A Sustainable Energy Management System for Isolated Microgrids

Solanki, Bharatkumar V.; Bhattacharya, Kankar; Cañizares, Claudio A.

doi:10.1109/tste.2017.2692754

Cited by 96 publications

(55 citation statements)

References 18 publications

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“…Aiming at minimizing the long‐term average running cost under actual operation and service constraints, a robust two‐stage optimization method was introduced in Reference . Model predictive control was integrated within an EMS to examine the possible impact of demand response on the total system emissions and economics of a microgrid . By using Stackelberg Game theory, Ma et al developed a multiparty energy management framework, where the microgrid operator acted as the leader and PV producers were the followers.…”

Section: Introductionmentioning

confidence: 99%

A prediction‐based optimization strategy to balance the use of diesel generator and emergency battery in the microgrid

Zhang

Dong

et al. 2020

Int J Energy Res

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This paper presents a prediction-based optimization strategy (POS) for the Energy Management System to balance the use of diesel generator (DG) and emergency battery (EB) in the microgrid. The POS is developed by combing two operating strategies, the "predictive analysis" and "optimal operation" in each scheduling period for the microgrid. Based on the predicted microgrid state and energy demand, a multi-objective mixed-integer nonlinear programming model (MOMINP) is constructed to minimize the fuel consumption and the regularization of battery charge/discharge subject to the practical constraints in the microgrid. This paper proposes a detailed scheme to deal with the multiple objectives and nonlinear constraints in the MOMINP, then the MOMINP is successfully converted into a mixed-integer linear programming model (MILP). And an adjustment strategy is designed to obtain the nearoptimal solution of the MOMINP based on the optimal solution of the MILP solved by using the CPLEX Optimizer. Experimental results show that in a basic scheduling period, the working time of DG in the POS-softmax regression strategy is shorter than the current operation, and the fuel consumption reduction ratio is about 15.3% with the same battery SoC value at the end of the scheduling. At the same time, the fuel consumption in the POS-accurate prediction strategy can be reduced by up to 54.9% compared with the POSsoftmax regression strategy and can be reduced by 61.8% compared to the current operation. Based on the comparative analysis of the actual case data of a micro-grid in 6 months, it can be seen that on average the POS works better than the current operation, with an approximately 23.6% decrease in the objective function and an additional 16.2% decrease with an accurate prediction. K E Y W O R D S energy management, microgrid, mixed-integer linear programming, multi-objective mixedinteger nonlinear programming, optimal operation

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Section: Introductionmentioning

confidence: 99%

A prediction‐based optimization strategy to balance the use of diesel generator and emergency battery in the microgrid

Zhang

Dong

et al. 2020

Int J Energy Res

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“…In this manuscript, the optimal operation management of CMGs is investigated that is regarded as one of the main challenges for CMGs. Several research have been conducted to fix issues relevant to technical, economic, and environmental aspects of CMGs operation . In Xiang et al, a scenario‐based robust energy management strategy is proposed considering the worst‐case amount of demanded power and renewable generation.…”

Section: Introductionmentioning

confidence: 99%

“…Authors in Hong et al proposed an energy scheduling algorithm for building MGs aiming at mitigating power quality concerns by co‐scheduling of controllable devices in building MGs. In addition, a distributed energy management approach is introduced in Olivares et al and a centralized energy management system is presented in Solanki et al and Marzband et al for grid‐connected and isolated MGs, respectively. In addition, a multi‐objective approach for energy management of MGs is introduced in Shen et al in which the regulation of grid tie‐line fluctuations is considered as one of the objectives of the proposed approach.…”

Section: Introductionmentioning

confidence: 99%

Optimal energy management of community microgrids: A risk-based multi-criteria approach

Abniki

Taghvaei²,

Mohammadi‐Hosseininejad

2018

Int Trans Electr Energ Syst

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Summary Community microgrids (CMGs) have been developing nowadays as an initiative to operate modern electric distribution systems in a more economical, reliable, and environmentally friendly manner than the existing centralized electricity grid which benefited both distribution system operator and consumers. In this paper, the optimal energy management of CMGs is formulated considering distributed energy resources and thermal and electrical demands in CMGs. The objective function of the proposed methodology consists of the total cost of CMGs operation, the total cost of energy not supplied in CMGs, and total cost of emission produced in CMGs in order to comprehensively manage the CMG operation. Moreover, the uncertainty of renewable energy resources, electricity price, and demanded power of CMGs are considered in the proposed methodology. In addition, two risk evaluation measures are employed to cope with existing risks in the CMG operation. Furthermore, a number of sensitivity studies are accomplished to investigate the effects of important parameters on the performance of the proposed approach. The effectiveness of the proposed methodology is examined on a test system.

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“…With the continuous establishment and rapid development of microgrid projects, the corresponding EMS [9], [10] has gradually become a prominent research area. The electric energy generated by photovoltaic (PV) and wind turbine (WT) possesses variability due to the impact of natural conditions [11].…”

Section: Introductionmentioning

confidence: 99%

Multi-objective energy management system for DC microgrids based on the maximum membership degree principle

Wang

Meng

et al. 2017

J. Mod. Power Syst. Clean Energy

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With the increasing quantity of DC electrical equipment, DC microgrids have been paid more and more attention. This paper proposes an approach to multi-objective optimisation of an energy management system (EMS) for a DC microgrid that includes a hybrid energy storage system (HESS). The operating and maintenance cost and the loss of power supply probability (LPSP) of the system are used as optimisation targets. The power flows of all distributed generators (DGs) in the DC microgrid during operating period are optimized. Based on the improved differential evolution (DE) algorithm, and by using the multi-objective non-dominated sorting method and the maximum membership degree principle (MMDP) of fuzzy control, the overall satisfaction degree of Pareto solutions to power flow optimization can be obtained. Simulation results verify the effectiveness of the proposed EMS optimization scheme, which is able to achieve an effective trade-off between the economy and the reliability of microgrid operation.

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A Sustainable Energy Management System for Isolated Microgrids

Cited by 96 publications

References 18 publications

A prediction‐based optimization strategy to balance the use of diesel generator and emergency battery in the microgrid

A prediction‐based optimization strategy to balance the use of diesel generator and emergency battery in the microgrid

Optimal energy management of community microgrids: A risk-based multi-criteria approach

Multi-objective energy management system for DC microgrids based on the maximum membership degree principle

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