An improved two-stage optimization for network and load recovery during power system restoration
•Proposed an improved two-stage optimization method for network and load recovery.•Decouples integer and continuous decision variables and solves them separately.•Proposed method significantly can improve the computational efficiency.•Verified the advantage in computational efficiency and plan optim...
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| Vydáno v: | Applied energy Ročník 249; s. 265 - 275 |
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| Hlavní autoři: | , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.09.2019
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| Témata: | |
| ISSN: | 0306-2619, 1872-9118 |
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| Abstract | •Proposed an improved two-stage optimization method for network and load recovery.•Decouples integer and continuous decision variables and solves them separately.•Proposed method significantly can improve the computational efficiency.•Verified the advantage in computational efficiency and plan optimality.•Demonstrated potential application through simulation in a practical system.
Network and load recovery (NLR) during power system restoration is a multi-step mixed-integer nonlinear programming (MINP) problem. The NLR is difficult to be solved as it is NP-hard. Thus, NLR is commonly solved step by step, which is short-sighted and will result in longer restoration time. To obtain a far-sighted NLR plan, this paper proposes an improved two-stage optimization method for NLR. The first stage adopts a mixed-integer linear programming (MILP) model to obtain optimal solutions of integer variables in NLR, namely the load pick-up schedules and transmission line charging schedules. Then in the second stage, a continuous non-linear optimization method based on AC power flow with frequency constraints and load model is established to minimize the restoration duration of the plan generated in the first stage step by step. Case studies are undertaken on a 10-machine 39-bus system and Southeast Hubei Provincial power system of China. Simulation results indicate that the restoration plan obtained from the improved two-stage optimization method is highly effective, while the computational efficient meets the intensive need for restoration scheduling after blackouts. |
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| AbstractList | •Proposed an improved two-stage optimization method for network and load recovery.•Decouples integer and continuous decision variables and solves them separately.•Proposed method significantly can improve the computational efficiency.•Verified the advantage in computational efficiency and plan optimality.•Demonstrated potential application through simulation in a practical system.
Network and load recovery (NLR) during power system restoration is a multi-step mixed-integer nonlinear programming (MINP) problem. The NLR is difficult to be solved as it is NP-hard. Thus, NLR is commonly solved step by step, which is short-sighted and will result in longer restoration time. To obtain a far-sighted NLR plan, this paper proposes an improved two-stage optimization method for NLR. The first stage adopts a mixed-integer linear programming (MILP) model to obtain optimal solutions of integer variables in NLR, namely the load pick-up schedules and transmission line charging schedules. Then in the second stage, a continuous non-linear optimization method based on AC power flow with frequency constraints and load model is established to minimize the restoration duration of the plan generated in the first stage step by step. Case studies are undertaken on a 10-machine 39-bus system and Southeast Hubei Provincial power system of China. Simulation results indicate that the restoration plan obtained from the improved two-stage optimization method is highly effective, while the computational efficient meets the intensive need for restoration scheduling after blackouts. Network and load recovery (NLR) during power system restoration is a multi-step mixed-integer nonlinear programming (MINP) problem. The NLR is difficult to be solved as it is NP-hard. Thus, NLR is commonly solved step by step, which is short-sighted and will result in longer restoration time. To obtain a far-sighted NLR plan, this paper proposes an improved two-stage optimization method for NLR. The first stage adopts a mixed-integer linear programming (MILP) model to obtain optimal solutions of integer variables in NLR, namely the load pick-up schedules and transmission line charging schedules. Then in the second stage, a continuous non-linear optimization method based on AC power flow with frequency constraints and load model is established to minimize the restoration duration of the plan generated in the first stage step by step. Case studies are undertaken on a 10-machine 39-bus system and Southeast Hubei Provincial power system of China. Simulation results indicate that the restoration plan obtained from the improved two-stage optimization method is highly effective, while the computational efficient meets the intensive need for restoration scheduling after blackouts. |
| Author | Wen, Jinyu Han, Xingning Fang, Jiakun Liao, Shiwu Yao, Wei He, Haibo Ai, Xiaomeng |
| Author_xml | – sequence: 1 givenname: Shiwu orcidid: 0000-0003-4057-2831 surname: Liao fullname: Liao, Shiwu organization: State Key Lab of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, 430074, China – sequence: 2 givenname: Wei orcidid: 0000-0002-4054-5916 surname: Yao fullname: Yao, Wei email: w.yao@hust.edu.cn organization: State Key Lab of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, 430074, China – sequence: 3 givenname: Xingning surname: Han fullname: Han, Xingning organization: State Grid Jiangsu Economic Research Institute, Nanjing 210008, China – sequence: 4 givenname: Jiakun surname: Fang fullname: Fang, Jiakun organization: Department of Energy Technology, Aalborg University, Aalborg DK-9220, Denmark – sequence: 5 givenname: Xiaomeng surname: Ai fullname: Ai, Xiaomeng organization: State Key Lab of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, 430074, China – sequence: 6 givenname: Jinyu surname: Wen fullname: Wen, Jinyu organization: State Key Lab of Advanced Electromagnetic Engineering and Technology, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, 430074, China – sequence: 7 givenname: Haibo surname: He fullname: He, Haibo organization: Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881, USA |
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| SubjectTerms | case studies China linear programming Load restoration Network restoration Power system restoration Two-stage optimization |
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