Sensitivity analysis based interaction cost calculation method for microgrid and power distribution grid

Abstract

A sensitivity analysis based interaction cost calculation method for a microgrid and a power distribution grid comprises the following steps of: acquiring basic structure and parameter information of the microgrid participating in interaction; forecasting the output and the load power of a distributed power supply in a scheduling period, and acquiring time-sharing electricity cost information of the power distribution grid; considering the electricity purchasing cost of the microgrid in the scheduling period, the electricity sell gain and the power generation cost of the distributed power supply by taking minimum running cost of the microgrid as a target function, and building a microgrid running optimal scheduling model; setting a constraint condition of a microgrid optimal scheduling problem; solving a microgrid optimal scheduling mode formed by the target function and the constraint condition by using an optimization tool to obtain running cost corresponding to a scheduling plan; acquiring interactive time frame information of the power distribution grid; and respectively calculating positive interaction cost and negative interaction cost of the microgrid, and acquiring the relation between the interaction capacity and the interaction cost during the positive interaction of the microgrid through piecewise linearization. By the method, the interaction between the microgrid and the power distribution grid is achieved at the minimum cost.

Description

technical field [0001] The invention relates to a method for calculating the interaction cost between a microgrid and a distribution network. In particular, it relates to a sensitivity analysis-based interaction cost calculation method between a micro-grid and a distribution network, which is suitable for demand-side response analysis of a distribution network containing a micro-grid. Background technique [0002] The access of distributed energy to the grid has promoted the development and innovation of the power industry, which has impacted the traditional monopoly development environment, made the power market more competitive, and also challenged the management of distributed energy. Demand response can effectively reduce the impact of the randomness, volatility and uncertainty of new energy power generation on the power grid, improve the reliability of power consumption, and improve the economic benefits of the power system. From the perspective of user response motiva...

AI Technical Summary

Problems solved by technology

However, due to the long update cycle of the time-of-use electricity price, it is difficult to achieve the expected goal of "shaving peaks and filling valleys" by applying a time-of-use electricity price mechanism to all users, and it is likely to cause the peak load to be transferred to other time periods

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