基于模拟退火和粒子群算法的公共建筑能耗优化拆分研究
Split optimization research on public building energy consumption based on simulated annealing and particle swarm optimization algorithm
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摘要: 针对公共建筑分项计量中的能耗拆分问题,提出了改进的SA_PSO算法.该算法将模拟退火机制与粒子群算法相结合,引入粒子速度收缩因子和最优粒子轮盘赌策略进行扰动.利用该算法对公共建筑能耗拆分数学模型中的相关参数进行优化,即可得到逐时能耗拆分数据.仿真结果表明,改进的SA_PSO算法具有更好的收敛性能,能够有效地避免粒子陷入局部最小能耗参数修正值并快速到达全局最优修正.Abstract: For public building sub metering in energy resolution of problems, the improved SA_PSO algorithm was put forward. The algorithm simulated the combination of annealing mechanism and particle swarm optimization algorithm, introduced particle velocity shrinkage factor and the optimal particle roulette gambling strategies for perturbation. Using SA_PSO algorithm to optimize the public building energy resolution mathematical model parameters, the hourly energy consumption data from split could be gotten. The simulation results showed that SA_PSO algorithm had better convergence performance, could effectively avoid the particles falling into local minimum energy consumption parameters correction value and quickly reached the global optimum.
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