Risk-aware short term hydro-wind-thermal scheduling using a probability interval optimization model
Risk-aware short term hydro-wind-thermal scheduling using a probability interval optimization model
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DOI：
10.1016/j.apenergy.2016.12.031
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发表时间：
2017-03
期刊：
影响因子：
11.2
通讯作者：
J. J. Chen-J.;Y. Zhuang;Y. Li;Ping Wang;Y. L. Zhao;C. Zhang
中科院分区：
文献类型：
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作者：
J. J. Chen-J.;Y. Zhuang;Y. Li;Ping Wang;Y. L. Zhao;C. Zhang
由于风电资源的不确定性和可利用水资源的复杂约束，短期水火电联合调度是电力系统运行规划中最困难的优化问题之一。本文提出了一种风险感知的优化模型，称为概率区间优化（PIO），从风险和收益的角度可靠地评估HWTS。PIO将不确定的风电功率视为概率区间变量，根据风电功率的概率分布来评估风电风险，以风电接入前后系统发电成本的降低来体现收益。针对PIO模型，提出了一种进化的捕食与被捕食策略（EPPS）。EPPS通过引入逃逸机制和分类机制，动态调整算法的探索和利用能力。此外，一个启发式的修复机制，而不是惩罚函数的方法，适用于处理复杂的等式和不等式约束的HWTS。基于3个HWTS系统的仿真研究表明，风险感知PIO模型具有良好的可靠性，适用于考虑不确定风电接入的HWTS求解; EPPS算法能够获得比其他算法更上级的解;启发式修复机制能够有效地处理HWTS复杂约束。
Due to the uncertainty of wind power and complex constraints of available hydro, short term hydro-wind-thermal scheduling (HWTS) is one of the most difficult optimization problems in the operational planning of power systems. This paper presents a risk-aware optimization model, named probability interval optimization (PIO), to reliably evaluate the HWTS from the perspective of risk and profit. In PIO, the uncertain wind power is deemed as a probability interval variable, the risk of wind power is assessed by its probability distribution, and the profit is manifested by the decrease of generation cost between the same system with and without wind power integrated. For solving the PIO model, an evolutionary predator and prey strategy (EPPS) is proposed in this paper. The EPPS focuses on dynamically adjusting the algorithm’s exploration and exploitation abilities by introducing an escaping mechanism and a classification mechanism. In addition, a heuristic repair mechanism, instead of penalty function approach, is applied to handle the complex equality and inequality constraints of HWTS. Simulation studies based on three HWTS systems demonstrate that the risk-aware PIO model is well reliable and applicable to solve HWTS considering the uncertain wind power integrated, the EPPS algorithm can obtain superior solutions in comparison with other recently developed algorithms, and the heuristic repair mechanism is efficient for dealing with complex constraints of HWTS.