METHOD FOR CONTROLLING ELECTRICAL ENERGY LOAD IN INDUSTRIAL ENTERPRISES COMBINED WITH SOLAR POWER PLANT AND ENERGY STORAGE SYSTEM

Abstract

Usage: The claimed utility model relates to industrial power engineering, renewable energy sources, energy storage systems, and intelligent control, and is intended for managing the electrical load of industrial enterprises integrated with solar power plants and energy storage systems. The objective is to reduce the maximum electrical load of an industrial enterprise, smooth the load curve, determine the required power and energy capacity of the energy storage system, optimally manage its charging and discharging modes, and reduce electricity costs during morning and evening peak periods.The essence of the utility model: A method for managing energy consumption based on probabilistic forecasting for photovoltaic energy storage systems (CN115423153B), considered the closest analogue, includes forecasting electricity generation using an LSTM neural network and controlling the energy storage system based on a model-based predictive control algorithm. In the claimed method, this solution is adapted to the operating mode of industrial enterprises using data on the enterprise's annual load, work shifts, electricity tariffs, ambient temperature, as well as climatic and technical parameters affecting the solar power plant's electricity generation. Based on this data, the LSTM neural network is used to forecast the enterprise's daily load and the solar power plant's electricity generation.In the daytime tariff zone, when peak load intervals are identified, the available solar power plant capacity is directed to power the industrial plant's load to reduce power drawn from the external power grid. Based on forecasting results, the capacity and energy storage system required to reduce the load to the average power level during morning and evening peak periods are determined. Then, using a model-based predictive control algorithm, the charging source, charging power, discharging power, and charging and discharging times of the energy storage system are determined, taking into account the projected load and generation, tariff zones, and the current state of charge of the energy storage system.Technical result: the implementation of the claimed method ensures a reduction in the maximum values ​​of the electrical load of an industrial enterprise during morning and evening peak periods, smoothing the daily load schedule, determining the required power and energy capacity of the energy storage system, optimally determining the source, power and time of charging and discharging the energy storage system, increasing the efficiency of using a solar power plant and an energy storage system, as well as reducing the costs of consumed electrical energy taking into account tariff zones.