Optimal Energy Management and Techno-economic Analysis in Microgrid with Hybrid Renewable Energy Sources

Murty, V. V. S. N.; Kumar, Ashwani

doi:10.35833/mpce.2020.000273

Cited by 120 publications

(21 citation statements)

References 33 publications

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“…Y el COE. El precio del combustible puede variar por disposiciones políticas o dinámicas de oferta y demanda a nivel mundial; tal como mencionan Murty y Kumar [49] y Masrur et al [50], un mayor valor del combustible incrementa el costo de operación del grupo electrógeno y, por Página 6 | 28 ende, del CPN y el COE. y las variables económicas (tasa de descuento y tasa de inflación) pueden influir en los flujos de caja del proyecto [46], [51]; tal como exponen Son et al [52] el incremento de la tasa de inflación aumenta el COE, mientras Chaurasia et al [53] indican que el incremento de la tasa de inflación aumenta el CPN.…”

Section: Página 5 | 28unclassified

“…El precio del combustible afecta el dimensionamiento y los costos de una MR, ya que su variación ocasiona que pueda decidir si usar el grupo electrógeno un mayor o menor tiempo. Ello está en consonancia con lo indicado por Murty y Kumar [49] y Masrur et al [50], quienes señalan que un mayor valor del combustible incrementa tanto el costo de operación del grupo electrógeno como los indicadores CPN y COE.…”

Section: Análisis Del Precio Del Combustibleunclassified

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Dimensionamiento y análisis de sensibilidad de una microrred aislada usando HOMER Pro

García-García¹,

Osma-Pinto²

2023

TecnoL.

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En años recientes, ha incrementado la implementación y el estudio de microrredes (MR). Su dimensionamiento depende de los datos de entrada (ej., demanda, microclima, costos y restricciones), por lo que la variación de uno o más de estos pueden modificar la solución óptima de la MR y su operación esperada. Tal variación se presenta debido al contexto económico, tecnológico o climático, por lo que, se propuso hacer un análisis de sensibilidad que caracterice su impacto. Con el fin de aportar en la aplicación del análisis de sensibilidad en proyectos de MR, el objetivo de este trabajo consistió en estudiar el impacto de siete variables de sensibilidad (irradiación solar, velocidad del viento, temperatura ambiente, estado de carga mínimo del banco de baterías, precio del combustible, tasa de descuento y tasa de inflación) sobre el dimensionamiento e indicadores económicos y operativos de una MR aislada para usuarios residenciales en un municipio rural de Colombia. El análisis se realizó a partir del uso de la herramienta HOMER Pro, siendo los principales indicadores analizados: costo presente neto, costo de energía, costo de capital, costo de operación y fracción renovable. Los resultados permitieron identificar que las variables más influyentes para el caso de estudio son: precio del combustible, tasa de inflación, tasa de descuento e irradiación solar; asimismo, apreció la utilidad de HOMER Pro para este tipo de análisis y la conveniencia de la representación gráfica para estudiar el impacto de las variables de sensibilidad. En conclusión, la variación de los datos de entrada influye en la factibilidad de resultados, como por ejemplo, el costo presente neto disminuye con el aumento del precio del combustible, la temperatura ambiente o la tasa de inflación, mientras que aumenta con la reducción del estado de carga mínimo, la irradiación solar o la tasa de descuento.

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Section: Página 5 | 28unclassified

Section: Análisis Del Precio Del Combustibleunclassified

Dimensionamiento y análisis de sensibilidad de una microrred aislada usando HOMER Pro

García-García¹,

Osma-Pinto²

2023

TecnoL.

View full text Add to dashboard Cite

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“…This metric aims to achieve a balanced voltage profile through the microgrid. The cost of fixing WTGs, denoted by WTG cost , is given in Equation ( 3), in which N is the whole number of buses and WTG size is in kW [38].…”

Section: Problem Formulationmentioning

confidence: 99%

“…The wind gusts together with the day-ahead variation around the normal load is shown in Figure 3(b). Due to the random nature of wind energy [38] and load variations, the attractive feature of integrating WTG within microgrids, such as at 8 p.m. when the load peaks, might be reinforced by the wind gusts variation to meet load demands. The top competitive optimizers are decided based on their behaviour at the normal load stage investigations.…”

Section: Day-ahead Load Investigationmentioning

confidence: 99%

Dual‐stage day‐ahead optimized performance of renewable‐based microgrids

Helmi

Abo‐Elyousr

Alhelou

et al. 2023

IET Renewable Power Gen

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In distributed networks, wind turbine generators (WTGs) are to be optimally sized and positioned for cost‐effective and efficient network service. Various meta‐heuristic algorithms have been proposed to allocate WTGs within microgrids. However, the ability of these optimizers might not be guaranteed with uncertainty loads and wind generations. This paper presents novel meta‐heuristic optimizers to mitigate extreme voltage drops and the total costs associated with WTGs allocation within microgrids. Arithmetic optimization algorithm (AOA), coronavirus herd immunity optimizer, and chimp optimization algorithm (ChOA) are proposed to manipulate these aspects. The trialed optimizers are developed and analyzed via Matlab, and fair comparison with the grey wolf optimization, particle swarm optimization, and the mature genetic algorithm are introduced. Numerical results for a large‐scale 295‐bus system (composed of IEEE 141‐bus, IEEE 85‐bus, IEEE 69‐bus subsystems) results illustrate the AOA and the ChOA outperform the other optimizers in terms of satisfying the objective functions, convergence, and execution time. The voltage profile is substantially improved at all buses with the penetration of the WTG with satisfactory power losses through the transmission lines. Day‐ahead is considered generic and efficient in terms of total costs. The AOA records costs of 16.575M$/year with a reduction of 31% compared to particle swarm optimization.

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“…The escalation of world energy demand and the need for environmentally sustainable development have attracted human attention to renewable energy sources [5]. Among the renewable energy sources, solar power has become increasingly prevalent as a utility-scale renewable energy supply due to its simplicity of installation and maintenance.…”

Section: Introductionmentioning

confidence: 99%

Day-Ahead Power Loss Minimization Based on Solar Irradiation Forecasting of Extreme Learning Machine

Rehiara¹,

Setiawidayat²,

Sumbung³

2023

Adv. sci. technol. eng. syst. j.

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Power losses exist naturally and have to be cared for in the operation of electrical power systems. Many researchers have worked on various methods and approaches to reduce losses by incorporating distributed generators (DG), particularly from renewable sources. These studies are based on the maximum unit penetration of the DGs, which is rarely achieved, resulting in inaccurate calculations. This paper proposes an advanced solution for calculating power losses by incorporating an Extreme Learning Machine (ELM) method for forecasting the solar irradiation. The ELM algorithm was used to create a model for forecasting solar radiation in the Manokwari region and its surroundings. Daily solar radiation in the region has been predicted using the model. NASA's 8016 data on temperature and solar irradiation were used to train the ELM model. With an MAE value of around 0.6392 and a training time of 4.4375 seconds, the test results demonstrate that the built model has good accuracy. The operation of a 1000 kWp solar power plant based on the ELM data forecasting can reduce the power loss of the existing distribution network around the location from 1.5095 kW/hour to 0.9068 kW/hour. Furthermore, the power plant operation can minimize the power loss by 39.9249 percent, from 36.2280 kW to 21.7640 kW.

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Optimal Energy Management and Techno-economic Analysis in Microgrid with Hybrid Renewable Energy Sources

Cited by 120 publications

References 33 publications

Dimensionamiento y análisis de sensibilidad de una microrred aislada usando HOMER Pro

Dimensionamiento y análisis de sensibilidad de una microrred aislada usando HOMER Pro

Dual‐stage day‐ahead optimized performance of renewable‐based microgrids

Day-Ahead Power Loss Minimization Based on Solar Irradiation Forecasting of Extreme Learning Machine

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