基于果蝇优化模糊神经网络模型的售电市场评估
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摘要
科学评估售电市场的运行绩效对市场主体有着重大的影响。首先,建立售电市场指标评价体系;其次,构建果蝇优化模糊神经网络综合评价模型,对售电市场进行定量评估;最后,通过评价结果分析售电市场运行状况,为市场参与者和监管部门提供相应的决策支持。
Evaluating the performance of electricity retail market scientifically has a significant impact on market players.First of all, index evaluation system is established. Secondly, fruit fly optimized fuzzy neural network comprehensive evaluation model is constructed to evaluate the performance of market quantitatively. Finally, the performance of the electricity retail market is analyzed through the result to provide appropriate decisions for market participants and regulators.
Evaluating the performance of electricity retail market scientifically has a significant impact on market players.First of all, index evaluation system is established. Secondly, fruit fly optimized fuzzy neural network comprehensive evaluation model is constructed to evaluate the performance of market quantitatively. Finally, the performance of the electricity retail market is analyzed through the result to provide appropriate decisions for market participants and regulators.
引文
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[11]王威,邵山,李磊,等.电力市场效率理论及其评价方法[J].电网技术,2009,33(14):66-71.WANG Wei, SHAO Shan, LI Lei, et al. Efficiency theory of electricity market and its evaluation method[J]. Power System Technology, 2009, 33(14):66-71.
[12]张天云,陈奎,魏伟,等. BP神经网络法确定工程材料评价指标的权重[J].材料导报,2012,26(2):159-163.ZHANG Tianyun, CHEN Kui, WEI Wei, et al. The determination of index weights for comprehensive evaluation of engineering materials with BP neural network[J]. Materials Review, 2012, 26(2):159-163.
[2]刘小溪.德国电力市场化改革成效:市场、价格与监管[J].价格与理论实践,2015(10):68-71.LIU Xiaoxi. The effectiveness of german electricity market reform:market, price and supervision[J]. Price:Theory&Practice, 2015(10):68-71.
[3]文福拴,王钦,刘敏,等.欧洲电力市场评价体系[J].电力系统及其自动化学报,2009,21(3):23-31.WEN Fushuan, WANG Qin, LIU Min, et al. Evaluation system for european electricity market[J]. Journal of Power System and Automation, 2009, 21(3):23-31.
[4]李韩房.中国电力市场绩效评价指标体系及评价模型研究[D].北京:华北电力大学,2008.LI Hanfang. Research on performance evaluation index system and evaluation model of china’s power market[D].Beijing:North China Electric Power University,2008.
[5]王钦,文福拴,刘敏,等.基于模糊集理论和层次分析法的电力市场综合评价[J].电力系统自动化,2009,33(7):32-37.WANG Qin, WEN Fushuan, LIU Min, et al. Combined use of fuzzy set theory and analytic hierarchy process for comprehensive assessment of electricity markets[J]. Automation of Electric Power Systems, 2009, 33(7):32-37.
[6]周建国,王潇炜.基于博弈论和灰色关联度的区域电力市场运营效果评价指标体系[J].电网技术,2007,31(10):69-88.ZHOU Jianguo, WANG Xiaowei. Game theory and gray incidence degree based appraisement index system for operation effect of regional electricity market[J]. Power System Technology, 2007, 31(10):69-88.
[7]庄彦,康重庆,胡江溢,等.售电市场质量及其综合评价[J].电力系统自动化,2009,33(3):25-29.ZHUANG Yan, KANG Chongqing, HU Jiangyi, et al. The quality of electricity retail market and its comprehensive evaluation[J]. Automation of Electric Power Systems, 2009,33(3):25-29.
[8] HAJIBANDEHA N, SHEIKH-EL-ESLAMIB M K, AMINNEJADA S, et al. Resemblance measurement of electricity market behavior based on a data distribution model[J].International Journal of Electrical Power&Energy Systems, 2016, 78(6):547-554.
[9]全生明,卢键明,谢传胜,等.需求侧响应机制的国际经验及对我国的启示[J].电力需求侧管理,2009,11(2):73-76.QUAN Shengming, LU Jianming, XIE Chuansheng, et al.International experience of demand-side response mechanisms and enlightenment to China[J]. Power Demand Side Management, 2009, 11(2):73-76.
[10]韦亚敏,胡泳,李爽.“互联网+”背景下电力客户需求变化分析[J].电力需求侧管理,2016,18(S1):66-68.WEI Yamin, HU Yong, LI Shuang. Analysis on the change of power customer demand under the background of‘Internet plus’[J]. Power Demand Side Management, 2016, 18(S1):66-68.
[11]王威,邵山,李磊,等.电力市场效率理论及其评价方法[J].电网技术,2009,33(14):66-71.WANG Wei, SHAO Shan, LI Lei, et al. Efficiency theory of electricity market and its evaluation method[J]. Power System Technology, 2009, 33(14):66-71.
[12]张天云,陈奎,魏伟,等. BP神经网络法确定工程材料评价指标的权重[J].材料导报,2012,26(2):159-163.ZHANG Tianyun, CHEN Kui, WEI Wei, et al. The determination of index weights for comprehensive evaluation of engineering materials with BP neural network[J]. Materials Review, 2012, 26(2):159-163.