文章摘要
马天祥,贾伯岩,张智远,等.基于二层规划的能源互联微电网能量优化调度方法[J].电力系统自动化,2019,43(16):34-43. DOI: 10.7500/AEPS20181220006.
MA Tianxiang,JIA Boyan,ZHANG Zhiyuan, et al.Energy Optimal Dispatching Method of Micro-energy Internet Based on Bi-level Programming[J].Automation of Electric Power Systems,2019,43(16):34-43. DOI: 10.7500/AEPS20181220006.
基于二层规划的能源互联微电网能量优化调度方法
Energy Optimal Dispatching Method of Micro-energy Internet Based on Bi-level Programming
DOI:10.7500/AEPS20181220006
关键词: 能源互联微电网  二层规划  能量优化调度  能量枢纽  广义Nash均衡  帝国竞争算法
KeyWords: micro-energy internet  bi-level programming  energy optimal dispatching  energy hub  generalized Nash equilibrium  imperial competition algorithm
上网日期:2019-06-21
基金项目:国家自然科学基金资助项目(51277056);国家电网公司总部科技项目(kj2018-063)
作者单位E-mail
马天祥 国网河北省电力有限公司电力科学研究院, 河北省石家庄市 050021 matianxiang1986@126.com 
贾伯岩 国网河北省电力有限公司电力科学研究院, 河北省石家庄市 050021  
张智远 国网河北省电力有限公司, 河北省石家庄市 050021  
程肖 河北省送变电有限公司, 河北省石家庄市 050051  
沈宏亮 国网河北省电力有限公司, 河北省石家庄市 050021  
范伟 国网河北省电力有限公司保定供电分公司, 河北省保定市 071000  
摘要:
      针对能源互联微电网能量优化调度问题,采用二层规划理论进行建模。以能量枢纽转化矩阵为上层决策变量,以系统综合运行成本最小为目标函数,构建上层模型;以电能子网、热能子网、气能子网以及交通子网的优化运行计划为下层决策者,以能源子网运行经济性指标为目标,计及各能源子网运行的必要约束,构建下层模型。分析得到模型的广义Nash均衡和Stackelberg-Nash均衡,采用反向学习机制改进帝国竞争算法,并采用改进的帝国竞争算法对所建立的模型设计求解流程。最后,算例分析表明,所建立的模型适用于多能互补协调的能源互联微电网能量优化调度问题,能充分发挥系统运行的经济性。
Abstract:
      Aiming at the energy optimal dispatching problem of micro-energy internet, the bi-level programming theory is used to build the model. Taking the transformation matrix of energy hub as the upper decision variable while the minimum comprehensive operation cost as the objective function, the upper model is constructed. Taking the optimal operation plan of electric energy sub-grid, heat energy sub-grid, gas energy sub-grid and traffic sub-grid as the lower decision-makers, while taking the economic indices of energy sub-networks as goals, the lower model is constructed with necessary constraints of energy sub-network operation. The generalized Nash equilibrium and Stackelberg-Nash equilibrium of the model are obtained. The imperial competition algorithm is improved by using the reverse learning mechanism, and the solving process is designed by using the improved imperial competition algorithm. Finally, an example shows that the model is applicable to the energy optimal dispatching of micro-energy internet considering multi-energy complementary and coordination, and can fully utilize the economy of system operation.
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