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Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 29210


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10006446
Hierarchical Operation Strategies for Grid Connected Building Microgrid with Energy Storage and Photovoltatic Source
Abstract:
This paper presents hierarchical operation strategies which are minimizing operation error between day ahead operation plan and real time operation. Operating power systems between centralized and decentralized approaches can be represented as hierarchical control scheme, featured as primary control, secondary control and tertiary control. Primary control is known as local control, featuring fast response. Secondary control is referred to as microgrid Energy Management System (EMS). Tertiary control is responsible of coordinating the operations of multi-microgrids. In this paper, we formulated 3 stage microgrid operation strategies which are similar to hierarchical control scheme. First stage is to set a day ahead scheduled output power of Battery Energy Storage System (BESS) which is only controllable source in microgrid and it is optimized to minimize cost of exchanged power with main grid using Particle Swarm Optimization (PSO) method. Second stage is to control the active and reactive power of BESS to be operated in day ahead scheduled plan in case that State of Charge (SOC) error occurs between real time and scheduled plan. The third is rescheduling the system when the predicted error is over the limited value. The first stage can be compared with the secondary control in that it adjusts the active power. The second stage is comparable to the primary control in that it controls the error in local manner. The third stage is compared with the secondary control in that it manages power balancing. The proposed strategies will be applied to one of the buildings in Electronics and Telecommunication Research Institute (ETRI). The building microgrid is composed of Photovoltaic (PV) generation, BESS and load and it will be interconnected with the main grid. Main purpose of that is minimizing operation cost and to be operated in scheduled plan. Simulation results support validation of proposed strategies.
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References:

[1] Claudio A. Cañizares, Rodrigo Palma-Behnke, Daniel E. Olivares, Ali Mehrizi-Sani “Trend in Microgrid Control” IEEE Trans. Smart Grid, vol. 5, no. 4, pp.1905-1919, July 2014.
[2] Dan Wu, Fen Tang, Tomislav Dragicevic, Juan C. Vasquez and Josep M. Guerrero, "Autonomous Active Power Control for Islanded AC Microgrids With Photovoltaic Generation and Energy Storage System", IEEE Trans. Energy Conversion, vol. 29, no. 4, pp.882-892 ,Dec 2014.
[3] Peng Zhao, Siddharth Suryanarayanan, and Marcelo Godoy Simões, “An Energy Management System for Building Structures Using a Multi-Agent Decision-Making Control Methodology”, IEEE Trans. Industry Application, vol. 49, no. 1, pp.322-330, Jan/Feb 2013.
[4] Quanyuan Jiang, Meidong Xue, and Guangchao Geng, “Energy Management of Microgrid in Grid-Connected and Stand-Alone Modes” IEEE Trans. Power Systems, vol. 28, no. 3, pp.3380-3389, Aug 2013.
[5] Wenbo Shi, Na Li, Chi-Cheng Chu, and Rajit Gadh, “Real-Time Energy Management in Microgrids”, IEEE Trans. Smart Grid, to be published.
[6] Zhaoyu Wang, Bokan Chen, Jianhui Wang and Chen Chen, “Networked Microgrids for Self-Healing Power Systems”, IEEE Trans. Smart Grid, VOL. 7, NO. 1, pp.310-319, Jan 2016.
[7] Jie Li, Yikui Liu, Lei Wu, “Optimal Operation for Community Based Multi-Party Microgrid in Grid-Connected and Islanded Modes”, IEEE Trans. Smart Grid, to be published.
[8] Hao Xing, Minyue Fu, Zhiyun Lin, and Yuting Mou, "Decentralized Optimal Scheduling for Charging and Discharging of Plug-In Electric Vehicles in Smart Grids", IEEE Trans. Power Systems, to be published.
[9] Wenbo Shi, Xiaorong Xie, Chi-Cheng Chu, and Rajit Gadh,"Distributed Optimal Energy Management in Microgrids", IEEE Trans. Smart Grid, Vol. 6, No. 3, pp.1137 – 1146, May 2015.
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