Photovoltaic intelligent community electric automobile and controllable load two-stage optimization scheduling method

Abstract

The invention discloses a photovoltaic intelligent community electric automobile and controllable load two-stage optimization scheduling method. A controllable load output model is established based on residential area, controllable load use characteristics and laws of thermodynamics, an electric automobile charging model is established based on electric automobile user driving characteristics, and a photovoltaic probability model is established based on the condition that photovoltaic output forecast deviations meet normal distribution; in day-ahead scheduling, time-of-use electricity price is set with profit maximization of an operator obtained after orderly charging of electric automobiles being as a target, and the electric automobiles are guided to be charged orderly through the time-of-use electricity price to reduce system valley-peak difference; taking consideration of influence of photovoltaic prediction and temperature prediction deviation on intelligent community electric automobile and controllable load co-scheduling, supply and demand unbalance due to day-ahead predication is corrected by introducing real-time scheduling; and in real-time scheduling, with the time-of-use electricity price set in day-ahead scheduling being as a basis, a day-ahead charging scheme of the electric automobiles is optimized to reduce real-time scheduling cost and stabilize load fluctuation. The method comprises day-ahead scheduling and real-time scheduling two-stage optimization.

Description

technical field [0001] The invention relates to a two-stage optimal scheduling method for electric vehicles and controllable loads in a photovoltaic smart community, belonging to the field of coordinated scheduling of electric vehicles and distributed energy. Background technique [0002] The rapid development of technologies such as electric vehicles, distributed energy, and smart homes has brought new challenges to traditional power distribution systems. The smart community is an important part of the smart grid, and the orderly scheduling of electric vehicles in the smart community is particularly important. As an emerging renewable energy, photovoltaics are widely used in residential quarters. The uncertainty of photovoltaic output makes it different from traditional loads, and there is a large deviation in the prediction of its output. However, in the research on the intelligent community, the temperature-type load represented by the air conditioner is relatively large...

AI Technical Summary

Problems solved by technology

At present, the research on scheduling mainly includes day-ahead collaborative scheduling and two-stage optimal scheduling. The day-ahead collaborative scheduling is only based on the scheduling of the day-ahead forecast data, and does not consider some deviations in the actual situation.

However, the existing two-stage optimal scheduling divides the optimization goal into two steps based on the primary and secondary relationship, and further optimizes the second goal on the basis of reaching the first optimization goal. Two-stage optimal dispatch combined with real-time. Some studies consider that the two-stage optimal dispatch combined with real-time is used to optimize the output structure of thermal power units, and electric vehicles are not considered as dispatch objects.

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