A new energy storage allocation optimization method based on short-period mean variance

Abstract

The invention discloses a new energy storage configuration optimization method based on short-period mean value variance. Taking 15 minutes as a cycle, the wind and light mean value and variance data of the previous operation cycle are collected; The data is reasonably weighted to determine the load reduction ratio, so as to determine the bidding value that can be supplied to the market in the next operation cycle; in the operation process, the smooth output of new energy active power is achieved through complementary control, and the ultimate goal of optimizing energy storage capacity is achieved. Compared with the traditional new energy fixed ratio load shedding, the method of the present invention can significantly reduce the energy storage capacity required for the new energy and ensure the stability of the active output of the new energy. Compared with other load shedding calculation methods, the algorithm of the present invention The amount of required data is small and easy to implement, which is conducive to the profitability of new energy in the real-time power market, and has good feasibility and practical value.

Description

technical field [0001] The invention relates to the field of power system control, in particular to a new energy storage configuration optimization method based on short-period mean variance. Background technique [0002] Distributed power generation is one of the ways to accommodate new energy power generation widely used in the world. However, in the existing power grid, the consumption of distributed new energy mainly faces two challenges. (1) The fluctuation of the output power of new energy is unavoidable; as the number of distributed new energy connected to the distribution network gradually increases, the fluctuation of active power will cause the stability of the system frequency and affect the operation safety. (2) The prediction error of new energy power generation is large; in the day-ahead market mode, the actual output of new energy is very different from the forecast, which limits the possibility of new energy power generation participating in the electricity ...

AI Technical Summary

Problems solved by technology

(1) The fluctuation of the output power of new energy is unavoidable; as the number of distributed new energy connected to the distribution network gradually increases, the fluctuation of active power will lead to the stability of the system frequency and affect the operation safety

(2) The prediction error of new energy power generation is large; in the day-ahead market mode, the actual output of new energy is very different from the forecast, which limits the possibility of new energy power generation participating in the electricity market

However, as the number of distributed new energy connected to the distribution network gradually increases, the output of new energy will fluctuate in active power. In order to smooth the output, it is necessary to equip with energy storage

At the same time, in order to comply with the day-ahead market rules, it leads to the problem of "long forecast time for new energy and large difference between output and forecast". To solve this problem, energy storage must also be equipped

However, the cost increases rapidly with the capacity

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