Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis

This paper proposes a multi-objective, bi-level optimization problem for cooperative planning between renewable energy sources and energy storage units in active distribution systems. The multi-objective upper level serves as the planning issues to determine the sizes, sites, and types of renewable...

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Vydané v:	Energy (Oxford) Ročník 168; s. 30 - 42
Hlavní autori:	Li, Rui, Wang, Wei, Wu, Xuezhi, Tang, Fen, Chen, Zhe
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Elsevier Ltd 01.02.2019 Elsevier BV
Predmet:	Active distribution system algorithms Alternative energy sources Bi-level programming Clean energy Electric vehicles energy Energy resources Energy storage Mixed integer Multiple objective analysis Pareto analysis Pareto optimization Particle swarm optimization Planning Renewable energy source Renewable energy sources Renewable resources Schedules Storage units Strategy system optimization uncertainty Active distribution system Renewable energy source Bi-level programming Planning Pareto analysis Energy storage
ISSN:	0360-5442, 1873-6785
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Abstract	This paper proposes a multi-objective, bi-level optimization problem for cooperative planning between renewable energy sources and energy storage units in active distribution systems. The multi-objective upper level serves as the planning issues to determine the sizes, sites, and types of renewable energy sources and energy storage units. The fuzzy multi-objective lower level serves as the operation issues to formulate operation strategy and determine the schedules of energy storage units. By means of bi-level programming, the optimal operation strategy of energy storage units is incorporated into the upper level and optimized with planning issues cooperatively. Meanwhile, to address high-level uncertainties and simultaneously capture the temporal correlation related to renewable energy sources, electric vehicles, and load demands, the validity index of Davies Bouldin is adopted to develop sets of probabilistic scenarios with high quality and diversity. A hierarchical solving strategy based on modified particle swarm optimization is applied to solve the bi-level nonlinear, mixed integer optimization problem. Results and further analyses demonstrate that the proposed planning model and optimization methods have the ability to allocate renewable energy sources and energy storage units effectively for reducing costs, enhancing reliability, and promoting clean energy. •Bi-level model is proposed to plan renewable energy and energy storage coordinately.•Short-term operation and long-term planning are optimized cooperatively.•Economy, reliability, and environment issues are considered with equal attention.•High-level uncertainties and temporal correlation are addressed simultaneously.•Temporal correlation between renewable energy and load demands are investigated.
AbstractList	This paper proposes a multi-objective, bi-level optimization problem for cooperative planning between renewable energy sources and energy storage units in active distribution systems. The multi-objective upper level serves as the planning issues to determine the sizes, sites, and types of renewable energy sources and energy storage units. The fuzzy multi-objective lower level serves as the operation issues to formulate operation strategy and determine the schedules of energy storage units. By means of bi-level programming, the optimal operation strategy of energy storage units is incorporated into the upper level and optimized with planning issues cooperatively. Meanwhile, to address high-level uncertainties and simultaneously capture the temporal correlation related to renewable energy sources, electric vehicles, and load demands, the validity index of Davies Bouldin is adopted to develop sets of probabilistic scenarios with high quality and diversity. A hierarchical solving strategy based on modified particle swarm optimization is applied to solve the bi-level nonlinear, mixed integer optimization problem. Results and further analyses demonstrate that the proposed planning model and optimization methods have the ability to allocate renewable energy sources and energy storage units effectively for reducing costs, enhancing reliability, and promoting clean energy. •Bi-level model is proposed to plan renewable energy and energy storage coordinately.•Short-term operation and long-term planning are optimized cooperatively.•Economy, reliability, and environment issues are considered with equal attention.•High-level uncertainties and temporal correlation are addressed simultaneously.•Temporal correlation between renewable energy and load demands are investigated. This paper proposes a multi-objective, bi-level optimization problem for cooperative planning between renewable energy sources and energy storage units in active distribution systems. The multi-objective upper level serves as the planning issues to determine the sizes, sites, and types of renewable energy sources and energy storage units. The fuzzy multi-objective lower level serves as the operation issues to formulate operation strategy and determine the schedules of energy storage units. By means of bi-level programming, the optimal operation strategy of energy storage units is incorporated into the upper level and optimized with planning issues cooperatively. Meanwhile, to address high-level uncertainties and simultaneously capture the temporal correlation related to renewable energy sources, electric vehicles, and load demands, the validity index of Davies Bouldin is adopted to develop sets of probabilistic scenarios with high quality and diversity. A hierarchical solving strategy based on modified particle swarm optimization is applied to solve the bi-level nonlinear, mixed integer optimization problem. Results and further analyses demonstrate that the proposed planning model and optimization methods have the ability to allocate renewable energy sources and energy storage units effectively for reducing costs, enhancing reliability, and promoting clean energy.
Author	Wang, Wei Chen, Zhe Li, Rui Wu, Xuezhi Tang, Fen
Author_xml	– sequence: 1 givenname: Rui orcidid: 0000-0003-1321-0835 surname: Li fullname: Li, Rui email: lirui_ee@bjtu.edu.cn organization: National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China – sequence: 2 givenname: Wei surname: Wang fullname: Wang, Wei organization: National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China – sequence: 3 givenname: Xuezhi surname: Wu fullname: Wu, Xuezhi organization: National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China – sequence: 4 givenname: Fen surname: Tang fullname: Tang, Fen organization: National Active Distribution Network Technology Research Center, Beijing Jiaotong University, Beijing 100044, China – sequence: 5 givenname: Zhe surname: Chen fullname: Chen, Zhe organization: Department of Energy Technology, Aalborg University, Aalborg DK9220, Denmark
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Snippet	This paper proposes a multi-objective, bi-level optimization problem for cooperative planning between renewable energy sources and energy storage units in...
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SubjectTerms	Active distribution system algorithms Alternative energy sources Bi-level programming Clean energy Electric vehicles energy Energy resources Energy storage Mixed integer Multiple objective analysis Pareto analysis Pareto optimization Particle swarm optimization Planning Renewable energy source Renewable energy sources Renewable resources Schedules Storage units Strategy system optimization uncertainty
Title	Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis
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