Optimal power dispatch considering load and renewable generation uncertainties in an AC-DC hybrid microgrid

被引:47
|
作者
Maulik, Avirup [1 ]
Das, Debapriya [1 ]
机构
[1] Indian Inst Technol Kharagpur, Elect Engn Dept, Kharagpur, W Bengal, India
关键词
fuzzy set theory; genetic algorithms; distributed power generation; power generation control; power generation dispatch; particle swarm optimisation; power generation scheduling; renewable generation uncertainties; AC-DC microgrid; optimal power dispatch strategy; 6-bus AC-DC hybrid microgrid system; generation activities; cost reduction; emission reduction; optimal scheduling problem; customised power-flow technique; two-point estimate method; fuzzy domain; fuzzy membership functions; fuzzy max-min technique; multiobjective GA; Pareto-front; POINT ESTIMATE METHOD; PARTICLE SWARM OPTIMIZATION; OPTIMAL OPERATION MANAGEMENT; FLOW-ANALYSIS; ALGORITHM; WIND; SYSTEMS; MARKET; RECONFIGURATION; STRATEGIES;
D O I
10.1049/iet-gtd.2018.6502
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
An AC-DC hybrid microgrid is gradually becoming popular. For economic viability and environmental sustainability, an AC-DC microgrid should be operated optimally. This study introduces an optimal power dispatch strategy for simultaneous reduction of cost and emission from generation activities in an AC-DC hybrid microgrid under load and generation uncertainties. The operational attributes of an AC-DC hybrid microgrid, and load and renewable generation uncertainties are incorporated in the optimal scheduling problem by using a customised power-flow technique, and by modelling uncertainties by Hong's two-point estimate method, respectively. The economic and environmental objectives are modelled in the fuzzy domain by fuzzy membership functions. A combination of particle swarm optimisation and fuzzy max-min technique is then employed for obtaining the optimal solution. The static active power droop constants of the dispatchable units are the control variables. Simulation results on a 6-bus AC-DC hybrid microgrid system demonstrate that optimal scheduling results in 4.26% reduction of operating cost and 13.91% reduction of emission in comparison to capacity based droop settings. Further, a comparison between the proposed method and the elitist multi-objective GA indicates that the optimised solution lies on the Pareto-front, thereby validating the proposed technique.
引用
收藏
页码:1164 / 1176
页数:13
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