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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Shrnutí: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.
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ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2018.11.069