Research on the model and method for energy-saving generation dispatching

Energy-Saving generation dispatching can effectively reduce the energy consumption and harmful gas emission, which is of significant social benefits, helps to further clean energy resources development and promote the sustainable development of power system and the whole society. Therefore, it is of theoretical and practical significance. The establishment of a suit of effective models and algorithms for energy-saving generation dispatching is the core to ensure its effective implementation. This paper first expatiates that the implementation of energy-saving generation dispatching is of great significance for the promotion of clean energy resources and the achievement of energy saving and environmental protection goals. Then, after an in-depth study on the theory and practice of the energy-saving generation dispatching, the article analyzes the short-term and long-term feasible development models. That is, the article establishes a short-term mathematical model according to the energy consumption to dispatch, which is designed directly to reduce the system energy consumption as a major objective. Furthermore, from the foreseeable power industry institution in China and the development of energy and environment protection policies, economic optimization mode may be needed to be used in the energy-saving generation dispatching. Therefore, this article establishes a mathematical dispatching model according to energy price in the premise of the implement of related two-part electricity price. The energy price in this model takes various objectives and constraints into consideration such as energy-saving, environmental protection and economy. Afterwards, for the above-mentioned two types of models, this paper proposes a method combined with heuristic dynamic programming and linear programming for the generation output solution of day-ahead generation scheduling. Finally, numerical simulation results in a practical power system demonstrate the correctness and validity of the proposed model and method.