Abstract
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.
Highlights
Multienergy complementary microgrid system is a multiinput and multi-output energy system, which generally covers integrated power supply, gas supply, heating supply, cold supply, and other energy systems as well as related communication and information infrastructure. e efficient economic and environmental protection operation of multienergy complementary system is the development direction of the energy industry in the future
According to the system load demand and operation mode, the first layer of this two-layer operation strategy calculates the power required by each node of the microgrid system to reduce the system loss and 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
E results show that the active power loss and voltage deviation of the multienergy complementary microgrid system are reduced by 51.41% and 41.89%, respectively, after using the real-time optimal control strategy based on double-layer nondominated sorting genetic algorithm. e total operation cost and pollutant emission control cost of the multienergy complementary microgrid system are reduced by 9.37% and 20.81%, respectively, when the power load priority operation mode is used; when the cooling and
Summary
Multienergy complementary microgrid system is a multiinput and multi-output energy system, which generally covers integrated power supply, gas supply, heating supply, cold supply, and other energy systems as well as related communication and information infrastructure. e efficient economic and environmental protection operation of multienergy complementary system is the development direction of the energy industry in the future. E structure of the multienergy complementary microgrid system is shown, which mainly includes wind turbine (WT), photovoltaic power generation (PV), internal combustion engine (GE), absorption chiller (AC), electric refrigerator (EC), electric boiler (EB), battery storage (BS), and cooling/heating storage (HS) equipment [10]. Based on the characteristics of multienergy complementary microgrid system, this paper proposes two different operation strategies: power load priority and cooling and heating load priority, so as to optimize the operation mode of each equipment in the microgrid system. (ii) When the power load is higher than the renewable energy generation capacity, the wind turbine and photovoltaic power supply directly to the power load, and the excess load is supplemented by electric energy storage discharge At this time, the cooling load is met by electric refrigeration. The charge and the discharge of energy storage are the same as those in scheme i
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