Load Distribution Optimization of Multi-Source District Heating System Based on Fuzzy Analytic Hierarchy Process

Abstract

As part of the energy structure transition, a key focus in district heating systems is the load distribution optimization of multiple heat sources under the specific heating network. A multi-objective optimization approach is discussed in this paper with a goal of achieving complementary advantages among heat sources, and improving the performance of the system in terms of economic cost, energy structure, and environmental benefits. This paper firstly establishes the mechanism model for multi-source district heating systems (MSDHS). Secondly, it proposes a multi-objective optimization system to account for the operation economy, energy structure, and environmental impact for MSDHS. The selected objectives are such selected that they could be justified and used in real sites. The weights of the objective functions are obtained via the fuzzy analytic hierarchy process (FAHP). Finally, this paper solves the optimization problem via particle swarm optimization (PSO) to obtain the optimal load distribution and tests its validity in a real heating system covering an area of 15 million m2. The optimized load distribution scheme achieves a coal saving of 1.14%, a natural gas saving of 0.53%, and a cost-saving of 3,270 during a 24-hour pilot operation. This study provides the basis for future optimization enhancement and algorithm development.