Improving capacity configuration and load scheduling for an integrated multi-sourced cogeneration system

Abstract

The integration of renewable energy sources and fossil fuel e.g. coal in a heat and power cogeneration system has been proven to be an effective way to reduce CO2 emissions. An integrated multi-sourced cogeneration (IMC) system consisting of wind, solar photovoltaic (PV), and coal-fired combined heat and power (CHP) plant on the energy supply side, is studied in this paper. A bi-level collaborative optimization model for capacity configuration and load scheduling of the wind-PV-coal IMC system is developed. In the upper level, the capacity of wind farm and PV farm are optimized with the enumeration method, while the load scheduling under typical annual conditions is optimized with adaptive particle swarm optimization algorithm in the lower level. The results show that the optimal capacities of wind and PV are 120 MW and 280 MW for the IMC system, respectively. The annual and typical day load scheduling with optimal wind and PV capacities are analyzed. The result of the load scheduling shows that heating and power load distribution unevenly between the two CHP units contributes to reducing total standard coal consumption, which saves 34.96 t in a typical day during the heating season. This study can provide a reference for the capacity configuration and operation scheduling of the IMC system.