Electricity Pricing in Texas (2019–2021): Seasonal Trends, Weather Impacts & Strategy

• Role: Data preparation (Tableau Prep), dashboarding (Tableau), analysis, and recommendations.
• Data: ERCOT settlement point prices, load/generation, and weather (2019–2021).

Overview

This study explores how weather, load, and generation shape Texas electricity price swings, with a focus on seasonal patterns and regional differences. Visual analysis in Tableau highlights strong hourly/seasonal volatility and ties summer heat and winter extremes to sharp price spikes. The most volatile regions are LZ_WEST and LZ_SOUTH.

Business Questions

1. How do settlement point prices vary by region and season?
2. Which fuel types contribute most to generation, and how is that changing?
3. How do weather factors relate to prices and generation over time?
4. Which months show the largest shortages, and how do those align with price changes? (Answered via Graphs 1–7 in the dashboard/story.)

Preparation & Approach

1. Cleaned and deduplicated data, then joined and pivoted large volumes from 2019–2021 in Tableau Prep.
2. Built a calculated field to efficiently remove weather nulls across variables.
3. Grouped weather variables by region (not city) to match business questions, and used pivots where needed.

Key Findings

• Seasonality & Regional Volatility. Prices show clear summer peaks and winter-event spikes, with LZ_WEST/LZ_SOUTH the most volatile. Effects intensify during peak (afternoon) hours.
• Weather ↔ Price Link. High temperatures correlate strongly and positively with settlement prices, especially in LZ_NORTH and LZ_WEST—and more so during peak hours.
• Generation Mix. Coal, wind, and gas-fired sources account for >80% of total generation; heavy reliance during extreme weather contributes to price spikes and generation shortages.
• Shortages by Month. The largest deficits occur in March and August, underscoring supply–demand imbalances during transitional and peak-demand periods.
• Seasonal Generation Dynamics. Generation rises sharply June–August and falls in winter; the summer peak (July–August) aligns with heat-driven demand.

Recommendations

Expand renewables in high-potential regions to blunt summer/winter peaks and reduce exposure to shortages. Evidence: fuel-mix trends, summer/winter price spikes, and shortage months.

Implement weather-aware dynamic pricing and demand response so retail/industrial users shift away from peak hours during extreme weather.

Continue building regional weather+price views to anticipate cross-regional transfers and plan generation ahead of forecasted shortfalls.

Visual Analytics (Dashboard Highlights)

1. Monthly/region price trend (seasonality + geography).

2. Top contributors to electricity generation (fuel mix).

3. Weather → price correlation by region.

4. Weather → generation over time.

What I Did

• Shaped the data and removed nulls efficiently;
• regionalized the weather variables;
• built interactive parameters (choose weather metric, select fuel, Top-N) to tailor insights for different audiences.

What I Learned / Next Steps

Seasonal/weather drivers explain much of ERCOT price volatility; aligning analysis to region & peak-hour granularity matters.

Next: deepen load forecasting and regional transfer planning, and validate dynamic pricing scenarios using forward weather forecasts.