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Hierarchical Collaborative Optimal Scheduling of Economy Energy Efficiency in Energy Internet Based on Cooperative Game

机译:基于合作游戏的能源互联网经济能源效率的分层协作优化调度

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As the development direction of energy field in the future, energy Internet is helpful to realize the efficient utilization of energy, help to play potential of multi energy complementary advantages, achieve the purpose of energy saving and emission reduction, and meet the goal of building a clean, low-carbon, safe and efficient new generation energy system. Under the background of the interaction between the park and the regional energy Internet, firstly, the basic framework of interaction between typical the park and the regional energy Internet is introduced, and the stratification phenomenon under the geographical factors, scheduling factors and energy management factors is explained. Secondly, on the basis of establishing typical the lower level park and the upper level regional energy Internet model, the day-ahead exergy efficiency optimization scheduling model of the lower level park energy Internet model, and the day-ahead economic optimization scheduling model of upper level regional energy Internet are proposed, and the energy efficiency and economic multi-objective collaborative optimization scheduling problem are mapped into the cooperative game strategy. Then, it introduces the solution process of hierarchical collaborative optimization scheduling based on cooperative game in detail, and expounds the effect and function of outer cooperative game and inner cooperative game. Finally, the rationality and superiority of the hierarchical collaborative optimization model and method based on cooperative game are verified by example analysis and comparison.
机译:作为未来能源领域的发展方向,能源互联网有助于实现能源有效利用,有助于发挥多能量互补优势的潜力,达到节能减排的目的,并满足建设的目标清洁,低碳,安全高效的新一代能源系统。在公园与区域能源互联网之间的相互作用的背景下,介绍了典型公园与区域能源互联网之间的基本互动框架,以及地理因素,调度因素和能源管理因素下的分层现象是解释。其次,在建立典型的较低级别公园和上层区域能源互联网模式的基础上,较低级别的升高效率优化调度模型的较低级别公园能源互联网模型,以及鞋面的日前经济优化调度模型提出级别区域能源互联网,能源效率和经济多目标协同优化调度问题映射到合作游戏策略。然后,详细介绍了基于协作游戏的分层协作优化调度的解决方法,并阐述了外部合作游戏和内部合作游戏的效果和功能。最后,通过示例分析和比较验证了基于合作游戏的分层协同优化模型和方法的合理性和优越性。

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