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Multi-objective dynamic unit commitment optimization for energy-saving and emission reduction with wind power

机译:风电节能减排的多目标动态机组承诺优化

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As a clean energy, wind power is massively utilized in net recent years, which significantly reduced the pollution emission created from unit. This article referred to the concept of energy-saving and emission reducing; built a multiple objective function with represent of the emission of CO2& SO2, the coal-fired from units and the lowest unit fees of commitment; Proposed a algorithm to improving NSGA-D (Non-dominated Sorting Genetic Algorithm-II) for the dynamic characteristics, consider of some constraint conditions such as the shortest operation and fault time and climbing etc.; Optimized and commitment discrete magnitude and Load distribution continuous quantity with the double-optimization strategy; Introduced the fuzzy satisfaction-maximizing method to reaching a decision for Pareto solution and also nested into each dynamic solution; Through simulation for 10 units of wind power, the result show that this method is an effective way to optimize the Multi-objective unit commitment modeling in wind power integrated system with Mixed-integer variable.
机译:风力发电作为一种清洁能源,近年来已被大量使用,大大减少了单位产生的污染排放。本文提到了节能减排的概念;建立了代表二氧化碳和二氧化硫排放量,单位燃煤量和最低单位承诺费的多目标函数;提出了一种改进NSGA-D动态特性的算法,该算法考虑了最短操作,故障时间和爬升等约束条件。通过双重优化策略优化并承诺离散量和负载分配连续量;引入了模糊满意度最大化方法来决定帕累托解,并将其嵌套到每个动态解中;通过对10个风电单元的仿真,结果表明,该方法是优化混合整数变量风电集成系统中多目标机组组合建模的有效途径。

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