Method for real-time scheduling of multi-energy complementary micro-grids based on rollout algorithm

Patent metadata

Field	Value
Publication number	US-11095127-B2
Application number	US-201716488059-A
Country	US
Kind code	B2
Filing date	Nov 8, 2017
Priority date	Mar 21, 2017
Publication date	Aug 17, 2021
Grant date	Aug 17, 2021

Abstract

The invention relates to a method for real-time scheduling of multi-energy complementary micro-grids based on a Rollout algorithm, which is technically characterized by comprising the following steps of: Step 1, setting up a moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids with random new-energy outputs, and establishing constraint conditions for the real-time scheduling; Step 2, establishing a target function of the real-time scheduling; Step 3, dividing a single complete scheduling cycle into a plurality of scheduling intervals, and finding one basic feasible solution meeting the constraint conditions for the real-time scheduling based on a greedy algorithm; and Step 4, finding a solution to the moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids by using the Rollout algorithm based on the basic feasible solution from Step 3. With the consideration of the fluctuations in the new-energy outputs, the present invention solves the problems of low speed and low efficiency of a traditional algorithm at the same time, enabling high-speed efficient multi-energy complementary micro-grid real-time scheduling.

First claim

The invention claimed is:

1. A method for real-time scheduling of multi-energy complementary micro-grids based on a Rollout algorithm, characterized by comprising the following steps of:
Step 1, setting up a moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids with random new-energy outputs, and establishing constraint conditions for the real-time scheduling;
Step 2, establishing a target function of the real-time scheduling for the moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids with the random new-energy outputs, with the goal of minimum operating cost of a micro-grid system in a moving-horizon Markov decision cycle;
Step 3, dividing a single complete scheduling cycle into a plurality of scheduling intervals, and finding one basic feasible solution meeting the constraint conditions for the real-time scheduling based on a greedy algorithm; and
Step 4, finding a solution to the moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids by using the Rollout algorithm based on the basic feasible solution from Step 3;
wherein the constraint conditions established for the real-time scheduling in Step 1 comprises:
micro-grid electric equilibrium constraints, storage battery operating constraints, exchange electric power constraints for the micro-grids and a main grid, and electric power output constraints for combined heat and power equipment;
the micro-grid electric equilibrium constraints are as follows:

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in the formula, t is a time parameter; p G (t) is exchange electric power for the micro-grids and the main grid at a time t, which is positive during purchasing of electricity from the main grid and negative during selling of electricity to the main grid; N is the quantity of the combined heat and power equipment; p i c (t) is output electric power of the i th combined heat and power equipment at the time t; p B (t) is charging/discharging power of the storage battery at the time t, which is negative during charging and positive during discharging; p w (t) is generated output of wind power at the time t; and p D (t) is an electric load demand at the time t;
the storage battery operating constraints are as follows:

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Assignees

• State Grid Tianjin Electric Power Co
• State Grid Corp China
• Univ Southeast

Inventors

• Huo Xianxu
• Jiang Ling
• Zhao Honglei
• Zhao Baoguo
• Wang Xudong
• Li Guodong
• Xiang Tianchun
• Xu Ke
• Qi Yan
• Wu Lei
• Ma Shiqian
• Yan Jingjing
• Wang Kai
• Xu Qingshan
• Sun Lu
• Zeng Aidong

Classifications

• H02J2103/30

  Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks · CPC title

• H02J7/865

  Battery or charger load switching, e.g. concurrent charging and load supply (H02J7/50 takes precedence) · CPC title

• H02J2101/28

  Wind energy · CPC title

• G05B2219/2639

  Energy management, use maximum of cheap power, keep peak load low · CPC title

• Y02E40/70

  Smart grids as climate change mitigation technology in the energy generation sector · CPC title