A dynamic optimization operation control method and system for a distributed energy station

Abstract

The invention discloses a dynamic optimization operation control method and system for a distributed energy station. The method comprises the steps that a load prediction model and a thermodynamic system simulation model of the distributed energy station are combined and applied to actual operation guidance; by means of driving of a global optimization algorithm, dynamic rolling optimization of operation of the energy station is achieved, and operation parameters and instructions are automatically issued to bottom layer functional equipment to achieve unattended operation or few-person attended operation of the energy station. The system comprises a load prediction module. A simulation calculation module (such as a gas turbine, an internal combustion engine, a gas boiler, a waste heat boiler, a pump, a plate heat exchanger, a cooling tower, an electric refrigerator and a heat pump); a load prediction algorithm based on the artificial intelligence technology, a global optimization algorithm and a thermodynamic system simulation model are organically combined together through an optimization algorithm module and an environmental parameter monitoring module, and a dynamic optimizationcontrol method for the distributed energy station is constructed.

Description

technical field [0001] The present invention relates to the application technical field of the combination of distributed energy thermal system calculation model, load forecasting model and global optimization algorithm in the fields of power machinery and engineering, fluid machinery and engineering, heat transfer, artificial intelligence, etc., especially relates to a distributed energy A dynamic optimization operation control method and system for a station. Background technique [0002] In the planning and construction of distributed energy stations, thermal system simulation analysis is used to calculate energy station under different working conditions (annual average working conditions, summer working conditions, winter working conditions, extreme cold working conditions, extreme hot working conditions) The overall performance and status parameters are used to assist the technical and economic departments to evaluate the economic benefits and economic efficiency of th...

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Problems solved by technology

Therefore, it is difficult to meet the operation guidance requirements of distributed energy stations only based on the thermal system analysis results under several typical environmental conditions, resulting in the fact that distributed energy stations cannot be guaranteed to be in the best operating state in real time during actual operation.

[0004] Compared with traditional thermal power projects, distributed energy projects have more types of equipment, and there are complementary effects between them, such as the complementarity of waste heat boilers and gas boilers in cogeneration; The complementarity between refrigerators, heat pumps, gas boilers, and direct-fired engines; the integration of various functional modules such as electric energy storage, water / ice storage, and heat storage charging and discharging strategies, has resulted in the complexity of the operation mode of distributed energy stations. sex

[0005] At present, most distributed energy stations still rely on human experience to guide their operation, resulting in uneven operation levels of energy stations

In the case of low income, it is easy for the energy station to fall into a state of loss-making operation due to a mistake in the operation strategy

It is also difficult for operators to find out the dynamic characteristics of energy stations from the thermal analysis results of only some specific working conditions, so it is also difficult to form an optimal dynamic equipment group control strategy

When a distributed energy station is equipped with energy storage equipment, the complexity of its operating mode is often beyond the scope of human brainpower. It is difficult to make the energy station respond to user load in a timely manner based on human experience alone, and it is also difficult to operate under specific working conditions. Select the best group control strategy, which affects the economic benefits of the entire energy station

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