Electricity demand planning forecasts should consider climate non-stationarity to maintain reserve margins during heat waves

Daniel Burillo, Mikhail V. Chester, Benjamin Ruddell and Nathan Johnson

Applied Energy, 2017, vol. 206, issue C, 267-277

Abstract: Climate non-stationarity is a challenge for electric power infrastructure reliability; recordbreaking heat waves significantly affect peak demand [1], lower contingency capacities, and expose cities to risk of blackouts due to component failures and security threats. The United States’ electric grid operates safely for a wide range of load, weather, and power quality conditions. Projected increases in ambient air temperatures could, however, create operating conditions that place the grid outside the boundaries of current reliability tolerances. Advancements in long-term forecasting, including projections of rising air temperatures and more severe heat waves, present opportunities to advance risk management methods for long-term infrastructure planning. This is particularly evident in the US Southwest—a relatively hot region expected to experience significant temperature increases affecting electric loads, generation, and delivery systems. Generation capacity is typically built to meet the 90th percentile (T90) hottest peak demand, plus an additional reserve margin of least 15%, but that may not be sufficient to ensure reliable power services if air temperatures are higher than expected. The problem with this T90 planning approach is that it requires a stationary climate to be completely effective. In reality, annual temperature differences can have more than a 15% effect on system performance. Current long-term infrastructure planning and risk management processes are biased climate data choices that can significantly underestimate peak demand, overestimate generation capacity, and result in major power outages during heat waves.

Keywords: Climate non-stationarity; Electric power infrastructure; Peak demand; Risk management; Structural equation modeling (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (10)

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DOI: 10.1016/j.apenergy.2017.08.141

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