Northwest Nigeria (comprising Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto, and Zamfara) faces persistent energy deficits despite abundant renewable energy resources. This study evaluates the technical feasibility of wind power and solar photovoltaic (PV) installations across these seven states using 10 years of meteorological data (2013–2022).
# Feasibility Study of Wind Power and Solar Panel Installation in the Northwest States, Nigeria
**Technical Report** | *Based on Climate Variability Analysis (2013–2022)*
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## 1. Introduction
Northwest Nigeria (comprising Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto, and Zamfara) faces persistent energy deficits despite abundant renewable energy resources. This study evaluates the technical feasibility of wind power and solar photovoltaic (PV) installations across these seven states using 10 years of meteorological data (2013–2022).
The analysis assesses:
- Solar resource potential (using temperature and humidity as proxies)
- Wind energy viability
- Seasonal constraints
- Spatial variability
- Extreme weather events affecting system durability
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## 2. Objectives
- Assess solar PV potential using temperature, humidity, and clear-sky seasonality
- Evaluate wind power feasibility based on wind speed magnitude and consistency
- Identify spatial and seasonal constraints affecting renewable energy generation
- Detect extreme weather events that could impact system durability
- Provide evidence-based siting recommendations for solar and wind installations
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## 3. Dataset Description
The study used monthly meteorological observations (2013–2022) from all seven Northwest states.
| Variable | Unit | Relevance |
|----------|------|-----------|
| Maximum Temperature | °C | Solar PV potential proxy |
| Minimum Temperature | °C | Nighttime/thermal stress indicator |
| Relative Humidity | % | PV efficiency (clear sky indicator) |
| Wind Speed | m/s | Wind power feasibility |
| Rainfall | mm | Soiling, cloud cover, flooding constraints |
**Temporal resolution**: Monthly aggregated data over 10 years
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## 4. Methods
### 4.1 Data Processing
- Cleaned duplicates, blank rows, and formatting inconsistencies
- Converted wide-format Excel data into unified long-format dataset
- Imputed missing values using mean imputation
- Standardized variable types for statist …