基于负荷预测的冰蓄冷空调系统运行策略研究
Research on operation strategy of ice cool storage air conditioning system based on load forecasting
摘要：
以重庆市某能源站冰蓄冷空调系统为研究对象，通过实地测试得到系统制冷机组侧、板式换热器侧实际运行性能偏差均在5%范围内，满足设计要求。以一周为周期，用户负荷呈3种类型：周一类型、周二~周五类型和周末类型。通过Matlab建立了3种遗传算法优化的BP神经网络负荷预测模型，并用测试样本进行了仿真训练，得到最大相对误差分别为16.5%，7.6%，13.9%。最后通过Matlab编程建模，得到了100%，75%，50%和25%负荷率下的运行优化控制策略。
Abstract：
Taking the ice cool storage air conditioning system of an energy station in Chongqing as the research object, obtains that the actual operating performance deviation of the chiller and the plate heat exchanger is within 5% to meet the design requirements. In a one-week cycle, there are three types of user load—Monday type, Tuesday to Friday type and weekend type. Establishes a load forecasting model of BP neural network optimized by genetic algorithm with Matlab, and trains the model with test samples. The results show that the maximum relative errors are 16.5%, 7.6% and 13.9%, respectively. Through Matlab programming modeling, obtains the optimal operation control strategy at 100%, 75%, 50% and 25% load rates, respectively.
Keywords:ice cool storage air conditioning system, genetic algorithm, BP neural network, control strategy, operation, load forecasting