A decentralized battery energy storage system(DBESS)is used for stabilizing power fluctuation in DC microgrids.Different state of charge(SoC)among various battery energy storage units(BESU)during operation will reduce...A decentralized battery energy storage system(DBESS)is used for stabilizing power fluctuation in DC microgrids.Different state of charge(SoC)among various battery energy storage units(BESU)during operation will reduce batteries’service life.A hierarchical distributed control method is proposed in this paper for SoC balancing and power control according to dispatching center requirement in DBESS.A consensus algorithm with pinning node is employed to allocate power among BESUs in the secondary control whereas in the primary control,the local controller of BESU adjusts output power according to the reference power from secondary control.Part of BESUs are selected to be pinning node for accepting command from dispatching center while other BESUs as following nodes which exchange output power and SoC information with the adjacent nodes through communication network.After calculating reference power of each BESU by adopting consensus algorithm,the power sharing in DBESS is achieved according to their respective SoC of BESUs.Meanwhile,the total output power of DBESS follows the varying requirements of dispatching center.The stability of DBESS is also improved because of having no center controller.The feasibility of the proposed control strategy is validated by simulation results.展开更多
Thermostatically controlled appliances(TCAs)have great thermal storage capability and are therefore excellent demand response(DR) resources to solve the problem of power fluctuation caused by renewable energy.Traditio...Thermostatically controlled appliances(TCAs)have great thermal storage capability and are therefore excellent demand response(DR) resources to solve the problem of power fluctuation caused by renewable energy.Traditional centralized management is affected by communication quality severely and thus usually has poor realtime control performance. To tackle this problem, a hierarchical and distributed control strategy for TCAs is established. In the proposed control strategy, target assignment has the feature of self-regulating, owing to the designed target assignment and compensating algorithm which can utilize DR resources maximally in the controlled regions and get better control effects. Besides, the model prediction strategy and customers’ responsive behavior model are integrated into the original optimal temperature regulation(OTR-O), and OTR-O will be evolved into improved optimal temperature regulation. A series of case studies have been given to demonstrate the control effectiveness of the proposed control strategy.展开更多
In a cyber-physical power system, active distribution network(ADN) facilitates the energy control through hierarchical and distributed control system(HDCS). Various researches have dedicated to develop the control str...In a cyber-physical power system, active distribution network(ADN) facilitates the energy control through hierarchical and distributed control system(HDCS). Various researches have dedicated to develop the control strategies of primary devices of ADN. However, an ADN demonstration project shows that the information transmission of HDCS may cause time delay and response lag, and little model can describe both the ADN primary device and HDCS as a cyber-physical system(CPS). In this paper, a hybrid system based CPS model is proposed to describe ADN primary devices, control information flow, and HDCS. Using the CPS model, the energy process of primary devices and the information process of HDCS are optimized by model predictive control(MPC) methodology to seamlessly integrate the energy flow and the information flow. The case study demonstrates that the proposed CPS model can accurately reflect main features of HDCS, and the control technique can effectively achieve the operation targets on primary devices despite the fact that HDCS brings adverse effects to control process.展开更多
基金The part of establishing DBESS model was supported by National Natural Science Foundation of China(61473238,51407146)the primary droop control analysis got support of Sichuan Provincial Youth Science and Technology Fund(2015JQ0016)the part of distributed consensus algorithm was supported by Doctoral Innovation Funds of Southwest Jiaotong University(D-CX201714).
文摘A decentralized battery energy storage system(DBESS)is used for stabilizing power fluctuation in DC microgrids.Different state of charge(SoC)among various battery energy storage units(BESU)during operation will reduce batteries’service life.A hierarchical distributed control method is proposed in this paper for SoC balancing and power control according to dispatching center requirement in DBESS.A consensus algorithm with pinning node is employed to allocate power among BESUs in the secondary control whereas in the primary control,the local controller of BESU adjusts output power according to the reference power from secondary control.Part of BESUs are selected to be pinning node for accepting command from dispatching center while other BESUs as following nodes which exchange output power and SoC information with the adjacent nodes through communication network.After calculating reference power of each BESU by adopting consensus algorithm,the power sharing in DBESS is achieved according to their respective SoC of BESUs.Meanwhile,the total output power of DBESS follows the varying requirements of dispatching center.The stability of DBESS is also improved because of having no center controller.The feasibility of the proposed control strategy is validated by simulation results.
基金supported by National High Technology Research and Development Program of China (863 Program) (No. 2015AA050403)National Natural Science Foundation of China (Nos. 51377117, 51407125, 51361135704)+3 种基金China-UK NSFC/EPSRC EV Grant (Nos. 5136113015, EP/L001039/1)‘‘131’’ Talent and Innovative Team of Tianjin City, State Grid Corporation of China (No. KJ16-1-42)Innovation Leading Talent Project of Qingdao, Shandong Province (No. 15-10-3-15-(43)-zch)Innovation and Entrepreneurship Development Funds Projects of Qingdao Blue Valley Core Area (No. 201503004)
文摘Thermostatically controlled appliances(TCAs)have great thermal storage capability and are therefore excellent demand response(DR) resources to solve the problem of power fluctuation caused by renewable energy.Traditional centralized management is affected by communication quality severely and thus usually has poor realtime control performance. To tackle this problem, a hierarchical and distributed control strategy for TCAs is established. In the proposed control strategy, target assignment has the feature of self-regulating, owing to the designed target assignment and compensating algorithm which can utilize DR resources maximally in the controlled regions and get better control effects. Besides, the model prediction strategy and customers’ responsive behavior model are integrated into the original optimal temperature regulation(OTR-O), and OTR-O will be evolved into improved optimal temperature regulation. A series of case studies have been given to demonstrate the control effectiveness of the proposed control strategy.
基金supported by the National Natural Science Foundation of China (No.51677116)the Science and Technology Program of State Grid Jiangsu Electric Power Company (No.J20170124)。
文摘In a cyber-physical power system, active distribution network(ADN) facilitates the energy control through hierarchical and distributed control system(HDCS). Various researches have dedicated to develop the control strategies of primary devices of ADN. However, an ADN demonstration project shows that the information transmission of HDCS may cause time delay and response lag, and little model can describe both the ADN primary device and HDCS as a cyber-physical system(CPS). In this paper, a hybrid system based CPS model is proposed to describe ADN primary devices, control information flow, and HDCS. Using the CPS model, the energy process of primary devices and the information process of HDCS are optimized by model predictive control(MPC) methodology to seamlessly integrate the energy flow and the information flow. The case study demonstrates that the proposed CPS model can accurately reflect main features of HDCS, and the control technique can effectively achieve the operation targets on primary devices despite the fact that HDCS brings adverse effects to control process.
