Optimisation of energy supply at off-grid healthcare facilities using Monte Carlo simulation

Dufo-López, Rodolfo; Pérez-Cebollada, Eduardo; Bernal-Agustín, José L.; Martínez, Ignacio Martínez

doi:10.1016/j.enconman.2016.01.057

Cited by 58 publications

(28 citation statements)

References 32 publications

(39 reference statements)

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“…As MCS is a repetitive procedure, sample generation process is repeated for some iterations. Finally, histograms, statistic criteria or other approaches are used to analyze the outcome [63]. Caralis et al [64] have used a Monte Carlo method to manage wind power uncertainties with the goal of earning profits from wind energy investment.…”

Section: Mcsmentioning

confidence: 99%

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A Survey on Microgrid Energy Management Considering Flexible Energy Sources

et al. 2019

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Aggregation of distributed generations (DGs) along with energy storage systems (ESSs) and controllable loads near power consumers has led to the concept of microgrids. However, the uncertain nature of renewable energy sources such as wind and photovoltaic generations, market prices and loads has led to difficulties in ensuring power quality and in balancing generation and consumption. To tackle these problems, microgrids should be managed by an energy management system (EMS) that facilitates the minimization of operational costs, emissions and peak loads while satisfying the microgrid technical constraints. Over the past years, microgrids' EMS have been studied from different perspectives and have recently attracted considerable attention of researchers. To this end, in this paper a classification and a survey of EMSs has been carried out from a new point of view. EMSs have been classified into four categories based on the kind of the reserve system being used, including non-renewable, ESS, demand-side management (DSM) and hybrid systems. Moreover, using recent literature, EMSs have been reviewed in terms of uncertainty modeling techniques, objective functions (OFs) and constraints, optimization techniques, and simulation and experimental results presented in the literature.

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Section: Mcsmentioning

confidence: 99%

“…Caralis et al [64] have used a Monte Carlo method to manage wind power uncertainties with the goal of earning profits from wind energy investment. Uncertainties related to solar radiation and load are investigated using MCS in [63] via optimization of the hybrid system.…”

Section: Mcsmentioning

confidence: 99%

A Survey on Microgrid Energy Management Considering Flexible Energy Sources

et al. 2019

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“…12 Simulation results show that a cost and emission reduction of 28% and 54% can be achieved respectively. 12 Simulation results show that a cost and emission reduction of 28% and 54% can be achieved respectively.…”

Section: Introductionmentioning

confidence: 96%

“…A study which incorporates uncertainties of both load and solar irradiation in the optimization of off-grid HRES for a healthcare facility in Congo was presented using Monte Carlo simulation. 12 Simulation results show that a cost and emission reduction of 28% and 54% can be achieved respectively. In another study, the determination of an optimal HRES alternative for a typical RHC in three off-grid villages in Nigeria were carried out.…”

Section: Introductionmentioning

confidence: 96%

Off‐grid hybrid renewable energy system for rural healthcare centers: A case study in Nigeria

Babatunde

Adedoja

Babatunde

et al. 2019

Energy Science & Engineering

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Presented in this study is an optimal hybrid renewable off‐grid energy system model that supplies a typical rural healthcare center across the six regions in Nigeria. A technical and economic evaluation was carried out to identify the optimal off‐grid hybrid energy system combination based on photovoltaic (PV), wind, diesel generator and battery. Due to governments’ fuel subsidy in many developing countries, the pump price of fuel is reduced and not a true reflection of what is obtainable in a deregulated market. In order to comprehensively capture the reality, the study considered the effect of subsidy removal by carrying out a sensitivity analysis on the fuel pump price. Therefore, the impact of a change in diesel fuel pump price and interest rates on the economic performance criteria of the optimal configuration is explored. Results show that across all the locations considered, PV/diesel/battery system is the most economically viable with a net present cost and renewable fraction (RF) ranging between $12 779 and $13 646 and 70%‐80% respectively. The cost of energy (COE) is also estimated to range between 0.507 and 0.542 $/kWh.

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“…It is seen from Table VIII, at the peak load hours(11)(12)(13)(14)(15)(16) which the value of power price exceeds generators cost coefficients, MG sells the surplus power (that generated by high-cost generator) to the upstream network and receives significant revenues, in this interval, r that shows the exchanged power direction with the upstream network is equal 1. Based on the proposed optimal scheduling, the profit of MG is determined as $7721.35 for scenario number 7.…”

mentioning

confidence: 99%

Uncertainty management in decision-making in power system operation

Hemmati

Mohammadi‐Ivatloo

Soroudi

2020

Decision Making Applications in Modern Power Systems

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I. AbstractDue to the penetration of renewable energy resources and load deviation, uncertainty handling is one of the main challenges for the power system. Therefore, the need for accurate decision making in a power system under the penetration of uncertainties is essential. However, decision-makers should use suitable methods for uncertainty management. In this chapter, some of uncertainty modeling methods in power system studies are analyzed. At first, multiple uncertain parameters which the power system deals with them are introduced, then, some useful uncertainty modeling methods are introduced. To show the uncertainty modeling process and its effect on the decision making, a microgrid consisting multiple uncertain parameters is considered, and stochastic scenario-based approach is used for uncertainty modeling. The scheduling of microgrid in presence of different types of uncertainty is solved from the profit maximization point of view. |The simulation results are presented for 33-bus microgrid which shows the effectiveness of the proposed method for decision making under high level of uncertainty.

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Optimisation of energy supply at off-grid healthcare facilities using Monte Carlo simulation

Cited by 58 publications

References 32 publications

A Survey on Microgrid Energy Management Considering Flexible Energy Sources

A Survey on Microgrid Energy Management Considering Flexible Energy Sources

Off‐grid hybrid renewable energy system for rural healthcare centers: A case study in Nigeria

Uncertainty management in decision-making in power system operation

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