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A novel parallel-series hybrid meta-heuristic method for solving a hybrid unit commitment problem

机译:解决混合单元承诺问题的新型并行系列混合元启发式方法

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Unit commitment is a traditional mixed-integer non-convex problem and remains a key optimisation task in power system scheduling. The high penetration of intermittent renewable generations such as wind and solar as well as mass roll-out of plug-in electric vehicles (PEVs) impose significant challenges to the traditional unit commitment problem, not only by significantly increasing the complexity of the problem in terms of the dimension and constraints, but also dramatically change the problem formulation. In this paper, a new hybrid unit commitment problem considering renewable generation scenarios and charging and discharging management of plug-in electric vehicles is first formulated. To effectively solve the problem, a novel parallel-series hybrid meta-heuristic optimisation method is then proposed, which combines a hybrid topology binary particle swarm optimisation, the self-adaptive differential evolution algorithm and a lambda iteration method, to simultaneously and intelligently determine the binary on/off status of each thermal unit, the generation power of online units, as well as the demand side management of plug-in electric vehicles. The proposed parallel-series hybrid method is first assessed on a 10-unit benchmark, and then on a case where renewable generation and smart PEV management are integrated. Numerical results confirm the superiority of the proposed new algorithm in comparison with some popular meta heuristic approaches. (C) 2017 Elsevier B.V. All rights reserved.
机译:机组承诺是传统的混合整数非凸问题,并且仍然是电力系统调度中的关键优化任务。间歇性可再生能源(如风能和太阳能)的高普及率以及插电式电动汽车(PEV)的大规模推出,不仅大大增加了问题的复杂性,还对传统的机组承诺问题提出了重大挑战。的维度和约束,也极大地改变了问题的表述方式。本文首先提出了一种新的混合动力单位承担问题,该问题考虑了可再生能源发电情景以及插电式电动汽车的充放电管理。为了有效解决该问题,提出了一种新颖的并行系列混合元启发式优化方法,该方法结合了混合拓扑二进制粒子群优化,自适应差分进化算法和λ迭代方法,可以同时智能地确定每个热单元的二进制开/关状态,在线单元的发电功率以及插电式电动汽车的需求侧管理。首先以10个单位为基准评估提出的并行串联混合动力方法,然后再将可再生能源发电和智能PEV管理集成在一起。数值结果证实了与一些流行的元启发式方法相比,该新算法的优越性。 (C)2017 Elsevier B.V.保留所有权利。

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