Abstract
Renewable energy sources have emerged as an alternative to meet the growing demand for energy, mitigate climate change, and contribute to sustainable development. The integration of these systems is carried out in a distributed manner via microgrid systems; this provides a set of technological solutions that allows information exchange between the consumers and the distributed generation centers, which implies that they need to be managed optimally. Energy management in microgrids is defined as an information and control system that provides the necessary functionality, which ensures that both the generation and distribution systems supply energy at minimal operational costs. This paper presents a literature review of energy management in microgrid systems using renewable energies, along with a comparative analysis of the different optimization objectives, constraints, solution approaches, and simulation tools applied to both the interconnected and isolated microgrids. To manage the intermittent nature of renewable energy, energy storage technology is considered to be an attractive option due to increased technological maturity, energy density, and capability of providing grid services such as frequency response. Finally, future directions on predictive modeling mainly for energy storage systems are also proposed.
Highlights
The exponential demand for energy has led to the depletion of fossil fuels such as petroleum, oil, and carbon
Linear programming can be considered a gooddepending approach on objective and constraints, while artificial intelligence methods are focused to approach depending on objective and constraints, while artificial intelligence methods are focused to situations approach where otherwhere methods lead to unsatisfactory results, including renewable generation forecasting and situations other methods lead to unsatisfactory results, including renewable generation optimal operation of energy storageofconsidering battery aging, among others
It uses simple operations to solve complex problems. It can obtain more than one optimal solution to choose from, which is an advantage over the mixed integer linear programming (MILP) formulation
Summary
The exponential demand for energy has led to the depletion of fossil fuels such as petroleum, oil, and carbon. Afew fewauthors authors have have solved solved the problem of of energy energy management managementusing usingdifferent differenttechniques techniquestotoachieve achieve an optimal microgrid operation These techniques must incorporate better solution strategies due to the integration of distributed generation, storage elements, and electric vehicles. Authors presented a comparative analysis on decision making strategies for microgrid energy management systems These methods are selected based on their suitability, practicability, and tractability, for optimal operation of microgrids. Authors presented a review on strategies and approaches used to implement energy management in stand-alone and grid-connected hybrid renewable energy systems. Authors showed previous solutions approaches, optimization techniques, and tools used to solve energy management problem in microgrids It includes heuristic, agent-based, MPC, evolutionary algorithms, and other methods. Authors showed in detail the optimization of distributed energy microgrids in both the grid-connected and stand-alone mode
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