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    Monday, March 24, 2014


    PJM Renewable Integration Study

    February 28, 2014 (General Electric International, Inc. for PJM Interconnection, LLC.)

    Executive Summary

    Project Overview

    At the request of its stakeholders, PJM Interconnection, LLC. (PJM) initiated this study to perform a comprehensive impact assessment of increased penetrations of wind and solar generation resources on the operation of the PJM grid. The principal objectives include:

    • Determine, for the PJM balancing area, the operational, planning, and energy market effects of large-scale integration of wind and solar power as well as mitigation/facilitation measures available to PJM

    • Make recommendations for the implementation of such mitigation/facilitation measures This study is motivated by the need for PJM to be prepared for a considerably higher penetration of renewable energy in the next 10 to 15 years. Every jurisdiction within the PJM footprint, except for Kentucky and Tennessee, has a renewable portfolio standard (RPS), or Alternative Energy Portfolio Standard (AEPS), or non-binding Renewable Portfolio Goal (RPG)1.

    This study investigates operational, planning, and energy market effects of large-scale wind/solar integration, and makes recommendations for possible facilitation/mitigation measures. It is not a detailed near-term planning study for any specific issue or mitigation. The target year is 2026, which was used to estimate the PJM annual load profile used in the study scenarios.

    The growth of renewable energy is largely driven by Renewable Portfolio Standards and other legislative policies. The cost-benefit economics of renewable resources, and quantifying the capital investment required to install additional wind and solar infrastructure, were beyond the scope of this study and were not investigated. The study assumed that the penetration of renewable resources would increase and investigated how the PJM system would be affected.

    The impact of renewables on production cost savings was investigated, but the analysis did not include possible secondary impacts to the capacity market such as increased retirements due to non-economic performance or a possible need for generators to recover more in the capacity market because of reduced revenue in the energy market.

    Project Team

    Six companies joined forces to execute the broad range of technical analysis required for this study.

    • GE Energy Consulting – overall project leadership, production cost and capacity value analysis

    • AWS Truepower – development of wind and solar power profile data

    • EnerNex – statistical analysis of wind and solar power, reserve requirement analysis

    • Exeter Associates – review of industry practice/experience with integration of wind/solar resources

    • Intertek Asset Integrity Management (Intertek AIM), formerly APTECH – impacts of increased cycling on thermal plant O&M costs and emissions

    • PowerGEM – transmission expansion analysis, simulation of sub-hourly operations and real-time market performance

    Data Sources

    This study used a combination of publicly available and confidential data to model the Eastern Interconnection, the PJM grid, and its power plants. In order to protect the proprietary interests of PJM stakeholders, the production simulation analysis was primarily based on publically available data, reviewed and vetted by PJM to assure consistency with the operating characteristics of the PJM grid and the power plants under its control. The sub-hourly analysis used PowerGEM’s Portfolio Ownership and Bid Evaluation (PROBE) program, which is regularly used by PJM to monitor the performance of the real-time market2. PROBE uses proprietary power plant data, but that data was not shared with any other study team members per PJMs existing non-disclosure agreement with PowerGEM.

    AWST provided wind and solar power generation profiles and power forecasts within the PJM interconnection region, as well as the rest of the Eastern Interconnection, as inputs to hourly and sub-hourly grid simulations. These data sets were based on high-resolution simulations of the historical climate performed by a mesoscale numerical weather prediction (NWP) model covering the period 2004 to 2006.

    Meteorological data from NREL’s EWITS project3 was used to produce power output profiles for both wind and solar renewable energy generation facilities. A site selection process was completed for onshore and offshore wind as well as for the centralized and distributed solar sites within the PJM region. The selection includes sites that could be developed to meet and exceed renewable portfolio standards for the PJM Interconnection. Power output profiles were produced for each of the sites using performance characteristics from the most current power conversion technologies as of July 2011. The resulting wind and solar power profiles were validated against measurements.

    Study Scenarios

    Table 1 summarizes the PJM wind and solar installed capacity for the ten study scenarios. Note that the scenarios are defined in terms of percentage of renewable energy generation (MWh), whereas Table 1 summarizes the wind and solar capacity (MW) in each scenario. Also, all scenarios include 1.5% of non-wind, non-solar renewable generation.

    2% BAU: This is a Business As Usual (BAU) reference case with the existing level of wind/solar in year 2011. This case is a benchmark for how PJM operations will change as wind and solar penetration increases.

    14% RPS: Wind and solar generation meets existing RPS mandates by 2026, with 14% renewable energy penetration in PJM.

    20% LOBO: 20% wind and solar energy penetration in PJM, Low Offshore and Best Onshore; 10% of wind resources are offshore, 90% of wind resources are onshore in locations with best wind quality.

    20% LODO: 20% wind and solar energy penetration in PJM, Low Offshore and Dispersed Onshore; 10% of wind resources are offshore, 90% of wind resources are onshore. Incremental onshore wind added in proportion to load energy of individual states.

    20% HOBO: 20% wind and solar energy penetration in PJM, High Offshore and Best Onshore; 50% of wind resources are offshore, 50% of wind resources are onshore in locations with best wind quality.

    20% HSBO: 20% wind and solar energy penetration in PJM, High Solar and Best Onshore; similar to 20% LOBO, but with twice the solar energy and proportionately less wind energy.

    The 30% scenarios are similar to the 20% scenarios, but with more wind and solar resources to achieve 30% wind and solar energy penetration in PJM.

    Figure 1 shows the locations of wind plants for the 14% RPS scenario. Note the high concentration of wind plants in Illinois, Indiana and Ohio, which have high quality wind resources. Other study scenarios where onshore wind resources were selected based on a “best sites” criteria also have high concentrations of wind plants in these western PJM states. Scenarios with the “dispersed sites” criteria moved some of the Illinois and Indiana wind resources eastward, to Ohio, Pennsylvania, and West Virginia.

    Most of the scenario technical analysis was performed using wind, solar and load profiles from year 2006. Four scenarios (2% BAU, 14% RPS, 20% LOBO, and 30% LOBO) were analyzed with 2004, 2005, and 2006 renewable and load profiles, in order to quantify differences in performance using different profile years. Although there were some observable differences in operational and economic performance due to differences in wind and solar production across the three profile years, the overall impacts were relatively small and did not affect the study conclusions.

    Study Assumptions

    PJM annual load energy was extrapolated to the study year 2026 using a method to retain critical daily and seasonal load shape characteristics. The average annual load growth for PJM was assumed to be 1.1%4. Load for the rest of the Eastern Interconnection was based on Ventyx “Historical and Forecast Demand by Zone”.

    New thermal generators (about 35 GW of SCGT and 6 GW of CCGT) were added to the PJM system in the 2% BAU scenario to meet the reserve margin requirements in 2026 consistent with the assumed load growth (for a total of about 65 GW of SCGT and 38 GW of CCGT). For consistency across scenarios, the new thermal generators added to meet reserve requirements in the 2% BAU scenario remained available in all higher renewable penetration scenarios. The additions included ISA/FSA qualified plants from the PJM queue, but rest of the additions were not reflective of other future projects in the PJM queue.

    Some existing PJM power plants were assumed to retire by 2026, per retirement forecast data from PJM and Ventyx.

    All operating power plants were assumed to have the necessary control technologies to be compliant with emissions requirements. No emission or carbon costs were assumed in the base scenarios although Carbon costs were considered in one of the sensitivity cases.

    Fuel prices used for production cost simulations are shown in Table 2.

    The wind profiles produced for this study used performance characteristics from the most current power conversion technologies as of July 2011. Therefore, the power output profiles are slightly higher than what has been historically observed in PJM.

    Major Conclusions and Recommendations

    A brief summary of the major conclusions and recommendations are listed here. Further details are presented in subsequent sections of this report.


    The study findings indicate that the PJM system, with adequate transmission expansion and additional regulating reserves, will not have any significant issues operating with up to 30% of its energy provided by wind and solar generation. The amount of additional transmission5 and reserves required are briefly defined later in this summary and in much greater detail in the main body of the report.

    • Although the values varied based on total penetration and the type of renewable generation added, on average, 36% of the delivered renewable energy displaced PJM coal fired generation, 39% displaced PJM gas fired generation, and the rest displaced PJM imports (or increased exports).

    • No insurmountable operating issues were uncovered over the many simulated scenarios of system-wide hourly operation and this was supported by hundreds of hours of sub-hourly operation using actual PJM ramping capability.

    • There was minimal curtailment of the renewable generation and this tended to result from localized congestion rather than broader system constraints.

    • Every scenario examined resulted in lower PJM fuel and variable Operations and Maintenance (O&M) costs as well as lower average Locational Marginal Prices (LMPs). The lower LMPs, when combined with the reduced capacity factors, resulted in lower gross and net revenues for the conventional generation resources. No examination was made to see if this might result in some of the less viable generation advancing their retirement dates.

    • Additional regulation were required to compensate for the increased variability introduced by the renewable generation. The 30% scenarios, which added over 100,000 MW of renewable capacity, required an annual average of only 1,000 to 1,500 MW of additional regulation compared to the roughly 1,200 MW of regulation modeled for load alone. No additional operating (spinning) reserves were required.

    • In addition to the reduced capacity factors on the thermal generation, some of the higher penetration scenarios showed new patterns of usage. High penetrations of solar generation significantly reduced the net loads during the day and resulted in economic operation which required the peaking turbines to run for a few hours prior to sun up and after sun set rather than committing larger intermediate and base load generation to run throughout the day.

    • The renewable generation increased the amount of cycling (start up, shut down and ramping) on the existing fleet of generators, which imply increased variable O&M costs on these units. These increased costs were small relative to the value of the fuel displacement and did not significantly affect the overall economic impact of the renewable generation.

    • While cycling operations will increase a unit’s emissions relative to steady state operations, these increases were small relative to the reductions due to the displacement of the fossil fueled generation.


    Adjustments to Regulation Requirements

    The amount of regulation required by the PJM system is highly dependent upon the amount of wind and solar production at that time. It is recommended that PJM develop a method to determine regulation requirements based on forecasted levels of wind and solar production. Day-ahead and shorter term forecasts could be used for this purpose.

    Renewable Energy Capacity Valuation

    Capacity value of renewable energy has a slightly diminishing return at progressively higher penetration, and the LOLE/ELCC approach provides a rigorous methodology for accurate capacity valuation of renewable energy.

    PJM may want to consider an annual or bi-annual application of methodology in order to calibrate its renewable capacity valuation methodology in order to occasionally adjust the applicable capacity valuation of different classes of renewable energy resources in PJM.

    Mid-Term Commitment & Better Wind and Solar Forecast

    Inherent errors in the day-ahead forecasts for wind and solar production lead to suboptimal commitment of generation resources in real-time operations, especially if simple cycle combustion turbines are the primary resources used to compensate for any generation shortages. Wind and solar forecasts are much more accurate in the four- to five-hour-ahead timeframe than in the current day-ahead commitment process. It is recommended that PJM consider using such a mid-range forecast in real-time operations to update the commitment of intermediate units (such as combined cycle units that could start in a few hours). The wind and solar forecast feature can be added to the current PJM application called Intermediate Term Security Constrained Economic Dispatch (IT SCED)6 which is used to commit CT’s and guides the Real Time SCED (RT SCED) by looking ahead up to two hours. This would result in less reliance on higher cost peaking generation.

    Exploring Improvements to Ramp Rate Performance

    Ramp-rate limits on the existing baseload generation fleet may constrain PJM’s ability to respond to rapid changes in net system load in some operating conditions. It is recommended that PJM explore the reasons for ramping constraints on specific units, determine whether the limitation are technical, contractual, or otherwise, and investigate possible methods for improving ramp rate performance.


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