\u5fae\u7f51\u591a\u76ee\u6807\u7ecf\u6d4e\u8c03\u5ea6\u4f18\u5316_\u9648\u6d01.pdf - 33 19 2013 7 5 0258-8013(2013 19-0057-10 Proceedings of the CSEE TM 73 A Vol.33 No.19 Jul 5 2013 2013

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ֻ 33 ֻ 19 ݓ ۽ ӱ Б Vol.33 No.19 Jul. 5, 2013 2013 7 5 Proceedings of the CSEE ©2013 Chin.Soc.for Elec.Eng. 57 ໓ᅣщݼğ 0258-8013 (2013) 19-0057-10 ٳোݼğ TM 73 ໓ངѓᆽ ğ A ࿐॓ٳোݼğ 470 40 ؟ଢѓ ט؇Ⴊ߄ ӧ đဗྮđᇫধđᅦૅ༩đ ( ഈݚ ৯࿐ đഈݚ൧ ဗ௵ 200090) Microgrid Multi-objective Economic Dispatch Optimization CHEN Jie, YANG Xiu, ZHU Lan, ZHANG Meixia, LI Zhenkun (Shanghai University of Electric Power, Yangpu District, Shanghai 200090, China) ABSTRACT: It is necessary to cut gaseous pollutant emission and develop energy-saving and emission-reducing in microgrid power generation scheduling. An optimization model of multi-objective economic dispatch combined heat and power (CHP) microgrid system considering heating income was presented. The microsources could provide both active and reactive power in the model. A typical microgrid consisting of a wind turbine, a photovoltaic, a storage battery, a micro turbine, a fuel cell, heating and electric loads was selected. Based on fuzzy optimization theory, the maximum fuzzy satisfaction degree method was adopted to transform the multi-objective optimization problem into a non-linear single-objective optimum problem. The improved genetic algorithm was used to optimize microsources’ active and reactive output, satisfaction degree of multi-objective optimization for grid-connected mode considering spot price. And the single-objective and multi-objective optimal values were comparatively analyzed. Simulation results show that multi-objective model was more precise than single-objective model in reflecting the actual operation characteristics of microgrid and the better environmental benefits could be reached at operation cost as low as possible in this model. So the validity of the proposed model and algorithm was proved. KEY WORDS: microgrid; multi-objective optimization; economic dispatch; fuzzy modeling; improved genetic algorithm; combined heat and power (CHP); network structure ᅋေ ğູ ഒగุ ֥ஆ٢đັ ࢫି ஆؿ ט؇Ӯ ཛଢ ğݓ 863 ۚ ཛଢ (2011AA05A106) Ġഈݚ൧॓ ׄ॓ ۾ܱ ߃ (11dz1210405) Ġආܻ ߃ (10SG51) Ġഈݚۚ֩ m 085 n۽ӱ ഡཛଢሧᇹĠഈݚ൧ ׄ࿐॓ ഡཛଢሧᇹ (J51301) b Project Supported by National Natural Science Foundation of China (2011AA05A106); Key Technology R&D Program of Shanghai (11dz1210405); Project Sunburst (10SG51); Shanghai Higher Education ‘085’ Engineering Construction Program; Leading Academic Discipline Project of Shanghai Municipal Education Commission (J51301). ູ၂ᇕсಖ bิԛॉ੮ັჷ ൈิ܂Ⴕۿބ ۿԛ৯ѩ ᇅಣ൬ၭ֥ಣ ৳Ӂ ؟ଢѓ ט؇ଆ đ ၛ၂۱Їݣڄaܻaԥaັ ಗగ aಗਘ ӽၛ ڵހ֥ऎุັ ູ২đ ࣮ଆ Ⴊ߄ ં֥ ԤഈđҐႨ ቋնଆ ડၩ؇م ؟ଢѓ ט؇໙ีሇ߄Ӯ٤ཌྟֆ ଢѓႪ߄໙ีđѩᄎႨڿ ෘمႪ߄ॉ੮ൌൈ ֥ѩ ᄎྛٚ ༯۲ັჷ֥Ⴕۿa ۿԛ৯ބ؟ଢѓႪ߄֥ડၩ ؇đؓбٳ༅ֆଢѓა؟ଢѓ༢ Ⴊ߄ᆴbٟᆇෘ২і đ ؟ଢѓଆ бֆଢѓଆ ۷ିಒ్ّ႘ັ ֥ൌ ᄎྛሑ
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