Recent trends in power management strategies for optimal operation of distributed energy resources in microgrids: A comprehensive review

Abstract

The current era in sustainable development is focused on the rapid integration of renewable energy sources driven by a wide range of socioeconomic objectives. Due to the inherent property of time-varying weather conditions, the intermittent sources, that is, Solar PV and Wind Energy, are considered as variable energy resources. The uncertainty and variability problem of these sources has brought many complications to distributed network operators to operate and control the complex or multi-microgrids with limited fast-ramping resources in order to maintain the power system flexibility. It led many researchers to find an alternative strategy since the conventional approaches are no longer adequate to handle the economic implications of operational decision making. At first, the brief review of various deterministic and probabilistic approaches, stochastic programming and robust optimisation strategies to address the uncertainty of variable energy resources are discussed. Furthermore, in the energy management point of view, the optimal scheduling problem of distributed sources of the microgrid is considered, and a brief review of optimisation models, advanced control strategies and demand response strategies to maximise economic benefits of microgrids are also elaborately presented. Finally, the multiagent-based distributed and decentralised control strategies for seamless integration of distributed generator units are reviewed under various configurations of the power grid along with communication network topologies.

Digital transformation of energy sector companies

“…Microgrids operate independently of the power grid and can be operated for up to 30 days without a central power grid. Microgrids are an on-site energy system with a large number of distributed energy resources and loads, which are operated, landed or locally operated and controlled independently [29]. Microgrids can provide temporary local power generation to avoid peak loads and store excess solar and wind energy, allowing them to send electricity when needed or work around the clock.…”

A comprehensive review of soft computing algorithms for optimal generation scheduling

“…The consensus gain functions are introduced to avoid the issues related to communication noise. The distributed pattern search algorithm is developed in 121,122 to choose the suitable communication topology while solving the nonconvex ED problem.…”

Distributed robust synergistic scheduling of electricity, natural gas, heating and cooling systems via alternating direction method of multipliers

“…However, different EHs generally owned by different operators, and thus the operators would be unwilling to upload all information such as operating states and device parameters to the central controller due to information security and privacy protection. Therefore, the distributed control is widely employed in IES, which is simply based on the local information and does not need the central controller 5,19,20,21,22,23 . So far, there are several distributed approaches employed to achieve the optimal scheduling for IES, such as Augmented Lagrangian Relaxation (ALR), 24,25 Benders Decomposition 26,27 and so on.…”

“…Therefore, the distributed control is widely employed in IES, which is simply based on the local information and does not need the central controller. 5,19,20,21,22,23 So far, there are several distributed approaches employed to achieve the optimal scheduling for IES, such as Augmented Lagrangian Relaxation (ALR), 24,25 Benders Decomposition 26,27 and so on. Besides, the ADMM algorithm 28 recently has become a popular method for distributed optimization, which combines the advantages of dual ascent and the method of multipliers.…”

“…Brand flow model of energy hub [Colour figure can be viewed at wileyonlinelibrary.com]withdrawn at node n. Constraints(18) to(20) limit the nodal pressure, natural gas flow and outputs of gas sources within their respective thresholds. π m,t −π n,t = sign gf mn,t…”