论文标题
指标和拥挤的基于距离的进化算法，用于加热和电力经济发射调度
Indicator & crowding Distance-Based Evolutionary Algorithm for Combined Heat and Power Economic Emission Dispatch
论文作者
论文摘要
热量和动力已成为最必不可少的资源。但是，传统的产生能力和热量的方式效率低下并引起高污染。 CHP（联合热量和功率）可以很好地解决这些问题。近年来，人们对节能和环境保护的关注得到了更多关注，并且加热与电力经济排放调度（CHPEED）已成为重要的多目标优化问题。在本文中，提出了一种指标和拥挤的基于距离的进化算法（IDBEA）来处理此非凸面和非线性问题。考虑到阀点效应和电力传输损失，IDBEA在具有不同类型的三种标准测试系统上进行了测试，包括四个单元，五个单元和七个单元。在实验中，IDBEA与几种进化算法进行了比较，模拟结果表明，IDBEA具有强大的稳定性和优越性，而溶液比几种典型的算法表现出更好的收敛性和多样性。
Heat and power have become the most indispensable resources. However, the traditional ways of generating power and heat are inefficient and cause high pollution; a CHP (Combined Heat and Power) unit can solve these problems well. In recent years, more attention has been paid to energy conservation and environmental protection, and Combined Heat and Power Economic Emission Dispatch (CHPEED) has become an important multi-objective optimization problem. In this paper, an Indicator & crowding Distance-based Evolutionary Algorithm (IDBEA) is put forward for handling this non-convex and non-linear problem. With consideration of the valve-point effects and power transmission loss, IDBEA is tested on three standard test systems with different types, including four units, five units and seven units. In the experiment, IDBEA is compared with several evolutionary algorithms, the simulation results demonstrate that IDBEA has strong stability and superiority, while the solutions show better convergence and diversity than several typical algorithms.
