Evaluation of Alternative Design Considerations for Renewable Portfolio Standards
This research project will employ and advance state of the art power systems modeling to evaluate an updated Renewable Portfolio Standard (RPS) for Michigan. In addition to methodological development, the project will provide an objective analysis on the environmental impacts and costs of RPS designs to better inform stakeholders across the state.
Overview of Problem:
Michigan is one of 29 states with a binding Renewable Portfolio Standard policy in place. Under the Clean, Renewable, and Efficient Energy Act of 2008, Michigan’s load serving entities are responsible for generating 10% of their retail electricity sales from renewable sources by 2015. Through new utility-owned generation, existing generation, and power purchase agreements, it is expected that this target will be met. In 2012, groups advocating for higher targets failed to pass Proposition 3, which would have added a constitutional amendment mandating higher penetrations of renewable energy. The debate over this proposal lacked objective analytical rigor when discussing the costs and benefits of expanding Michigan’s RPS. To better inform future policy debates, the University of Michigan Energy Institute will conduct a comprehensive study to assess the costs and environmental impacts of alternative RPS design.
1. Create baseline system representation: The team will employ a comprehensive unit commitment and economic dispatch model, utilizing the software tool Plexos for Power Systems, by Energy Exemplar, to simulate and optimize generator behavior.
The Eastern Interconnection will be modeled at the zonal level, with a higher degree of resolution employed for Michigan to capture intra-state transmission constraints. Approximately 10,000 generators are represented in the model, with detailed assumptions for costs and operational limits including heat rate (at multiple load points), start costs and fuel use, run time restrictions, ramp rates, variable operating and maintenance costs, forced outage rates, and emissions rates. Transmission constraints will be modeled at the zonal level, with the highest data resolution for Michigan employed. Load assumptions will be on an hourly level. Capacity needs will be met by the addition of the installed cost generation option (likely, natural gas combustion turbines) at a rate that maintains a minimum reserve margin. The model’s time horizon will be twenty years, modeling one representative day per month and extrapolating to full annual results. The costs to customers will be based on a utility revenue requirement model for the two major utilities that represents best publically available information.
2. Determine the least cost path for RPS compliance: The available renewable resources will be estimated, with information including the size of the resource, the diurnal pattern for wind and solar, and the installed and O&M costs. With this information, the revenue requirement for the renewable options will be calculated and the projects with the least cost above market energy rates for Michigan will be selected. The dispatch model will be run iteratively to assess the impact of integration on dispatchable resources, total system cost, and emissions.
3. Test scenarios with alternative RPS design, other environmental regulations: Three RPS targets will be assessed, varying the timing and renewable penetration. In addition, the impact of the Mercury and Air Toxics Standard (MATS) will be varied to illustrate the difference between compliance via control equipment versus retirement of selected generators.
4. Test sensitivity of results to key assumptions: For a selected scenario, the sensitivity of the results will be tested by (1) introducing a carbon tax, (2) high and low natural gas prices, (3) high and low coal prices, (4) high and low load forecasts, and (5) high and low installed costs for renewable generators.
5. Write white paper and academic article: The white paper will be suitable to external distribution to better inform policy makers and key stakeholders about the impact of design alternatives for future RPS targets. Assumptions will be transparent and, whenever possible, utilize publicly available and objective data sources (e.g., EIA, NREL). In addition, it is expected that the methodology will be novel and support an academic paper examining the interplay of environmental policies.
In order to bound the scope of this project and make it suitable for scenario and sensitivity analysis engagement, simplifying assumptions will be employed. Several such assumptions include:
- Imported energy from Canada follows historical patterns.
- Non-generation costs remain constant (in real terms) when used to calculate retail rate impacts.
- Pumped storage hydro charging and discharging patterns are user defined.
- Capacity needs are based on a fixed reserve margin over peak demand.
- Ancillary services representation may be simplified or not explicitly modeled.
- Given the uncertainty around CAIR and CSAPR, emissions allowance prices for NOx and SOx will be based on recent actual data.