Abstract
With the development of social economy and technology, the coupling relationship between different energy supply systems (cold, heat, electricity, gas, etc.) has become closer, and a comprehensive energy system with multiple subjects has become a development trend. In order to pursue a clean and efficient energy system, increase the consumption rate of new energy and reduce operating costs, a multiagent integrated energy system operation optimization method including combined heat and power (CHP) operators and photovoltaic user groups is proposed. In this paper, the distributed operation optimization method of integrated energy system based on multiple agents is studied. Considering the demand response of electric energy and thermal energy, and considering economy and user satisfaction, the distributed optimization scheduling model of integrated energy system with multiple agents is established to achieve the centralized optimization effect.
Highlights
Efficient, clean, and low-carbon are the mainstream directions of energy development in the world today
By establishing a demand response model that takes into account electrical and thermal energy, energy sharing between users and energy sharing between combined heat and power (CHP) operators and users are established
The research in this paper focuses on the integrated energy system with CHP operators and several photovoltaic users
Summary
Clean, and low-carbon are the mainstream directions of energy development in the world today. Compared with traditional energy production, the combined heat and power unit [2,3] can simultaneously supply electricity and heat to users, which greatly improves the operating efficiency of the system. Due to the advantages of cleanliness and high efficiency, distributed photovoltaic [4,5] (photovoltaic, PV) systems have developed rapidly. For the above reasons, integrated energy systems including CHP systems and photovoltaic user groups are increasing. By establishing a demand response model that takes into account electrical and thermal energy, energy sharing between users and energy sharing between CHP operators and users are established. The basic optimization model formed by CHP operators and photovoltaic user groups can minimize system operating costs and improve user satisfaction
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