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This study develops a reduced-order power plant dispatch model and uses it to simulate marginal emissions factors (MEFs) for the 2014−2017 United States (U.S.) electric grid at the North American Electric Reliability Corporation (NERC) regional level. MEFs help quantify the health, environmental, and climate change impacts caused by changes in marginal net electricity consumption, which could result, for example, from new technologies or policies. This study develops the model, validates it against historical data, and compares its simulated MEFs against historically derived regression-based MEFs. Our method accurately reproduces CO 2 , SO 2 , and NO x emissions for multiple U.S. NERC regions and years and enables us to analyze future scenarios that are absent from the historical data. Though historically derived regression-based MEFs are generally more accurate, our simulated MEFs provide a more nuanced picture of how clusters of low-or high-emitting power plants of similar production cost create large swings in MEFs throughout the day. Policymakers could use these dynamic MEFs to target demand-reduction strategies at high-emissions portions of the power plant merit order.

Adding large solar photovoltaic (PV) resources into an electric grid influences the flexibility characteristics of its net load profile. The dispatch of the existing generation fleet changes as it adjusts to accommodate the new net load. This study categorizes and defines these flexibility characteristics. It utilizes a unit commitment and dispatch (UC&D) model to simulate large solar generation assets with different geographic locations and orientations. The simulations show the sensitivity of the wholesale energy price, reserve market prices, total dispatch cost, fuel mix, emissions, and water use to changes in net load flexibility requirements. The results show that generating 22,500 GWh of solar energy in a 2011 simulation of the Electric Reliability Council of Texas (ERCOT) reduces total dispatch cost by approximately $900 Million (a 10.3% decrease) while increasing ancillary services costs by approximately $10 Million (a 3% increase). The results also show that PV reduces water consumption and water withdrawals as well as CO 2 , NO x , and SO x emissions. It also reduces peak load by 4% but increases net load volatility by 40-79% and ramping by 11-33%. In addition, west-located, west-oriented solar resources reduce total dispatch cost more than the other simulated solar scenarios. The west-located, west-oriented solar simulation required greater system flexibility, but utilized more low-cost generators and

The installation of wind and solar capacity in the electric grid can influence net load ramp rates and volatility, affecting grid stability and operating costs. In this study, the statistical analysis of load, wind, and solar data from the Electric Reliability Council of Texas (ERCOT) shows how wind and solar capacity impacts these grid flexibility requirements. Growing wind capacity shows only minor correlation with increasing flexibility requirements, and appears to correlate with decreasing flexibility requirements in some instances. Growing solar capacity might initially improve grid flexibility requirements, particularly volatility. However, beyond a certain penetration level (about 1.0 GW in this study), further solar capacity growth develops a direct correlation with increasing flexibility requirements if load patterns do not change. While adding 15.7 GW of wind power had insignificant effects, adding 14.5 GW of solar to the ERCOT grid increases maximum 1-hr ramp rates by 135%, 3-hr ramp rates by 30%, ramp factors by 140%, 1-hr volatility by 100%, and 1-day volatility by 30%. The geographic location and orientation of solar arrays influences these flexibility requirements, with fixed, southeast-facing panels providing a significant reduction. These results can inform strategies for managing the grid flexibility requirements created by growing renewable capacity.

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