Journal
IEEE TRANSACTIONS ON SMART GRID
Volume 7, Issue 1, Pages 66-73Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2015.2431072
Keywords
Binary particle swarm optimization (BPSO); chaos optimization; microgrid; microsource; optimal operation; uncertainty
Categories
Funding
- National High Technology Research and Development Program of China [2015AA050104]
- National Natural Science Foundation of China [50977029]
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Based on fuzzy mathematics theory, this paper proposes a fuzzy multi-objective optimization model with related constraints to minimize the total economic cost and network loss of microgrid. Uncontrollable microsources are considered as negative load, and stochastic net load scenarios are generated for taking the uncertainty of their output power and load into account. Cooperating with storage devices of the optimal capacity controllable microsources are treated as variables in the optimization process with the consideration of their start and stop strategy. Chaos optimization algorithm is introduced into binary particle swarm optimization (BPSO) to propose chaotic BPSO (CBPSO). Search capability of BPSO is improved via the chaotic search approach of chaos optimization algorithm. Tests of four benchmark functions show that the proposed CBPSO has better convergence performance than BPSO. Simulation results validate the correctness of the proposed model and the effectiveness of CBPSO.
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