Demand Response: Forecasting reserve margins in the Velocity Suite



Article Written By: Phil Pinson

About the Author: Phil Pinson is currently an MBA student at Babson College located in Wellesley, Massachusetts near Boston. He has over four years of experience as an analyst in the Energy Industry specializing in unit generation, emissions and independent system operator (ISO) energy markets. Babson College uses the Velocity Suite to conduct research and analysis on trends in North American Energy Markets. Secondary research and analysis for this article was conducted by the following MBA Students at Babson College: Rob Ahlering, Sergio Cedeno, Akshat Gupta, Viktor Hlas, Maiko Kamiya and Elena Tarassenko.

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Combining the Velocity Suite’s EV Transmission, EV Energy Map, EV Weather, EV Market Ops, and EV Power products can enable energy market experts to make powerful, informed decisions. Recently a team of MBA Students at Babson College used these Velocity Suite products to forecast changes in power demand and supply to determine energy efficiency opportunities in solutions such as demand response (DR).

More specifically, the team utilized the Velocity Suite to forecast market reserve margins, focusing on the following factors:

• Power plant retirements and additions
• Forecasted growth of energy consumption
• Anticipated transmission constraints
• Renewable Portfolio Standards (RPS)

Solar Additions Affect Reserve Margins:
The following Supply and Demand Analyst chart depicts a long-term forecast (years 2014-2020) of new/existing generating-unit capacity (MW) broken out by status color, for the sub-region of Southern California . The red line depicts Southern California’s expected load (MW), while the blue line depicts Southern California’s forecasted reserve margin (% on secondary axis).

VS1
Source: ABB, Supply & Demand Analyst, Velocity Suite, May 2014

The Supply and Demand Analyst depicts a substantial increase from currently low reserve margins to upwards of 30%, primarily due to California’s ambitious goal of achieving 34% of new capacity from solar power . Furthermore these long-term forecasted reserve margins didn’t take into account the less than 30% capacity factor for solar. Using Velocity Suite, it was determined that adjusted reserve margins to account for solar energy’s low reserve margins actually split Southern California’s reserve margins in half (roughly 14% by year 2020).

Regardless however, the entire state of California’s ambitious renewable portfolio standards – 33% by the year 2020 or adding roughly 3,835MW of capacity (mostly solar) – will have profound impacts on how the California Independent System Operator (CAISO) handles the discrepancy of peak solar generation with the ISO’s peak load. The chart below depicts one week of the entire CAISO region’s hourly load (red bar lines) on the primary axis, with CAISO’s solar generation in MWh (yellow line). The blue and green dotted lines depict likely growth scenarios in years 2015 and 2020 respectively using the Velocity Suite’s Intelligent Chart Tool.

VS2
Source: ABB, Weather Enhanced ISO Total Load Dataset, Velocity Suite, May 2014

While maximum load (MW) and generation (MWh) values change per day (especially on the 4th of July Holiday), the hourly difference between peak timing of hourly load and peak timing of solar generation remains relatively consistent (even on average across an entire year). That is, the sun gives its strongest energy output (i.e. highest solar generation) prior to when peak load occurs. The sharp peak in solar output will put severe constrains on the ISO since load is peaking while solar is sharply decreasing. Plants with higher generation costs are dispatched during these periods putting stress on the grid.

The Important Role of Transmission:
Finally the Intelligent Map in Velocity Suite allows easy analysis to determine where transmission outages occur most frequently. The map below was created to depict where high prices (indicated by the red and orange part of the heat map) occur relative to the transmission line outages (highlighted in pink). These three large transmission lines (especially Path15) were found to cause the majority of $/MWh- Locational Marginal Price (LMP) spikes, upwards to 1,200 $/MWh.

VS3
Source: ABB, Intelligent Map, Velocity Suite, May 2014

Conclusion:
Generalized reserve margin forecast reports are tempting to take for granted. Fortunately the Velocity Suite provides the information and tools necessary to forecast scenarios, specifically drivers of load and capacity variables calculating the reserve margin equation. Consequently, lower than expected reserve margins will lead to more demand response and energy efficiency opportunities. Market regulators will need to reduce the demand side when incidents such as transmission outages from fires, higher than expected load (MW), and intermittent load (i.e. solar) replaces baseline generation (i.e. San Onofre’s recent shutdown of a 2GW nuclear power plant). The Velocity Suite enables users to pinpoint unexpected targets where demand response and other energy efficiency opportunities exist, and allows users to make their own forecasts and compare them with reported ISO data. This capability is particularly enlightening since power is not utilized in the cheapest and most efficient economic way.

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