Open AccessOptimal energy management strategy in microgrids with mixed energy resources and energy storage system
Author(s) -
Semero Yordanos Kassa,
Zhang Jianhua,
Zheng Dehua
Publication year - 2020
Publication title -
iet cyber‐physical systems: theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.308
H-Index - 7
ISSN - 2398-3396
DOI - 10.1049/iet-cps.2019.0035
Subject(s) - microgrid , energy storage , distributed generation , renewable energy , integer programming , energy management , grid , energy management system , scheduling (production processes) , power system simulation , state of charge , computer science , linear programming , electric power system , mathematical optimization , automotive engineering , engineering , power (physics) , energy (signal processing) , electrical engineering , battery (electricity) , operations management , mathematics , statistics , physics , geometry , algorithm , quantum mechanics
The continued growth of distributed generation (DG) in the electrical grid has led to the expansion of microgrids. Microgrids contain distributed power generation units, energy storage devices, and controllable loads with the capability to operate in both grid‐connected and island modes. The economic operation of a microgrid is achieved through an energy management system that optimally schedules DGs and storage devices and continuously balances supply and demand. In this study, a formulation of optimal unit commitment (UC) and dispatch scheduling of DGs in a grid‐connected microgrid system is presented. Mixed‐integer linear programming is used to implement the optimal UC and dispatch scheduling model. The objective is to minimise the overall operating cost of the system by optimally utilising an energy storage device and a combined heat and power (CHP) generation unit using load and renewable energy generation prediction. Operational constraints such as generation limits of DGs, battery charging/discharging limits and state‐of‐charge limits are to be satisfied during all intervals of operation. Simulation results indicate that the operational cost of the system is significantly reduced through optimal scheduling of an energy storage system and a CHP unit using the proposed strategy.