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A strategy to optimize the multi-energy system in microgrid based on neurodynamic algorithm

机译:基于神经动力学算法的微电网优化多能量系统的策略

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In this paper, we design multi-energy management strategy for power-supply participants, heat-supply participants and consumers in a microgrid. The objectives of the management strategy are to maximize the social welfare and to balance the energy supply and demands. With the transmission loss, the proposed social welfare model, subject to practical operation constraints, is formulated as a nonconvex optimization problem. Based on a sufficient condition, a equivalent problem transformed from the primary optimization problem is presented as a convex problem. A neurodynamic algorithm based Karush-Kuhn-Tucker(KKT) conditions and projection with fewer neurons is developed to regulate the resource output of each participant. The convergence of the applied algorithm is proved by Lyapunov function. Finally, numerical simulations are used to prove the effectiveness of the designed management strategy. (C) 2018 Elsevier B.V. All rights reserved.
机译:在本文中,我们设计了微电网供暖参与者,供热参与者和消费者的多能量管理策略。 管理战略的目标是最大限度地提高社会福利,并平衡能源供需。 随着传输损失,拟议的社会福利模型受到实际操作约束的,被制定为非凸优化问题。 基于足够的条件,从主优化问题转换的等效问题被呈现为凸面问题。 基于神经动力学算法的Karush-Kuhn-tucker(KKT)条件和具有较少神经元的投影以调节每个参与者的资源输出。 Lyapunov函数证明了应用算法的收敛。 最后,使用数值模拟来证明设计的管理策略的有效性。 (c)2018 Elsevier B.v.保留所有权利。

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