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Because of the problems of low operation efficiency and poor energy management of multienergy input and output system with complex load demand and energy supply, this paper uses the double-layer nondominated sorting genetic algorithm to optimize the multienergy complementary microgrid system in real-time, allocating reasonably the output of each energy supply end and reducing the energy consumption of the system on the premise of meeting the demand of cooling, thermal and power load, so as to improve the economy of the whole system. According to the system load demand and operation mode, the first layer of this double-layer operation strategy calculates the power required by each node of the microgrid system to reduce the system loss. The second layer calculates the output of each equipment by using nondominated sorting genetic algorithm with various energy values calculated in the first layer as constraint conditions, considering the operation characteristics of various equipment and aiming at economy and environmental protection. In this paper, a typical model of energy input-output is established. This model combines with the operation control strategy suitable for multienergy complementary microgrid system, considers the operation mode and equipment characteristics of the system, and uses a double-layer nondominated sorting genetic algorithm to optimize the operation of each equipment in the multienergy complementary system in real time, so as to reduce the operation cost of the system.

The cascade utilization of energy is an important subject of energy conservation research. This paper takes the gas-steam combined cycle as an object, A high-speed radial turbine steam differential pressure power generation system is proposed to replace the temperature and pressure reduction devices. Ebsilon is used to simulate and analyze the effect of temperature and pressure reduction scheme, steam differential pressure generation scheme and the influence of differential pressure generation on combined cycle unit performance. The steam differential pressure power generation system generate 382.81kW, the combined cycle unit load increased by 0.82%, resulting in an additional generation of 388.03kW. Considering the power generation benefits of back pressure unit of the combined cycle, the cost will be recovered in 3.06 years; considering the benefits of differential pressure power generation only, the payback period is 3.75 years. The payback period can be reduced to 2.4 years for the user side steam pressure differential generation system, The work of this paper provides a theoretical reference for the application and promotion of steam pressure difference power generation technology in integrated energy system.

Aiming at the optimization of an integrated energy system in a certain area, an efficient utilization system of flue gas waste heat in a combined cycle unit of coupled flue gas waste heat system, natural gas heating system, chemical water heating system and office area refrigeration and heating system is proposed. According to the energy demand analysis of natural gas heating system, chemical water heating system and office cooling and heating system in different seasons, the system uses the thermal medium water in the low-pressure economizer as the carrier of energy transfer and conversion. For the purpose of uniform utilization of heat, the heat medium water enters the water-water heat exchanger for heat exchange to heat the natural gas heating system, chemical water heating system and office cooling and heating system of the plant pressure regulating station. Finally, an integrated whole energy supply system is constructed, which improves the energy efficiency and economy of the integrated energy system. The practical operation shows that the flue gas waste heat efficient utilization system has the advantages of flexible application, strong seasonal adaptability and remarkable energy-saving effect. After application, the annual operating cost of the unit can be reduced by 2.7 million yuan. Relevant experience in this paper can be used as reference for subsequent similar generator sets.

Aiming at the problems of complex structures, variable loads, and fluctuation of power outputs of multienergy networks, this paper proposes an optimal allocation strategy of multienergy networks based on the double-layer nondominated sorting genetic algorithm, which can optimize the allocation of distributed generation (DG) and then improve the system economy. In this strategy, the multiobjective nondominated sorting genetic algorithm is adopted in both layers, and the second-layer optimization is based on the optimization result of the first layer. The first layer is based on the structure and load of the multienergy network. With the purpose of minimizing the active power loss and the node voltage offset, an optimization model of the multienergy network is established, which uses the multiobjective nondominated sorting genetic algorithm to solve the installation location and the capacity of DGs in multienergy networks. In the second layer, according to the optimization results of the first layer and the characteristics of different DGs (wind power generator, photovoltaic panel, microturbine, and storage battery), the optimization model of the multienergy network is established to improve the economy, reliability, and environmental benefits of multienergy networks. It uses the multiobjective nondominated sorting genetic algorithm to solve the allocation capacity of different DGs so as to solve the optimal allocation problem of node capacity in multienergy networks. The double-layer optimization strategy proposed in this paper greatly promotes the development of multienergy networks and provides effective guidance for the optimal allocation and reliable operation of multienergy networks.

Energy consumption of the data center is one of the main constraints for the development of data centers in developed regions. Shanghai has clearly defined the conditions and requirements for the construction of the data center. Through the scheme demonstration and economic analysis of gas distributed energy stations for the data center in Shanghai, the energy economy is the main factor restricting the gas distribution energy supply for the data center. Under the current background, the gas distributed energy station for the data center in Shanghai is more suitable for the construction of third-party investment operation and maintenance entities, which can significantly reduce the power usage effectiveness of the data center, although the annual energy cost of the data center increase significantly. At the same time, gas distributed energy stations need to pay attention to expand winter heat users and improve the equivalent utilization hours of energy stations to achieve greater economic benefits.