Power distribution network collaborative planning method considering DG correlation and EV demand response

Abstract

The invention discloses a power distribution network collaborative planning method considering DG correlation and EV demand response; according to the method, a wind-photovoltaic independent normal distribution sample is generated by adopting a monte carlo random sampling method and a wind speed illumination probability distribution model, and the wind-photovoltaic independent normal distributionsample is converted into a related sample by applying an improved correlation matrix method so as to calculate wind-photovoltaic output power; a multi-target double-layer mixed integer linear programming model is established, a planning layer carries out site selection and constant volume on a wind generator, a photovoltaic component and a charging pile, and a running layer takes the lowest cost of electricity purchasing, network loss, load fluctuation penalty, waste electricity penalty and the like into consideration based on the thought of a penalty function, and expresses the investment, the DG output, the power flow, the EV charging an discharging price and the like in a linear constraint mode; a Voronoi diagram is applied to partition a road network system to obtain the service rangeof an EV charging station so as to determine an upper limit of the EV response; and the time scale of the unified double-layer model is converted into a single layer for solving in a unified mode, soas to obtain the planning result of the wind generator, the photovoltaic component and the charging station.

Description

technical field [0001] The invention belongs to the technical field of urban distribution network planning, and in particular relates to a distribution network collaborative planning method considering DG correlation and EV demand response. Background technique [0002] Driven by green development, the penetration rate of wind turbines, photovoltaics and electric vehicles, as well as the power consumption of distribution networks are increasing day by day, and the peak and valley loads increase accordingly, resulting in a decline in the economy of the power system and a waste of resources. However, the output of wind turbines and photovoltaics is easily affected by environmental factors, and has strong randomness and timing, and the output of wind turbines and photovoltaics in different regions is correlated. Therefore, it is of great significance to consider the correlation between wind turbines and photovoltaic nodes and consider EV charging and discharging demand response...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the above-mentioned deficiencies in the prior art, the distribution network collaborative planning method that considers DG correlation and EV demand response provided by the present invention solves the problem of excessive peak-to-valley load difference in the existing urban distribution network

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