Using a Multi-Functional Inverter to Connect the Distributed Generation Source to the Network with Purpose of Reducing Harmonic and Network Imbalance

Ghiasi, Narges S.; Forouzanfar, Mehdi; Babaei, M.; Sanjareh, Mehrdad Bagheri; Ghiasi, Seyyed Mohammad Sadegh

doi:10.1109/ictem56862.2023.10084004

Cited by 3 publications

(1 citation statement)

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“…Studies on the energy management of MGs can be classified into four categories [74][75][76][77][78][79][80][81][82][83]. These categories encompass various aspects, including types of problem data, both stochastic and deterministic; problem objectives covering both technical and economic goals; the employed devices, such as renewable and non-renewable units, storage, DRPs, and capacitors; and the methods used for solving the problems like metaheuristic and nonmetaheuristic algorithms.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Economic–Resilience Management of Combined Cooling, Heat, and Power-Based Microgrids in a Multi-Objective Approach

Azarinfar,

Khosravi,

Sabzevari

et al. 2024

Sustainability

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The primary goal of a microgrid (MG) operator is to provide electricity to consumers while minimizing costs. For this aim, the operator must engage in the cost-effective management of its resource outputs, which can encompass electrical, thermal, or combined cooling, heat and power (CCHP) systems. Conversely, there has been a growing emphasis on enhancing the resilience of MGs in response to low-probability high-impact (LPHI) incidents in recent years. Therefore, MG-associated energy management strategies have to factor in resilience considerations. While resilience improvement activities increase the operational cost, they lead to a reduction in lost load, and subsequently, a decrease in the MG outage costs, making these activities economically viable. This paper focuses on MGs’ energy management with the primary goals of enhancing resilience, minimizing operational costs, and mitigating active power losses as well as environmental pollution. To attain this goal, various means like renewable resources (specifically photovoltaic (PV) and wind turbine (WT) systems), CCHP, and energy storage devices are integrated. Additionally, for reaching the solution, a genetic algorithm (GA) is implemented. MG operation considers the resilience concept, and according to the obtained results, it is observed that the cost of operation and environmental pollution, respectively, experience an increase about 6.31% and 2.8%. However, due to the reduction in outage costs by an average of 13.91% and power losses by 0.5%, the overall cost is diminished about 5.93%. This cost reduction is achieved through increased CCHP generation and a decreased outage duration during emergencies.

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