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Energies 2017, 10(9), 1288; https://doi.org/10.3390/en10091288

Optimal Energy Management for Microgrids with Combined Heat and Power (CHP) Generation, Energy Storages, and Renewable Energy Sources

1
College of Information Science and Technology, Engineering Research Center of Digitized Textile and Fashion Technology, Ministry of Education, Donghua University, Shanghai 201620, China
2
Department of Automation, Shanghai Jiaotong University, Shanghai 200240, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Pedro Faria
Received: 26 July 2017 / Revised: 20 August 2017 / Accepted: 25 August 2017 / Published: 29 August 2017
(This article belongs to the Special Issue Distributed Energy Resources Management)
Full-Text   |   PDF [344 KB, uploaded 30 August 2017]   |  

Abstract

This paper studies an energy management problem for a typical grid-connected microgrid system that consists of renewable energy sources, Combined Heat and Power (CHP) co-generation, and energy storages to satisfy electricity and heat demand simultaneously. We formulate this problem into a stochastic non-convex optimization programming to achieve the minimum microgrid’s operating cost, which is difficult to solve due to its non-convexity and coupling feature of constraints. Existing approaches such as dynamic programming (DP) assume that all the system dynamics are known, which results in a high computational complexity and thus are not feasible in practice. The focus of this paper is on the design of a real-time energy management strategy for the optimal operation of microgrids with low computational complexity. Specifically, derived from a modified Lyapunov optimization technique, an online algorithm with random inputs (e.g., the charging/discharging of energy storage devices, power from the CHP system, the electricity from external power grid, and the renewables generation, etc.), which requires no statistic system information, is proposed. We provide an implementation of the proposed energy management algorithm and prove its optimality theoretically. Based on real-world data traces, extensive empirical evaluations are presented to verify the performance of our algorithm. View Full-Text
Keywords: microgrids; renewable energy; storage; scheduling; co-generation microgrids; renewable energy; storage; scheduling; co-generation
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Zhang, G.; Cao, Y.; Cao, Y.; Li, D.; Wang, L. Optimal Energy Management for Microgrids with Combined Heat and Power (CHP) Generation, Energy Storages, and Renewable Energy Sources. Energies 2017, 10, 1288.

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