Short answer

Before designing or specifying small wind turbines for domestic use in similar island environments, conduct a thorough, long-term wind speed analysis for the specific location and model turbine performance based on that data.

Field: Resource Management
Source: Journal of Wind Energy (2015)
Method: Quantitative analysis and simulation
Sample: 40 years of wind speed data
Evidence: Moderate effect

Analysis of long-term wind speed data in Mauritius indicates that small-scale wind turbines (1-3kW) can be a viable option for domestic electricity generation in specific locations. This resource management research insight is drawn from a 2015 study published in Journal of Wind Energy. Using Quantitative analysis and simulation with 40 years of wind speed data, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Before designing or specifying small wind turbines for domestic use in similar island environments, conduct a thorough, long-term wind speed analysis for the specific location and model turbine performance based on that data.

Study

Resource ManagementHigh ImpactModerate effect

Mauritius wind data suggests 1-3kW turbines viable for domestic power generation

Analysis of long-term wind speed data in Mauritius indicates that small-scale wind turbines (1-3kW) can be a viable option for domestic electricity generation in specific locations.

Journal of Wind Energy · 2015

Key Findings

01Plaisance exhibited higher average wind velocities compared to Vacoas.
02The Weibull distribution effectively characterized the wind speed data for power density estimation.
03Simulations indicated potential energy generation from 1-3kW turbines at both sites, with varying outputs based on location and turbine height.

Application

Design takeaway

How to apply

When evaluating wind energy potential for a design project, gather historical wind data for the specific location, analyze it using statistical methods like the Weibull distribution, and then simulate the expected energy output of candidate turbine models at various heights.

Project actions

01When researching energy sources for a design, look for local data rather than relying on general information.
02Consider how the environment (like wind patterns) affects the performance of your chosen technology.

Method & Evidence

AimTo assess the potential of small-wind turbines for domestic power generation in Plaisance and Vacoas, Mauritius, by analyzing long-term wind speed data and estimating energy output.

MethodQuantitative analysis and simulation

ProcedureCollected approximately 40 years of mean wind speed data for two locations (Plaisance and Vacoas). Correlated wind speed data to a two-parameter Weibull probability distribution to estimate average wind power density. Simulated the energy output of six commercial small-wind turbines (1-3kW capacity) at different heights in both locations.

Sample40 years of wind speed data

ContextRenewable energy assessment for domestic applications in Mauritius.

Variables

IVWind speed, Turbine capacity, Turbine height

DVAverage wind power density, Estimated energy output

CVLocation (Plaisance, Vacoas), Duration of data collection (approx. 40 years), Weibull distribution parameters

Strengths & Limitations

Strengths

+Utilizes a long historical dataset (40 years) for robust analysis.
+Applies a recognized statistical method (Weibull distribution) for wind resource assessment.

Limitations

Collecting 40 years of data is impractical for most design projects; therefore, using publicly available historical data or conducting shorter-term measurements and extrapolating with statistical models is necessary.

Reliability & validity

The use of a long-term dataset and a standard statistical method enhances the reliability and validity of the wind resource assessment. However, the simulation of energy output relies on manufacturer specifications and theoretical models, which may introduce some limitations.

Think critically

How might the findings of this study be generalized to other island nations with similar geographical characteristics, and what additional factors beyond wind speed (e.g., cost, maintenance, grid integration) would need to be considered for a comprehensive feasibility assessment?

Design Principles

"Site-specific resource assessment is fundamental to the successful and efficient deployment of renewable energy technologies."

This research provides crucial data for designers and engineers considering renewable energy solutions for residential applications in island nations or similar geographical contexts. It highlights the importance of localized wind resource assessment for effective technology selection and deployment.

What This Means for Your Design

This study looked at wind data over many years in two places in Mauritius to see if small wind turbines could power homes. It found that one place had better wind, and that small turbines could work there.

How to use in your project

1.Use this study to justify the need for site-specific data collection when proposing a renewable energy system for a design project.

Add to My Project

Quick Cite

Paragraph starter

This research highlights the importance of localized wind resource assessment for the effective deployment of small wind turbines. By analyzing long-term wind speed data and applying statistical models like the Weibull distribution, the study demonstrated the potential viability of 1-3kW turbines for domestic power generation in specific Mauritian locations, emphasizing that site-specific conditions significantly influence energy output.

Source

Journal of Wind Energy

Long-Term Wind Characteristics at Selected Locations in Mauritius for Power Generation

journal · 2015

View source

Questions About This Research

What does the research say about mauritius wind data suggests 1-3kw turbines viable for domestic power generation?: Before designing or specifying small wind turbines for domestic use in similar island environments, conduct a thorough, long-term wind speed analysis for the specific location and model turbine performance based on that data. Evidence: Journal of Wind Energy (2015).
Why does "Mauritius wind data suggests 1-3kW turbines viable for domestic power generation" matter for design?: This research provides crucial data for designers and engineers considering renewable energy solutions for residential applications in island nations or similar geographical contexts. It highlights the importance of localized wind resource assessment for effective technology selection and deployment.
How can designers apply this research?: Before designing or specifying small wind turbines for domestic use in similar island environments, conduct a thorough, long-term wind speed analysis for the specific location and model turbine performance based on that data.
What were the main findings?: Plaisance exhibited higher average wind velocities compared to Vacoas.. The Weibull distribution effectively characterized the wind speed data for power density estimation.. Simulations indicated potential energy generation from 1-3kW turbines at both sites, with varying outputs based on location and turbine height.
What research method was used?: Quantitative analysis and simulation with 40 years of wind speed data.
How strong is the evidence?: Evidence strength is rated Moderate effect, based on a 2015 journal from Journal of Wind Energy.
What should I do differently in my next project?: When evaluating wind energy potential for a design project, gather historical wind data for the specific location, analyze it using statistical methods like the Weibull distribution, and then simulate the expected energy output of candidate turbine models at various heights.
What are the limitations?: The study focused on only two locations and did not account for micro-siting factors like local obstructions or turbulence. The simulation of energy output is based on theoretical models and may not perfectly reflect real-world performance.