High-proportion photovoltaic power distribution network reactive power optimization method considering day-ahead random-intra-day rolling distribution

By establishing a few days optimization model and performing intraday rolling optimization, and combining distributed algorithms to optimize the reactive power output strategy, the power fluctuations and grid instability caused by high proportion of photovoltaic access to the distribution network are solved, and more efficient and reliable distribution network operation is achieved.

CN119726985APending Publication Date: 2025-03-28YUSHU POWER SUPPLY CO OF STATE GRID QINGHAI ELECTRIC POWER CO +1
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Patent Information

Application Number
CN202411859137.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-17
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

High proportion of photovoltaic access to the distribution network leads to power fluctuations and grid instability, and existing reactive power optimization methods are difficult to effectively deal with the uncertainty of photovoltaic power generation and load.

Method used

Monte Carlo simulation method combined with mixed integer linear programming (MILP) model was used to establish a recently optimized model to predict the uncertainty of photovoltaic power generation and load, and real-time adjustments were made through intraday rolling optimization and distributed algorithms (such as alternating direction multipliers method, ADMM) to optimize the reactive power output strategy.

Benefits of technology

It improves the operating stability and economy of the distribution network, reduces grid losses and operating costs, improves power quality, and ensures the stable operation of the system under different working conditions.

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Abstract

The invention relates to a high-proportion photovoltaic power distribution network reactive power optimization method considering day-ahead random-intra-day rolling distribution. Monte Carlo simulation is combined with an M ILP model to establish a day-ahead optimization model, output strategies of a photovoltaic inverter and a micro gas turbine are predicted and optimized, and network loss and operation cost are minimized; on the basis, DPMU real-time data is used for carrying out intra-day rolling optimization, and a reactive power output strategy is dynamically adjusted; a model is constructed by taking reactive power loss minimization as a target, and reactive power resources are coordinated by using an ADMM algorithm; and finally, realizing continuous optimization through closed-loop control and effect evaluation. The system stability can be improved, the operation cost can be reduced, the electric energy quality can be improved, the adaptability and the optimization precision can be enhanced, and the reactive power optimization problem of the high-proportion photovoltaic power distribution network can be effectively solved.
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