论文标题
BCS-GDE多目标优化算法,用于结合冷却,供暖和功率模型与决策策略
A BCS-GDE Multi-objective Optimization Algorithm for Combined Cooling, Heating and Power Model with Decision Strategies
论文作者
论文摘要
地区能源系统不仅可以减少能源消耗,而且还可以根据需求设定能源供应调度方案。除了经济成本外,在评估综合冷却,供暖和功率(CCHP)模型时,能源消耗和污染物更值得关注。在本文中,CCHP模型以经济成本,一级能源消耗和污染物排放为目标。提出了CCHP系统的数学表达,并建立了具有约束的多目标优化模型。根据不同的用法要求,设计了两种决策策略,可以适应不同的情况。此外,提出了具有最佳折衷解决方案处理机制(BCS-GDE)算法的广义差异进化,以首次优化CCHP模型。该算法通过优化不同容量设备的生产能力来提供最佳的能源调度方案。该模拟是在三种应用程序中进行的:酒店,办公室和住宅建筑物。模拟结果表明,本文建立的模型可以将经济成本降低72%,初级能源消耗73%,污染物排放量增加了88%。同时,Wilcoxon签名的额定测试表明,BCSGDE明显优于Omopso,NSGA-II和SPEA2,其置信度大于95%。
District energy systems can not only reduce energy consumption but also set energy supply dispatching schemes according to demand. In addition to economic cost, energy consumption and pollutant are more worthy of attention when evaluating combined cooling, heating and power (CCHP) models. In this paper, the CCHP model is established with the objective of economic cost, primary energy consumption, and pollutant emissions. The mathematical expression of the CCHP system is proposed, and a multi-objective optimization model with constraints is established. According to different usage requirements, two decision-making strategies are designed, which can adapt to different scenarios. Besides, a generalized differential evolution with the best compromise solution processing mechanism (BCS-GDE) algorithm is proposed to optimize the CCHP model for the first time. The algorithm provides the optimal energy scheduling scheme by optimizing the production capacity of different capacity equipment. The simulation is conducted in three application scenarios: hotels, offices, and residential buildings. The simulation results show that the model established in this paper can reduce economic cost by 72%, primary energy consumption by 73%, and pollutant emission by 88%. Concurrently, the Wilcoxon signed-rank test shows that BCSGDE is significantly better than OMOPSO, NSGA-II, and SPEA2 with greater than 95% confidence.