Optimal Inverter-Based Resource Installation to Minimize Technical Energy Losses in Distribution Systems

Dantas, Felipe B.; Fernandes, Damásio; Neves, Washington L. A.; Branco, Alana K. X. B.; Costa, Flavio B.

doi:10.1109/access.2023.3330083

Cited by 2 publications

References 31 publications

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Water Wave Optimization Algorithm-Based Dynamic Optimal Dispatch Considering a Day-Ahead Load Forecasting in a Microgrid

Huynh,

Ho,

Pham

et al. 2024

IEEE Access

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A novel strategy is proposed to tackle an optimal dispatch of a microgrid in response to dynamic conditions, utilizing a water wave optimization (WWO) algorithm and considering a day-ahead load forecasting. Amongst meta-heuristic algorithms, the WWO algorithm stands out in terms of population size, parameter tuning, exploitation and exploration, convergence speed, as well as optimization mechanism. It leverages its ability to efficiently explore solution spaces and adapt to changing conditions. It is applied to the dynamic optimal dispatch of a microgrid with the uncertainty of load power considered and solved by day-ahead load forecasting. It dynamically adjusts the microgrid operation in response to these inputs, ensuring optimal decision-making in the face of varying load scenarios. With the competition of various dayahead load forecasting techniques in the microgrid, a multi-variate linear regression (MLR) model shows its advantage features, being more transparent, more effective, and more robust than other techniques, especially transparent explainability, as well as simple and fast in model training. These are requirements to achieve the result of day-ahead load forecasting. Thus, the MLR model is proposed to forecast day-ahead load in the microgrid in this paper. The simulation results show that the percentage error (PE) between the MLR modelbased forecasted and actual load powers is always less than 4.42%, the mean absolute percentage error (MAPE) of the forecasting result is 3.33%, and the execution time is 49 (s). These achievements meet the accurate and fast requirements. They are completely competitive with the results of using other techniques such as convolutional neural networks (CNN) and long short-term memory (LSTM), especially in the execution time. This has contributed to improving the efficiency of the dynamic optimal dispatch in the microgrid. Then, the diesel generation, battery energy storage, and total microgrid generation costs are 68.76 ($), 5.09 ($), and 73.85 ($) respectively by using the WWO algorithm which are better than those by using a genetic algorithm (GA), a non-dominated sorting genetic algorithm-II (NSGA-II), a particle swarm optimization (PSO) algorithm, and a transient search optimization (TSO) algorithm in the microgrid. The findings offer valuable insights for microgrid operators, energy planners, and policymakers seeking sustainable and cost-effective solutions for distributed energy resource management.INDEX TERMS Dynamic optimal dispatch, day-ahead load forecasting, microgrid, water wave optimization algorithm

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Water Wave Optimization Algorithm-Based Dynamic Optimal Dispatch Considering a Day-Ahead Load Forecasting in a Microgrid

Huynh,

Ho,

Pham

et al. 2024

IEEE Access

View full text Add to dashboard Cite

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A New Traveling Wave-based Methodology to Optimally Detect Faults in HVDC Systems

de Lima,

Júnior,

Neves

et al. 2024

Preprint

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A new traveling wave (TW) based methodology to optimally detect faults in HVDC transmission lines is proposed in this paper. Basically, an optimal digital filter is defined using techniques that minimize the fault location error. The proposed solution is validated through several short-circuit simulations carried out in a bipolar direct current network, being the fault parameters varied in each simulation, such as type, location and resistance. The performance of the proposed methodology is compared against other traditional methods reported in the literature. From the obtained results, the proposed technique has shown to be more accurate due to an optimization technique being applied to find an optimal solution to detect faults, resulting in a customized traveling wave-based fault detector solution for each considered power grid.

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Optimal Inverter-Based Resource Installation to Minimize Technical Energy Losses in Distribution Systems

Cited by 2 publications

References 31 publications

Water Wave Optimization Algorithm-Based Dynamic Optimal Dispatch Considering a Day-Ahead Load Forecasting in a Microgrid

Water Wave Optimization Algorithm-Based Dynamic Optimal Dispatch Considering a Day-Ahead Load Forecasting in a Microgrid

A New Traveling Wave-based Methodology to Optimally Detect Faults in HVDC Systems

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