Microgrids Multiobjective Design Optimization for Critical Loads

Alvarez, Jorge Alejandro May; Zurbriggen, Ignacio Galiano; Paz, Francisco; Ordonez, Martin

doi:10.1109/tsg.2022.3195989

Cited by 13 publications

(3 citation statements)

References 43 publications

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“…These metrics play a vital role in enabling project managers and investors to evaluate the potential profitability and associated risks of a given microgrid project [38], [39]. By quantifying these metrics, stakeholders can make informed decisions regarding investment opportunities.…”

Section: Microgrid Pre-feasibility Toolkit a Planning Methodologymentioning

confidence: 99%

A New Toolkit for Energy Planning for Isolated Microgrids

Polanco,

Esparza,

Singh

et al. 2023

IEEE Access

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Rural areas in various locations are facing electricity shortages and are compelled to heavily rely on non-renewable and ecologically harmful fossil fuels as their primary source of energy. To address this issue, microgrids were proposed as a solution to provide energy to these areas. An IEEE working group, the SESDC Working Group, was established to investigate the feasibility of implementing isolated microgrids as solutions in these communities. However, it has been identified that a proper software tool for microgrid planning is needed to accurately analyze the optimal microgrid configuration. Thus, a user-friendly and secure web-based system for microgrid planning was proposed. This tool was developed using the Django web development framework and Python programming language. It was then validated with users to ensure that the data entered is calculated correctly and produced the expected results.

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Section: Microgrid Pre-feasibility Toolkit a Planning Methodologymentioning

confidence: 99%

A New Toolkit for Energy Planning for Isolated Microgrids

Polanco,

Esparza,

Singh

et al. 2023

IEEE Access

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“…Ref. [23] introduced a new critical load vector microgrid optimization design methodology to find the desired balance between microgrid power availability, net present value cost, and power efficiency. Ref.…”

Section: Introductionmentioning

confidence: 99%

A Modified Particle Swarm Algorithm for the Multi-Objective Optimization of Wind/Photovoltaic/Diesel/Storage Microgrids

Wu,

Shan,

Fan

2024

Sustainability

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Microgrids have been widely used due to their advantages, such as flexibility and cleanliness. This study adopts the hierarchical control method for microgrids containing multiple energy sources, i.e., photovoltaic (PV), wind, diesel, and storage, and carries out multi-objective optimization in the tertiary control, i.e., optimizing the economic cost, environmental cost, and the degree of energy utilization of microgrids. As the traditional multi-objective particle swarm algorithm is prone to local convergence, this study introduces variable inertia weight and learning factors to obtain a modified particle swarm algorithm, which is more advantageous in multi-objective optimization. Compared to the traditional particle swarm algorithm, the modified particle swarm algorithm increased the photovoltaic absorbed rate from 0.7724 to 0.8683 and the wind energy absorbed rate from 0.6064 to 0.7158 in one day, which resulted in an increase in energy utilization by 14.89%, and a reduction in financial environmental costs from RMB 135,870 to RMB 132,230. The simulation of the optimization effect of the conventional particle swarm algorithm and the modified particle swarm algorithm on the microgrid were carried out, respectively, in MATLAB, which verifies the advantage of the modified particle swarm algorithm on the optimization of microgrids. Then, the optimization results, i.e., the data of the power scheduling process of the four power sources, were made into a table and imported into the microgrid model in Simulink. The simulation results indicated that the microgrid was able to output stable voltage, current, and frequency. Finally, the changes in microgrids affected by the external environment were further investigated from the aspects of the market environment and natural environment. Moreover, we verified the presence of a contradiction between the optimization of the microgrid economy and environmental protection. Thus, microgrids need to adjust their optimization focus according to the natural conditions in which they are located.

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“…However, it also addresses the disadvantages of MPC, including high computational cost, sensitivity to model errors, and difficulty in dealing with large-scale systems. Paper [39] focuses on the design of microgrids for powering critical loads. It proposes a new design method called vectorial microgrid optimization (VMO) that integrates the selection of microgrid power conversion architecture and energy source sizing into a unified strategy.…”

Section: Introductionmentioning

confidence: 99%

Lagrange Multiplier-Based Optimization for Hybrid Energy Management System with Renewable Energy Sources and Electric Vehicles

Tran,

Ton-That,

Thao

2023

Electronics

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The issues of energy scarcity and environmental harm have become major priorities for both business and human progress. Hence, it is important and useful to focus on renewable energy research and efficient utilization of distributed energy sources (DERs). A microgrid (MG) is a self-managed system that encompasses these energy resources as well as interconnected consumers. It has the flexibility to function in both isolated and grid-connected configurations. This study aims to design an effective method of power management for a MG in the two operating modes. The proposed optimization model seeks to strike a balance between energy usage, protecting the life of batteries, and maximizing economic benefits for users in the MG, with consideration of the real-time electricity price and constraints of the power grid. Furthermore, in order to accurately account for the dynamic nature of not only the stationary battery banks used as the energy storage systems (ESS) but also the built-in batteries of electric vehicles (EVs), the model is presented as a multi-objective, multiparametric and constrained problem. The solution is proposed to be found using the Lagrange multiplier theory, which helps to achieve good performance with less computational burden. Lastly, simulation results from both the isolated and grid-connected modes also demonstrate the effectiveness of the designed method.

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Microgrids Multiobjective Design Optimization for Critical Loads

Cited by 13 publications

References 43 publications

A New Toolkit for Energy Planning for Isolated Microgrids

A New Toolkit for Energy Planning for Isolated Microgrids

A Modified Particle Swarm Algorithm for the Multi-Objective Optimization of Wind/Photovoltaic/Diesel/Storage Microgrids

Lagrange Multiplier-Based Optimization for Hybrid Energy Management System with Renewable Energy Sources and Electric Vehicles

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