Microgrid Energy Management Strategy with Battery Energy Storage System and Approximate Dynamic Programming

In the past few years, the application and research community has expressed a lot of interest in managing energy and power while using distributed generation systems. Electricity generation and its usage coordination are vital aspects of energy efficiency that can help in saving energy, decreasing energy costs, and fulfilling global emission objectives. Owing to the relevance of the topic, here, the researchers have presented a comparative and critical review of recent developments in the fields of energy management systems (EMSs) and power management systems (PMSs). Furthermore, the researchers also reviewed the various EMS and PMS methods that could be used for reviewing microgrid (MG) and nanogrid (NG) systems. The EMS for MG and NG systems helps in addressing important economic objectives like minimisation of operational costs after optimising the fuel costs, emission costs, and battery degradation costs, while also improving the life of the MG devices. Alternatively, the PMS helps in addressing technical objectives like improving the stability, flexibility, reliability, and quality of MG and NG systems. The researchers have also discussed the drawbacks and challenges affecting the widespread application of EMSs and PMSs.

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“…Another EMS based on dynamic programming for controlling the MG system was proposed in [52]. It included wind energy and battery systems.…”

Section: Energy Management Based On Dynamic Programming (Dp) and Rule-based Methodsmentioning

confidence: 99%

A Review of Energy Management and Power Management Systems for Microgrid and Nanogrid Applications

2021

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“…DP is an optimization framework proposed by Bellman in the mid 1950s, which splits a multi-stage decisionmaking problem into a sequence of simpler subproblems and thus, results in a computational time reduction [108,109]. The DP framework for operation optimization of islanded and grid-connected MGs has been widely addressed [57,110,111,112]. For instance, in [57], the SOC of batteries is quantized in each time-step (between its limits) during the whole time horizon.…”

Section: Dynamic Programmingmentioning

confidence: 99%

Energy management system optimization in islanded microgrids: An overview and future trends

Raya-Armenta¹,

Bazmohammadi²,

Aviña-Cervantes

et al. 2021

Renewable and Sustainable Energy Reviews

104

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“…In recent years, MDP appears to be a promising mathematical formulation of the optimizing microgrid operation problem [63,64]. A number of studies clearly demonstrate the effectiveness of energy microgrids management using MDP-based methods: dynamic programming [65,66], deep RL [55,56,58,67], and Monte Carlo models [57,68].…”

Section: Microgrid Mdp-based Environment Simulatormentioning

confidence: 99%

Optimal Operation Control of PV-Biomass Gasifier-Diesel-Hybrid Systems Using Reinforcement Learning Techniques

et al. 2020

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The importance of efficient utilization of biomass as renewable energy in terms of global warming and resource shortages are well known and documented. Biomass gasification is a promising power technology especially for decentralized energy systems. Decisive progress has been made in the gasification technologies development during the last decade. This paper deals with the control and optimization problems for an isolated microgrid combining the renewable energy sources (solar energy and biomass gasification) with a diesel power plant. The control problem of an isolated microgrid is formulated as a Markov decision process and we studied how reinforcement learning can be employed to address this problem to minimize the total system cost. The most economic microgrid configuration was found, and it uses biomass gasification units with an internal combustion engine operating both in single-fuel mode (producer gas) and in dual-fuel mode (diesel fuel and producer gas).

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Microgrid Energy Management Strategy with Battery Energy Storage System and Approximate Dynamic Programming

Cited by 12 publications

References 21 publications

A Review of Energy Management and Power Management Systems for Microgrid and Nanogrid Applications

A Review of Energy Management and Power Management Systems for Microgrid and Nanogrid Applications

Energy management system optimization in islanded microgrids: An overview and future trends

Optimal Operation Control of PV-Biomass Gasifier-Diesel-Hybrid Systems Using Reinforcement Learning Techniques

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