New-energy energy storage configuration optimization method based on short-period mean value variance

Abstract

The invention discloses a new-energy energy storage configuration optimization method based on short-period mean value variance. Wind and light mean values and variance data of the former period are collected by taking 15min as one period; by taking the mean value data as the basis, the variance data is subjected to reasonable weighting to decide load shedding proportion, so as to decide a tendering value to be supplied to the market in the next operating period; and in the operation process, new energy active smoothing output is realized through complementation control, so as to optimize the energy storage capacity finally. Compared with the conventional new energy fixed-proportion load shedding mode, the method provided by the invention can greatly reduce the energy storage capacity needed to be configured for new energy, and the new energy active output stability can be ensured; compared with other load shedding calculation methods, the algorithm disclosed in the invention is low in needed data size and easy to realize; and in addition, benefits of new energy in the real-time electricity market can be increased, and quite high feasibility and practical value can be achieved.

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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