A Stochastic Spatiotemporal Decomposition Decision-Making Approach for Real-Time Dynamic Energy Management of Multi-Microgrids
- 2 September 2020
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Sustainable Energy
- Vol. 12 (2), 821-833
- https://doi.org/10.1109/tste.2020.3021226
Abstract
This paper studies the real-time dynamic energy management (DEM) of multi microgrids (MMGs) considering active and reactive power flow constraints, voltage constraints, battery operational characters, and uncertainties in the renewable generation and load. A stochastic spatiotemporal decomposition decision-making framework is proposed based on approximate dynamic programming (ADP) to make decentralized decisions in both spatial and temporal dimensions. The tie-line power and the state of charge (SOC) of the battery are coordinated in real time to deal with the uncertainties in the upcoming future, preserving the decision independence of MGs and periods. And the shift factors are derived to consider active and reactive power flow constraints of MMGs in the stochastic spatiotemporal decomposition framework. Moreover, the historical information is utilized offline to avoid the dependency on forecast information and iterative calculation, while near-optimal solutions can be obtained in real time. Case studies on several MMG test systems and a real MMG system demonstrate the effectiveness of the proposed approach.Keywords
Funding Information
- National Natural Science Foundation of China (51977081)
- Natural Science Foundation of Guangdong Province (2018A0303131001, 2019A1515010877)
- Fundamental Research Funds for the Central Universities (2019MS020)
This publication has 28 references indexed in Scilit:
- Novel Linearized Power Flow and Linearized OPF Models for Active Distribution Networks With Application in Distribution LMPIEEE Transactions on Smart Grid, 2016
- Optimal Operation for Community-Based Multi-Party Microgrid in Grid-Connected and Islanded ModesIEEE Transactions on Smart Grid, 2016
- A Two-Stage Model Predictive Control Strategy for Economic Diesel-PV-Battery Island Microgrid Operation in Rural AreasIEEE Transactions on Sustainable Energy, 2016
- A Fully Distributed Power Dispatch Method for Fast Frequency Recovery and Minimal Generation Cost in Autonomous MicrogridsIEEE Transactions on Smart Grid, 2015
- Fully distributed multi‐area economic dispatch method for active distribution networksIET Generation, Transmission & Distribution, 2015
- Load Scheduling and Power Trading in Systems With High Penetration of Renewable Energy ResourcesIEEE Transactions on Smart Grid, 2015
- A Centralized Energy Management System for Isolated MicrogridsIEEE Transactions on Smart Grid, 2014
- Wind Power Forecasts Using Gaussian Processes and Numerical Weather PredictionIEEE Transactions on Power Systems, 2013
- SMART: A Stochastic Multiscale Model for the Analysis of Energy Resources, Technology, and PolicyINFORMS Journal on Computing, 2012
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of MultipliersFoundations and Trends® in Machine Learning, 2010