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Optimal Energy Pricing and Dispatch for a Multi-Microgrid Industrial Park Operating Based on Just-In-Time Strategy

机译:基于即时战略的多微电网工业园区最优能源定价与调度

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Energy dispatch in multi-user networks with limited energy resources can lead to competitive markets where individuals would place bids with the goal of maximizing their own profits. Game theoretic techniques are elegant mathematical candidates to solve such problems. However, existence of equilibrium points cannot be guaranteed this way. Even if such points are reached, Pareto optimality of the solution cannot be ensured. In this paper, an alternative approach based on multiobjective optimization is proposed in order to maximize the “collective benefits” of a group of players. Instead of allowing individuals to compete for resources, a neutral third party finds a solution that is Pareto optimal and meets all constraints associated with individual users. A multi-microgrid industrial park is considered where each microgrid represents a manufacturing plant. The park is assumed to be equipped with a central controller that purchases energy from the grid and dispatches it among the individual microgrids. When this energy is limited due to capacity constraints, each microgrid would try to receive a larger portion so as to increase its production level. Naturally, these individual objectives are contradictory. As such, the problem is formulated as multi-objective optimization and solved using a modified approach based on goal programming to ensure the Pareto optimality of the overall solution. This way, the limited energy resource is shared in a way that maximizes the collective profit of the group, instead of individuals.
机译:具有有限的能源资源的多用户网络中的能量调度可能导致竞争市场,其中个人将获得最大化自身利润的目标。游戏理论技术是优雅的数学候选人来解决这些问题。然而,这种方式无法保证均衡点的存在。即使达到了这样的点,也不能确保解决方案的帕累托最优性。在本文中,提出了一种基于多目标优化的替代方法,以最大限度地提高一组球员的“集体益处”。而不是允许个人竞争资源,所中立的第三方找到一个解决方案,该解决方案是帕累托最佳的,符合与个别用户相关的所有约束。考虑多微电网工业园区,其中每个微电网代表制造厂。假设公园配备有一个中央控制器,该控制器从网格中购买能量,并在各个微电网之间调度。当由于容量限制而受到限制的限制时,每个微电网将尝试接收更大的部分以增加其生产水平。当然,这些个体目标是矛盾的。因此,该问题被配制为多目标优化,并使用基于目标编程的修改方法解决,以确保整个解决方案的帕累托最优性。这样,有限的能源资源以最大化集团的集体利润而不是个人的方式共享。

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