Decision method for rolling optimization of wind and light storage cooperative scheduling

Abstract

The invention discloses a decision method for rolling optimization of wind and light storage cooperative scheduling. The decision method comprises the following implementation steps of: acquiring day-ahead prediction values of load, wind power of wind power farms and output power of photovoltaic power stations and data such as charging demand of each electric automobile recharging station; arranging a day-ahead plan of a next-day charging plan of each electric automobile recharging station, wherein the plan can meet energy demands of electric automobiles of each electric automobile recharging station and reduce the peak valley difference rate of equivalent load curves, so that the peak pitching pressure of the conventional machine sets is reduced, and the energy access level of renewable energy is improved; and continuously modifying the rolling of the charging plan of each electric automobile recharging station in rest time period of a current day in real time through the updated predication data acquired every hour such as the load, the wind power of the wind power farms and the output power of the photovoltaic power stations of the rest time period of the current day in the operation of the current day, so that the problem that an actual equivalent load curve smoothing effect of the current day is weakened by the charging plan of each electric automobile recharging station due to prediction errors is solved as possible.

Description

Technical field [0001] The invention relates to a rolling optimization decision-making method of wind-solar-storage cooperative scheduling. Background technique [0002] The technological development of renewable energy power generation methods such as wind power and photovoltaic power generation has gradually matured, and the proportion of power generation capacity has increased year by year. However, wind energy, solar energy and other energy sources have the characteristics of randomness and intermittentness. In particular, wind power generation has the characteristics of more power generation at night and lower reverse peak regulation characteristics during the day, making the system an equivalent load composed of load, wind power, and photovoltaic power. Compared with the original load curve, the peak-to-valley difference rate of the curve is significantly increased. The peak-shaving pressure faced by thermal power units in the system increases, which restricts the power gri...

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Problems solved by technology

However, energy sources such as wind energy and solar energy have the characteristics of randomness and intermittency, especially wind power generation has the characteristics of more power generation at night and lower anti-peaking characteristics during the day, which makes the equivalent load in the system composed of load, wind power, and photovoltaic power Compared with the peak-valley difference rate of the original load curve, the peak-to-valley difference rate of the curve has increased significantly, and the peak-shaving pressure faced by thermal power units in the system has increased, which has restricted the ability of the grid to accept more wind power and photovoltaic power generation power.

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