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Start Over Search Limiters Available in Library Collection Topic mathematical optimization Topic particle swarm optimization Publication Year Range Last 10 years Journal energy
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1. Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis

Author

Wei Wang, Rui Li, Fen Tang, Zhe Chen, and Xuezhi Wu

Subjects
Mathematical optimization, Energy storage, Optimization problem, Computer science, Pareto analysis, 020209 energy, Reliability (computer networking), Renewable energy source, 02 engineering and technology, Fuzzy logic, Industrial and Manufacturing Engineering, 020401 chemical engineering, 0202 electrical engineering, electronic engineering, information engineering, Bi-level programming, 0204 chemical engineering, Electrical and Electronic Engineering, Active distribution system, Civil and Structural Engineering, business.industry, Mechanical Engineering, Probabilistic logic, Particle swarm optimization, Building and Construction, Pollution, Renewable energy, Planning, General Energy, business
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.

Published
2019

2. Decision support for grid-connected renewable energy generators planning

Author

Ferran Torrent-Fontbona, Beatriz López, and Ministerio de Economía y Competitividad (Espanya)

Subjects
Electric power production, Decision support system, Mathematical optimization, Engineering, 020209 energy, 02 engineering and technology, Decision support systems, Industrial and Manufacturing Engineering, Sistemes d'ajuda a la decisió, 0202 electrical engineering, electronic engineering, information engineering, Electrical and Electronic Engineering, Simulation, Civil and Structural Engineering, Electric power distribution, business.industry, Mechanical Engineering, 020208 electrical & electronic engineering, Particle swarm optimization, Energia elèctrica -- Producció, Building and Construction, Grid, Pollution, Sizing, General Energy, Smart grid, Distributed generation, Simulated annealing, Energia elèctrica -- Distribució, business
Abstract

Recent technological advances and the incremental demand for electrical energy are leading a growth in the prevalence of distributed generation. There are some off-the-shelf tools to support grid planners in locating and sizing a given number of Distributed Generators (DGs), but they approach the problem using a single set of the variables (either location, size or number of DGs). This paper reviews the problem and provides a new pathway for supporting grid planning with an integrated view; hence, a new planning problem is formulated to jointly determine how many new DGs are needed, of which type, their location and size, while attempting to maximise the profit of the generators, minimise the system losses and improve the voltage profile. Accompanying the new grid planning problem, solution approaches based on meta-heuristic methods are provided. A detailed performance analysis of the proposed approaches is carried out on 14- and 57-bus systems to illustrate what could be the outcomes of the new problem. In so doing, particle swarm optimisation-based approaches are able to find the best optimised solutions Work developed with the support of the research group SITES awarded with distinction by the Generalitat de Catalunya (SGR 2014e2016) and the MESC project funded by the Spanish MINECO (Ref. DPI2013-47450-C2-1-R)

Published
2016