the time of restoration should not exceed the capacity of feeder cable; switches and other components. III. The proposed reconfiguration should ensure the radial configuration. The total number of feeder incident on the section must be at most unity [4]. There are several technologies has been used to resolve this restoration problem. The fuzzy reasoning has been applied in [5] for the network reconfiguration using the heuristic rules and past experiences. There are several heuristic methods has been applied in [6] & [7} and in [8] it has discussed about four comparative heuristic method for network reconfiguration. The genetic algorithm technique is used in [9], it searches for optimal supply restoration strategy subjected to the radial constraints. In [10], it present power restoration technique based on non-dominated genetic algorithm-ii. All above techniques were based on centralized approach and when the distribution network become large problem solving get more complex. The value of decentralized approach and multi agent approach in power engineering field is discussed in [11].The MAS is to solve power restoration problem in ring structured ship board power system is studied in [12] and 136

3 power distribution fault isolation and restoration discussed in [13].In [14] it discusses the MAS approach to the power system restoration by only using two agents, bus agent and junction agent verifying their application for a large scale network. The power system restoration problem solving and simulation using virtual test bed (VTB) is discussed in [15]. 3. System Development Multi agent system bring the Photostat of physical system and make the distribution system equipment live. Three agent types were selected which is much closer with distribution power system maintenance; which are primary substation agent, feeder agent and load break switch agent. The behaviour of each agents were implemented by considering the application of each component at the time of power restoration in conventional system. In addition to the above agent, the proxy agent was used to communicate with external interface and which is used as the connecting tunnel between the MAS and external world. Basic block diagram for system modelling is shown in the figure 2. Physical System Wired or Wireless Com Layer Figure 2 - System Modelling Application Socket Proxy Tunnel MAS App Layer 3.1. Agent Formation a. Primary Substation- PSS Agent PSS Agent is a top manager of a distribution system and distribution system is a corporation of PSS agents. Its main responsibilities are as follows, Register the details on the ellow Pages Search about LBS agents and feeder Agents from the yellow pages Investigate the fault location and localized the fault Commanding the Feeder Agent to Provide the Best Proposal for the Fault Restoration b. Feeder Agent The feeder agent is the manager for the LBSs and it reports to the PSS Agents. The main duties of feeder agent is summarized below. As in the physical environment, the feeder is a branch distributed from PSS and it is a group of equipment. Therefore in this study, the feeder agent acts as a virtual agent and its duties are summarised as follows. Register Details of feeder agents on ellow Pages Search details about LBS and PSS from yellow pages Commanding LBS Agents how to isolating the faults Start the discussion with LBS how to restore the fault Find out best proposal from available options Giving commands to the LBS for the etwork rearrangement c. Load Break Switch LBS Agent The load break system (LBS) agent is the last level of this framework and the duties are summarized below, Register details on the ellow Pages Find out details of the feeders and primary from yellow pages Keep updating its operating current When voltage level get loosed, inform the Primary agent about the fault Contribution to the fault localizing discussion Activate the fault isolating actions according to the feeder agent Activate Fault Restoration actions according to the feeder Agent 3.2. System Main Process The whole process discussed here is summarised to a flow diagram in figure 3 and it points out some main processes assist the system to operate. 137

4 Physical System Data The physical system sends data messages to the MAS in two instances depending on its voltage level. System Data Update Fault The first typed message is initiated when the system voltage at operational level and at periodic time intervals as configured at communication layer. Fault Localisation Process Localized Fault Isolation Process Isolated etwork Reconfiguration The main objective of this message is to inform the MAS about the system operation condition such as operating current via the load break switch. The second typed of the message is initiated at the event of voltage loss at the load break switch or voltage goes to zero. In such situation, load break switch is advised to send messages to the relevant agent at MAS, fault has occurred in the system. Then rest of the processes start to localize the fault, isolate the fault and network rearrangement. To accomplish above sub targets, it has been used several techniques in JADE such as interaction protocols (eg: contract-net protocol, request protocol), yellow pages service and socket proxy agent for communication with outside world. Finally using all above techniques, the fault section will be isolated and network get reconfigured for the optimal usage. The operational teams can focus to clear the fault in the faulty section. 4. Results & Validation Re configured The MAS based system is run on java and in order to run the system smoothly it is needed to provide the agents as mentioned in the agent formation section in 3.1. The agent creation GUI shows in figure 4 and agent creation can be done using GUI or command prompt as instructed by JADE. Completed Figure 3 - Flow diagram of Main Process They are, 1. System Data update 2. Fault Localization 3. Fault Isolation 4. etwork Reconfiguration Once the agents are created in multi agent system, each of these agents needed to communicate with physical system. But due to the communication limitation in JADE, it is needed to create an interface layer between application layer and communication layer or physical layer. 138

5 selected considering all the available options. Finally PSS agent order feeder agent to activate the best option. Then feeder rearrangement plan is activated and each LBS at the activation plan notify their status back. In the figure 6, line interconnection LBS search about the load currents and line for the receiving proposals for restoration from interconnection LBSs. Figure 4 - Agent Creation GUI The interface layer GUI is shown in the figure 5 for the selected part of the network and it is act as a virtual network for the supporting the application layer for easy processing. In this virtual network it was simulate the feeder arrangement in Kolonnawa PSS as in the figure 1 considering the LBS arrangements in the area. Figure 5 - Interface Layer GUI In a typical fault restoration problem, agents have to communicate with other agents for responding to contract net protocol, request protocol, socket proxy agent communication and other commanding and informative communication. Such monitored communication process is illustrated in figure no. 6. According to the algorithm when there is a fault, it is first notified to the PSS agent to find the fault upstream LBS. Depending on the fault upstream LBS, PSS agent order the Feeder agent to isolate the faulty section as well as find a restoration plan based on the load current. The best restoration plan is Figure 6 - ACL Communication for fault restoration It was tested all possible fault scenario in the network given in figure 5 and tabulated the result in the table1 to see the performance of the MAS based approach for a distribution network. Time was measured in milliseconds and there are two time measurement for JADE and TOTAL. JADE time is for the result came out from JADE system and for the TOTAL time it is included the outside word communication dependencies. Table 1 - Elapsed time of execution Results Fault Occurred Elapsed Time (ms) JAD E KL1 KL2 37 KL2 KL3 33 KL3 KL4 33 KL4 KL5 33 KL5 KL6 33 KL7 KL8 34 KL8 KL9 35 KL9 KL10 45 KL10 KL11 47 KL11 KL12 33 TOTA L Fault Occurred Elapsed Time (ms) JAD E 103 KL13 KL KL14 KL KL15 KL KL16 KL KL17 KL KL19 KL KL20 KL KL21 KL KL22 KL KL23 KL24 33 TOTA L

6 Since all these results are in millisecond range, it would more closely to the breaker operating time. Therefore this is very much quicker compared to the conventional system. 5. Conclusion A multi agent system that enables to localize the distribution system fault and restore the system for the maximum supply reliability was presented. The result in table 1 shows that the time taken for the communication between MAS and external system consumes more time than the process optimized in JADE. By closely monitoring the communication inefficiencies, it can be improve the total process. Power system restoration involve different steps such as full restoration, partial restorations, restoration with load shedding etc. In this study it was considered full restoration and communication platform with external system, hence further system can be developed to make partial restoration; which involve the restoration using more than one source and restoration with the load shedding. In addition multi agent based system can be link with power system monitoring techniques, metering techniques and them all linking to smart power distribution network. References 1. Solanki, J. M., Khushalani, S. & Schulz,.., A Multi-Agent Solution to Distribution Systems Restoration, IEEE Transactions on Power systems, Vol 22,o 3,2007,pp Buse, D. P., Sun, P., Wu, Q. H., and Fitch, J., Agent-Based Substation Automation, IEEE Power and Energy Magazine, Vol 1(2),2003, pp Bellifemine, F. L., Caire, G., & Greenwood, D., Developing Multi-agent Systems with JADE, Vol. 7, 2007, John Wiley & Sons. 4. agata, T., & Sasaki, H., A Multi-Agent Approach to Power System Restoration, IEEE Transactions on power systems, Vol 17(2), 2002, pp Hsu,. H., & Kuo, H. C., A Heuristic Based Fuzzy Reasoning Approach for Distribution System Service Restoration, IEEE Transactions on Power Delivery, Vol 9, o 2, Apr 1994, pp A ew Heuristic Reconfiguration Algorithm for Large Distribution Systems, IEEE Transactions on Power Systems, Vol 20(3), 2005, pp Morelato, A. L., & Monticelli, A. J., Heuristic Search Approach to Distribution System Restoration, IEEE Transactions on Power Delivery, Vol 4(4), 1989, pp Toune, S., Fudo, H., Genji, T., Fukuyama,. & akanishi,., Comparative Study of Modern Heuristic Algorithms to Service Restoration in Distribution Systems, IEEE Transactions on Power Delivery, Vol17(1),2002, pp Luan, W. P., Irving, M. R., & Daniel, J. S, Genetic Algorithm for Supply Restoration and Optimal Load Shedding in Power System Distribution etworks, IEEProceedings, Vol 149(2),2002, pp Kumar,., Das, B., & Sharma, J., Multi Objective, Multi Constraint Service Restoration of Electric Power Distribution System with Priority Customers, IEEE Transactions on Power delivery, Vol 23(1), 2008, pp McArthur, S. D., Davidson, E. M., Dimeas, A. L., Hatziargyriou,. D., Ponci, F., & Funabashi, T. Multi-Agent Systems for Power Engineering Applications Part I: Concepts, Approaches, and Technical Challenges, IEEE Transactions on Power systems, Vol 22(4), 2007, pp Huang, K., Cartes, D. A., & Srivastava, S. K. A Multiagent Based Algorithm for Ring- Structured Shipboard Power System Reconfiguration, IEEE International Conference on Systems, Man and Cybernetics, Vol. 1, 2005, pp ordman, M. M., & Lehtonen, M. An Agent Concept for Managing Electrical Distribution etworks, IEEE transactions on power delivery, Vol 20(2),2005, pp agata, T., Tao,., & Fujita, H. An Autonomous Agent for Power System Restoration, Power Eng. General Meeting, pp Sun, L., Morejon, G., & Cartes, D. Interfacing Software Agents with Power System Simulations, In Proceedings of the WSEAS Conference, Gomes, F. V., Carneiro, S., Pereira, J. L. R., Vinagre, M. P., Garcia, P. A.., & Araujo, L. R. 140

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