Generation and storage scheduling of combined heat and power

Abstract

Generation scheduling of combined heat and power extends the traditional power generation scheduling by satisfying the thermal load in parallel with the electrical load; the integration of storages into the system further improves the economic efficiency of the traditional generation scheduling. Such combined heat and power scheduling of the dispatchable generators and storages, which incorporates the dispatch of both electrical and thermal energy storages with the scheduling of the dispatchable generators, is realised as the main contribution of this study, by enhancing the technique of the metaheuristics-enabled “storage-integrated generation scheduling”. The metaheuristic approach relieves the modelling complexity of the scheduling, by using fewer decisions variables of the optimisation than the existing methods like linear programming. The non-dominated sorting genetic algorithm II (NSGA-II) serves as the metaheuristic tool, which supports concurrent binary and real-number encoding that fits the variable types of the generation scheduling. The combined heat and power scheduling is evaluated in a hypothetical building to serve the electrical and thermal loads driven by the occupants' comfort requirements, which proves the advantage of integrating the storages into the system, and in the perspective of application, has the value of guiding through the building heat and power operation.