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Security Constrained Generation Scheduling Using Harmony Search Optimization Case Study: Day-ahead Heat and Power Scheduling

机译:使用和谐搜索优化的安全约束发电调度案例研究:日前热电调度

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Security Constraint Generation Scheduling (SCGS) is one of the most important issues in modern power system shortterm operation. In the SCGS the optimal and secure operation of power system has been taken into account. SCGS includes the timing and production of available energy resources in order to maintaining customer demands. In this paper, we present a new approach for SCGS in Day-Ahead market considering both heat and power demands entire the system. Harmony Search Algorithm, (HSA) which is a recent meta-heuristic optimization algorithms is addressed in this paper to solve the SCGS problem which is a large-scale, non-convex, nonlinear with both continuous and discrete variables. It is shown that HSA, as a meta-heuristic optimization algorithm, may solve power system scheduling problem (Heat and Power) in a better fashion in comparison with the other evolutionary search algorithm that are implemented in such complicated issue. HSA was conceptualized using the musical process of searching for a perfect state of harmony. Compared to the earlier meta-heuristic optimization algorithms, HSA imposes fewer mathematical requirements that can be easily adopted for various types of engineering optimization problems, such as Combined Heat and Power SCGS (CHP-SCGS). An adopted case study is conducted to facilitate the effectiveness of the proposed method. This case study is recently presented in order to analysis the Day-Ahead power system studies with a 24-h scheduling horizon, which considers the Hydro-Thermal and conventional Unit Commitment (UC) problem. Simulation results show the effectiveness and fastness of the proposed method.
机译:安全约束生成调度(SCGS)是现代电力系统短期运行中最重要的问题之一。在SCGS中,已经考虑了电力系统的最佳和安全运行。 SCGS包括可用能源的时间安排和生产,以维持客户需求。在本文中,我们考虑到整个系统的热量和功率需求,提出了一种在日前市场中SCGS的新方法。为了解决SCGS问题,它是一种大规模的,非凸的,具有连续变量和离散变量的非线性算法,本文提出了一种新的元启发式优化算法-和谐搜索算法(HSA)。结果表明,HSA作为一种元启发式优化算法,与在这种复杂问题中实现的其他进化搜索算法相比,可以更好地解决电力系统调度问题(热力和动力)。 HSA是通过寻求完美和谐状态的音乐过程来概念化的。与早期的元启发式优化算法相比,HSA提出了较少的数学要求,可以轻松地将其用于各种类型的工程优化问题,例如热电联产SCGS(CHP-SCGS)。进行了案例研究,以提高所提出方法的有效性。最近提出了此案例研究,以分析具有24小时调度范围的日前电力系统研究,该研究考虑了水力热力发电和常规机组承诺(UC)问题。仿真结果表明了该方法的有效性和快速性。

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