Hospital power grid load optimization control system and control method

Abstract

The invention discloses a hospital power grid load optimization control system. The system comprises a parameter acquisition module, a total cost calculation module, a constraint condition calculation module, a particle swarm algorithm module and an optimization control module. The invention also discloses a control method of the hospital power grid load optimization control system, which comprises the following steps of taking the output power of the power supply equipment and the input power of the electric equipment as particles, determining the initial speed and position of the particles according to constraint conditions, and taking the total cost of the hospital power grid as the target function of the particles, and performing iterative calculation by using a particle swarm algorithm until convergence, and obtaining the target output power of the power supply equipment and the target input power of the electric equipment in the next first optimization control period. The target power of the power grid is accurately predicted, and the fluctuation of the power grid load is reduced; and the stability and environmental protection of the power grid load are considered.

Description

technical field [0001] The invention relates to the technical field of power grid load control, in particular to a hospital power grid load optimization control system and control method. Background technique [0002] In recent years, as energy and environmental issues have become increasingly prominent, the proportion of renewable energy has gradually increased during the development of the power industry. Due to the randomness and volatility of renewable energy such as solar energy and wind energy, after they are connected to the grid, they also have a great impact on the optimal dispatch of the power system. The emergence of micro-grid provides effective means and ways for the comprehensive utilization of renewable energy, and is an effective way to solve the problem of centralized grid-connected distributed renewable energy for power supply. However, the randomness and volatility of distributed renewable energy will have a great impact on the safe and stable operation o...

AI Technical Summary

Problems solved by technology

[0004] At present, most of the methods for micro-grid optimization control are mainly the combination of day-ahead optimization and intra-day real-time control. The established model is relatively complicated and difficult in practical applications.

The traditional micro-grid optimization control method is prone to insufficient adjustable capacity when the electric load or renewable energy fluctuates, and even the excessive power interaction with the grid will cause relatively large fluctuations, which will affect the security and stability of the grid. run

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