Practical multi-area bi-objective environmental economic dispatch equipped with a hybrid gradient search method and improved Jaya algorithm
Practical multi-area bi-objective environmental economic dispatch equipped with a hybrid gradient search method and improved Jaya algorithm
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DOI：
10.1049/iet-gtd.2016.0333
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发表时间：
2016-11
影响因子：
2.5
通讯作者：
R. Azizipanah‐Abarghooee;P. Dehghanian;V. Terzija
中科院分区：
文献类型：
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作者：
R. Azizipanah‐Abarghooee;P. Dehghanian;V. Terzija
整合到集中批发电力市场中的发电调度决策一直是输电系统运营商面临的一个具有挑战性的问题。究其原因，主要在于电网结构复杂、互联程度高、需求不断升级以及能源数量和价格的危机。为了使调度解决方案具有较高的可靠性和可接受的精度水平，需要考虑几个因素，其中可以提到阀点效应、多种燃料选择、不相交的禁区、机组的上/下斜率要求以及旋转储备约束，这些因素反过来又加剧了此类组合问题的非平滑性、非凸性、非线性和动态限制。本研究针对双目标多区域经济调度问题提出了一种新的优化工具集，以确定机组的输电潮流和功率输出，同时满足每个区域的系统需求和安全约束。所提出的架构建立在改进的基于梯度的 Jaya 算法的基础上，生成一组可行的帕累托最优解决方案，对应于通过新的鲁棒双目标梯度方法计算出的运营成本和排放量。事实证明，该投影算法能够快速准确地找到鲁棒的全局或近全局帕累托解。
Generation dispatch decision making integrated into a centralised wholesale electricity market has been always a challenging concern for transmission system operators. The reason lies mainly in the complex and highly-interconnected structure of the grid, escalated demand, and the crisis of the amount and price of energy. For the dispatch solutions to be highly reliable with an acceptable level of accuracy, several factors need to be taken into account, among which one can mention the valve-point effect, multiple fuel options, disjoint prohibited zones, up/down ramp rate requirements of units, as well as the spinning reserve constraints which, in turn, intensify the non-smoothness, non-convexity, non-linearity, and dynamic restriction of such combinatorial problems. This study proposes a new optimization toolset for the bi-objective multi-area economic dispatch problem to determine the transmission power flow and power output of units while satisfying system demand and security constraints at each area. The proposed architecture builds on an improved gradient-based Jaya algorithm to generate a feasible set of Pareto-optimal solutions corresponding to the operation cost and emission calculated through a new robust bi-objective gradient-based method. The projected algorithm is proved to be capable of finding the robust global or near-global Pareto solutions fast and accurate.