Research on the optimization of the clean heating system for regional residential buildings based on the multi-objective optimization strategy

Abstract

For the residential building district heating (RBDH) system, choosing the appropriate combination of heat sources according to local conditions is the key to improving economic efficiency. In this study, three climatic regions in China were selected, namely, a hot summer and cold winter region, cold region, and severe cold region. Among them, Nanjing, Tianjin, and Shenyang were selected as typical representative cities in the hot summer and cold winter region, cold region, and severe cold region, respectively. Taking the levelized cost of heat (LCOH) as the economic evaluation index and considering the carbon emission cost of the system operation, the energy consumption and the CO2 emissions were analyzed. TRNSYS software was used to simulate and analyze the system performance. The multi-objective optimization based on a genetic algorithm was proposed to optimize system parameters. From an economic point of view, the SA system was suitable for the hot summer and cold winter region, the SAS system was suitable for the cold region, and the SE system was suitable for the severe cold region. The operation control strategy based on quality adjustment can reduce heating energy consumption and maintain indoor temperatures at approximately 20°C. The proportion of clean energy heating in the optimized heating system decreased after the multi-objective optimization strategy. However, the initial investment and maintenance costs of the system were reduced, which reduced the LOCH of the system. Therefore, the multi-objective optimization strategy can effectively reduce the heating costs.