The application of a gas-fired CCHP can effectively solve seasonal shortages of electricity and gas. To realize providing investment decision for gas-fired CCHP in Beijing, first, the paper analyses the status of gas-fired CCHP systems in Beijing; second, the technology structure and economic benefits of gas-fired CCHP systems are analysed; third, a technical economic evaluation framework of a gas-fired CCHP is built, which analyses the cascade utilization and energy saving effects of a heat and power energy system in a gas-fired CCHP system. Analysis of the gas-fired CCHP system economy and the factors that influence the economic performance is also performed, as well as a sensitivity analysis. In addition, the paper also analyses an energy efficiency sharing model of a cooling, heating and power system that considers the grid enterprises' economic efficiency. Finally, an empirical analysis of a trigeneration project control centre in the Beijing Gas Group is carried out. Research results show that gas-fired CCHP system is good to both customers and beneficial, fuel price and electricity price will influence revenue of Gas-fired CCHP system greatly, a reasonable energy efficiency sharing ratio will help to the recovery of investment in Gas-fired CCHP.

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In order to achieve more efficient and optimised resource scheduling, this research carried out a multi‐objective task resource allocation method for low‐voltage station edge computing based on hierarchical Bayesian adaptive sparsity. Based on hierarchical Bayesian adaptive sparsity, the multi‐objective task resource allocation technical framework for edge computing in low‐voltage stations is established, which is composed of end pipe edge cloud; After collecting real‐time operation data of power distribution equipment, substation terminals, transmission terminals, etc. in the architecture end, it is transmitted to the data middle platform and service middle platform of the Internet of Things management platform in the cloud through the edge Internet of Things agent; Set and solve the constraint conditions, and build a multi type flexible load hierarchical optimal allocation model; The abnormal area topology identification sub module of multi‐objective task resource of low‐voltage station area edge computing is used to identify the abnormal area topology of the current low‐voltage station area; Taking it as input, the multi‐objective task resources of edge computing are allocated, and the multi‐objective task resources allocation method of edge computing in low pressure platform area is realized under the differential evolution algorithm. The experimental results show that the proposed method has good convergence effect, strong distribution ability, relatively gentle increase in energy consumption, and the calculated results are basically consistent with the actual values, with good effectiveness.

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