Technical assessment of small-scale wind power for residential use in Mexico: A Bayesian intelligence approach

Borunda, Mónica; Cruz, Javier de la; Garduno-Ramirez, Raul; Nicholson, Ann E.

doi:10.1371/journal.pone.0230122

Cited by 11 publications

(6 citation statements)

References 31 publications

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“…The potential to supply part, most or all required energy with the available wind resource at a given site must be clearly stated, considering that the energy produced by a small-scale wind turbine can be estimated from the turbine power curve and the wind speed distribution at the site [56]. In [57], we introduced a Bayesian decision system based on probabilistic reasoning to assess the suitability of small-scale wind turbines taking into consideration the availability of wind resources at various sites and the energy pricing structure in Mexico.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Long-Term Estimation of Wind Power by Probabilistic Forecast Using Genetic Programming

et al. 2020

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Given the imminent threats of climate change, it is urgent to boost the use of clean energy, being wind energy a potential candidate. Nowadays, deployment of wind turbines has become extremely important and long-term estimation of the produced power entails a challenge to achieve good prediction accuracy for site assessment, economic feasibility analysis, farm dispatch, and system operation. We present a method for long-term wind power forecasting using wind turbine properties, statistics, and genetic programming. First, due to the high degree of intermittency of wind speed, we characterize it with Weibull probability distributions and consider wind speed data of time intervals corresponding to prediction horizons of 30, 25, 20, 15 and 10 days ahead. Second, we perform the prediction of a wind speed distribution with genetic programming using the parameters of the Weibull distribution and other relevant meteorological variables. Third, the estimation of wind power is obtained by integrating the forecasted wind velocity distribution into the wind turbine power curve. To demonstrate the feasibility of the proposed method, we present a case study for a location in Mexico with low wind speeds. Estimation results are promising when compared against real data, as shown by MAE and MAPE forecasting metrics.

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Section: Experiments and Resultsmentioning

confidence: 99%

Long-Term Estimation of Wind Power by Probabilistic Forecast Using Genetic Programming

et al. 2020

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“…Residential, public, and commercial buildings * * * * HAWT Off-grid Rodriguez-Hernandez et al [17] 2019 Mexico Valley of mexico metropolitan -* SSWT On-grid Borunda et al [18] 2020 Mexico Whole country Residential * SSWT -Ibrik [19] 2019 Palestine West Bank Several households * SS-HAWT Off-grid…”

Section: Economic Analysismentioning

confidence: 99%

“…Rodriguez-Hernandez et al [17] evaluated 28 SSWT models at 18 locations in the Valley of Mexico Metropolitan area to estimate annual energy production. Borunda et al [18] studied 5-kW and 10-kW SSWT to supply the residential demand in different Mexican cities with Intelligent Bayesian decision-making. Ibrik [19] analyzed 10, 100, and 220 kW SSWTs at eight sites in West Bank cities.…”

Section: Introductionmentioning

confidence: 99%

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Techno−Economic Analysis and Multi‐Objective Optimization of Cross‐Flow Wind Turbines for Smart Building Energy Systems

2023

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Paris Climate Agreement 2015, have been established to restrict the use of ozonedepleting substances and reduce greenhouse gas (GHG) emissions. [2] Buildings consume about 40% of global energy and are responsible for approximately onethird of the total world's GHG emissions. [3] Previous research shows that proven and commercially available technologies can reduce buildings' energy consumption by 30-80%. [4] One of the concepts that could be much helpful for this is renewablebased smart building energy systems with two-way interaction with the energy grids. [5] Among all renewable energy sources, abundant and affordable wind energy has been used by humankind for centuries, and small scale wind turbines (SSWTs), such as CFWTs, have grown and developed rapidly in the past few years. [6] The most notable features of CFWTs are high starting torque at low wind speed, self-starting capability, and simplicity of installation and structure, which together make them a suitable option for use in the urban environment. [7,8] Many researchers have already studied the techno-economic aspects of renewable-based smart building energy systems in Iran. Fazelpour et al. [9] investigated the feasibility of supplying a household electrical demand on Qeshm Island. After simulating and optimizing several combinations, it was concluded that the wind turbine (WT) and photovoltaic (PV) hybrid system with battery storage is the most cost-effective system, with a cost of energy (COE) of 0.604 $ kWh −1 and a total net present cost (NPC) of 30700 $ (based on 2015 US$). Baneshi and Hadianfard [10] analyzed a WT-PV-diesel-battery system for large nonresidential consumers with an average daily load demand of 9911 kWh in Shiraz. They presented the optimal hybrid system characteristics for off-grid and on-grid with the COE and renewable fraction values. Qolipour et al. [11] ranked six regions in Ardabil province in terms of generated electricity, depreciation values, and total income and net cost for the construction of household WTs with a generator and batteries by a Nonfractional DEA-BSC-Game theory hybrid approach. Mohammadi et al. [12] proposed a 100% renewable energy system for a residential single-family house in Hesarek, Tehran. Their final optimal solution with minimizing the cost function and the reliability constraint consists This work reports a technical, economic, and environmental investigation of the possibility of using a recently developed smallscale crossflow wind turbine (CFWT) to supply the energy demand of buildings for different integration scenarios. For this purpose, three CFWT-assisted building energy system configurations with heat pumps, with and without batteries, and two-way interaction with the local grid in two residential building models in Iran and Germany are investigated. Triobjective optimization with a Nondominated Sorting Genetic Algorithm (NSGA-II) is performed for finding the optimal configuration of the energy system in different configurations. For economic assessment, the Capital Budgeting Analysis meth...

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“…Borunda et al [23] give an example of small-scale wind turbines (SSWT) and their process behind site selection based on a case in Mexico. These are defined in the article as ranging from 5-10 kW in generation capacity and are intended to cover the demand load of residential power usage in Mexico.…”

Section: Literature Reviewmentioning

confidence: 99%

Wind Microgeneration Strategy for Meeting California’s Carbon Neutral Grid Goal

Niswander

Xydis

2022

Applied Sciences

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As California’s Renewables Portfolio Standard continues to phase power production from fossil fuels, carbon neutral sources will need to be implemented. This sets small-scale wind production and battery storage in a position to integrate into current grid infrastructure as means of production. This would be an “E Pluribus Unum” approach where many decentralized small production and storage units would act in combination to provide a stable grid. This is often referred to as distributed generation (DG). By distributing the grid’s production in this manner and designating predetermined regional hubs for control (in the event of a fractured grid due to natural disaster), the state and its residents will be able to maintain power for critical infrastructure and basic utilities. This work presents, in detail, a sustainable plan for achieving carbon neutral Californian grid by 2045.

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Technical assessment of small-scale wind power for residential use in Mexico: A Bayesian intelligence approach

Cited by 11 publications

References 31 publications

Long-Term Estimation of Wind Power by Probabilistic Forecast Using Genetic Programming

Long-Term Estimation of Wind Power by Probabilistic Forecast Using Genetic Programming

Techno−Economic Analysis and Multi‐Objective Optimization of Cross‐Flow Wind Turbines for Smart Building Energy Systems

Wind Microgeneration Strategy for Meeting California’s Carbon Neutral Grid Goal

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