Εξώφυλλο

Research on cross-building energy storage management system based on reinforcement learning

Αποθηκεύτηκε σε:
Εκδόθηκε σε:Journal of Physics: Conference Series vol. 2936, no. 1 (Jan 2025), p. 012018
Κύριος συγγραφέας: Xin, Ming
Άλλοι συγγραφείς: Wang, Yanli, Zhang, Ruizhi, Zhang, Jibin, Liu, Xinan
Έκδοση:
IOP Publishing
Θέματα:
Routers
Computing costs
Linear programming
Dynamic programming
Algorithms
Energy storage
Mixed integer
Integer programming
Stochastic programming
Linear functions
Διαθέσιμο Online:Citation/Abstract
Full Text - PDF
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022 |a 1742-6588 
022 |a 1742-6596 
024 7 |a 10.1088/1742-6596/2936/1/012018  |2 doi 
035 |a 3159430997 
045 2 |b d20250101  |b d20250131 
100 1 |a Xin, Ming  |u State Grid Heilongjiang Electric Power Company Limited , Harbin, Heilongjiang, 150090, China 
245 1 |a Research on cross-building energy storage management system based on reinforcement learning 
260 |b IOP Publishing  |c Jan 2025 
513 |a Journal Article 
520 3 |a This study considers a cross-building energy storage system in which the objective function of each step is a piecewise linear function of decision variables and state variables. Therefore, the objective function can be modeled as piecewise linear programming and then transformed into a mixed integer linear programming (MILP) problem. However, as a multi-stage stochastic programming problem in which we utilize approximate dynamic programming (ADP) to tackle the computational issues, we need to solve the objective function multiple times. To further decrease computational cost, we propose several approximate algorithms to determine variable splitting, which degrades the problem to a linear programming problem. We use approximate techniques to solve the problem and design experiments to verify our conclusion. Numerical experiments show that our algorithm greatly reduces the time needed to solve the problem under the condition of minimal loss of accuracy. The simulation experiment in a Python environment further proves that the cross-building energy storage management system based on energy routers and control centers is better than the energy system of each building working alone to maximize the benefits. 
653 |a Routers 
653 |a Computing costs 
653 |a Linear programming 
653 |a Dynamic programming 
653 |a Algorithms 
653 |a Energy storage 
653 |a Mixed integer 
653 |a Integer programming 
653 |a Stochastic programming 
653 |a Linear functions 
700 1 |a Wang, Yanli  |u State Grid Heilongjiang Electric Power Company Limited , Harbin, Heilongjiang, 150090, China 
700 1 |a Zhang, Ruizhi  |u State Grid Heilongjiang Electric Power Company Limited , Harbin, Heilongjiang, 150090, China 
700 1 |a Zhang, Jibin  |u State Grid Heilongjiang Electric Power Company Limited , Harbin, Heilongjiang, 150090, China 
700 1 |a Liu, Xinan  |u School of Management, Harbin Institute of Technology , Harbin, Heilongjiang, 150001, China 
773 0 |t Journal of Physics: Conference Series  |g vol. 2936, no. 1 (Jan 2025), p. 012018 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3159430997/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3159430997/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch