With the increasing consumption of energy, the efficiency of energy utilization urgently needs to be further improved. At present, the coordinated optimization control of the integrated energy system of multiple types of cooling, heating, and power equipment is an important way to improve the comprehensive energy efficiency of the regional power grid and reduce the operating cost of the power grid. Aiming at this scenario, this paper establishes a fine energy storage model by analyzing the uncertainty of wind power output and considering the influence of low temperature and other conditions on the energy storage device in the energy storage side. On the load side, the influence of comprehensive demand response of electricity and heat on system operation is analyzed, and a combined cold, heat, and electricity supply system including renewable energy and energy storage device is established. Aiming at the optimal total cost of the integrated energy cooling and heating triple power system collaborative optimization control, the crow search algorithm is used to iteratively optimize the configuration model of the triple power system. The four models are considered in the article include groundless heat pump and energy storage, excluding joint demand response, including ground source heat pump and traditional energy storage model, excluding joint demand response, including ground source heat pump and fine energy storage model, excluding joint demand response, including ground source heat pump and fine energy storage model, taking into account the joint demand response. The simulation results show that the cooperative optimization control strategy of the combined cooling, heating, and power system with renewable energy and fine energy storage device model can enhance the system’s schedulable space, improve the comprehensive energy utilization efficiency, and have considerable economic benefits.
The global demand for new energy has entered an unprecedented era, and the application of wind energy is one of the key contents in the development of new energy. Taking the “wind energy + application” in WOS (Web of Science) and CNKI database as the retrieval target, and the relevant papers retrieved as the research data, this paper uses the scientific knowledge mapping software (CiteSpace5) to carry out the keyword commonality analysis, cluster analysis and time mapping analysis on wind energy application scenarios.Finally, summarized research hotspots and forecasted its research trends in wind energy application scenarios in global and China. The results show that the international wind energy application research hotspots and trends are wind energy storage and wind power project site selection; In China there are offshore wind power and wind energy evaluation.
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