Publication Number: 500-04-054
Publication Date: July 2004
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IntroductionWith the adoption of the California Renewable Portfolio Standards (RPS) under Senate Bill 1078, the legislation envisioned annual procurements of new renewable resources through a bid selection process. Proposed renewable generation projects are expected to compete against one another to supply the IOUs with electricity, following a "least-cost, best-fit (LCBF) process. The California Public Utilities Commission (CPUC) was charged with establishing and monitoring the LCBF process. The Energy Commission was tasked with providing input on the technical evaluation of integration costs.
The technical review effort became known as the RPS Integration Cost Study, a multi-phased study to develop, quantify and define procedures needed for routine calculation of the indirect integration costs for eligible renewable generators. In Phase I, a fair, transparent and independent methodology was developed to assess integration costs for existing renewable generators. With review and feedback from industry, the estimates for integration costs were adopted and recommended as initial values to use for upcoming RPS procurement process. Phase II work concentrated on evaluating renewable generator attributes (new technology, location of resource, etc) that can potentially improve and/or change initial Phase I results. The focus was on wind & geothermal resources since these resources are anticipated to achieve the greatest market penetration in the near-term. In the Phase III effort, the recommended methodologies are summarized a formalized process for evaluation of integration costs is documented. This report is the culmination of the Phase III effort and provides detailed recommendations for performing integration cost analyses of various renewable generating resources for the state.
The ultimate purpose of the CEC RPS Integration Cost Study is to develop and define the procedures needed for routine calculation of the indirect integration costs for eligible renewable generators. This report documents findings of the RPS Integration Cost Study and the methodologies for evaluating the integration costs of renewable generators. It is important to note that integration costs as discussed in this report are just a subset of the potential indirect costs. The recommended calculation procedures are suitable for routine application on a continuing basis as part of the resource procurement process. Other indirect costs not addressed include investments in new transmission capacity and cost associated with remarketing electricity already purchased in long term supply contracts.
The third report in the study, this report focuses on developing and defining procedures needed for routine calculation of the indirect integration costs for eligible renewable generators. The Integration team also provides specific recommendations for implementation.
- Create a fair and transparent methodology for
evaluating integration costs, specifically capacity credit, regulation costs
and load following
- Perform analysis using the method on a full-year
generation dataset and multi-year dataset and present results
- Recommend calculation procedures suitable for routine
application on a continuing basis as part of the resource procurement
- Recommend process for conducting routine assessment of
- A fair and transparent methodology for evaluating
integration costs, specifically capacity credit, regulation costs and load
following was created.
- A detailed calculation procedure is provided along with
data handling requirements
- Simplified evaluation methods developed and explored.
Results provided for comparison and review.
- Analysis was performed using the method on a full-year
generation dataset (one-minute and hourly generation data).
- Modified cost adders are provided based on full-year
dataset along with new capacity credit values.
- A process for conducting routine assessment of integration costs is recommended.
Conclusions & Recommendations
A systematic approach is recommended to perform evaluation
of integration costs under Phase III. The following are primary recommendation
- CEC or CPUC should identify dedicated personnel and
resources to perform the functions of the Integration Cost Analyst (ICA) on
a routine basis.
- Mechanisms must be established at the CaISO and IOUs to
provide generation data on a timely basis to the ICA for analysis and to the
CEC/CPUC. Data handling and storage protocols are also needed to ensure
standardization, completeness and data quality
- Integration cost reports should be prepared during the
1st quarter of each calendar year and contain capacity credit, regulation
and load following analysis for each generator type, resource areas and
technology. Trend analysis should provide understanding of impact of
increasing penetration by renewable generators.
CEC or CPUC should periodically engage technical experts and the industry to
document the changes to performance and other attributes of each renewable
technology. Changes should be incorporated in the evaluation of integration
In support of the Renewable Portfolio Standards, the Energy Commission was tasked with providing input on the technical evaluation of integration costs. The technical review effort became known as the RPS Integration Cost Study, a multi-phased study to develop, quantify and define procedures needed for routine calculation of the indirect integration costs for eligible renewable generators. The RPS Integration Cost Study was completed over the course of eighteen months. Under Phase I, the goal was to develop initial methodologies for evaluating the integration costs for existing renewable generation sources in California and compare their characteristics with non-renewable generation sources. Phase II concentrated on evaluating key attributes of renewable generators that might affect integration costs. Attributes such as developing technology, geographic issues and other technical aspects were considered. Phase III formalized the evaluation process and provided recommendations for implementation. The Renewables Portfolio Standards (RPS) Integration Methods Group is led by the California Wind Energy Collaborative (CWEC) and includes staff and researchers from the California Independent System Operator (Cal-ISO), Oak Ridge National Laboratory, National Renewable Energy Laboratory and other technology consultants in consultation with staff from the Energy Commission.
The ultimate goal of the RPS Integration Cost Study is to develop and define a fair, transparent and unbiased methodology to assess integration costs for all renewables. Phase III objectives include:
- Formalizing a process using developed methodologies to
conduct a fair and transparent evaluation of integration costs, specifically
capacity credit, regulation costs and load following.
- Performing analysis using the methods on a full-year
generation dataset and multi-year dataset and present results, includes
evaluation using simplified methods.
- Recommending calculation procedures and data handling
suitable for routine application on a continuing basis as part of the
resource procurement process
- Recommending process for conducting routine assessment of integration costs
The Phase III report represents a culmination of the Phase III activities and provides detailed recommendations for performing integration cost analyses of various renewable generation resources under the RPS requirement. The methodology developed initial estimates of integration costs that are intended for use in the upcoming RPS procurement process. Though there are concerns with adopting these numbers, they represent "acceptable" preliminary figures for use in the bid selection process. The intent is to revisit these results as new data becomes available and incorporated to provide the maximum benefits of integrating renewable technologies.
Table of Contents
1.2. Integration Costs
1.3. Development of Methodologies
1.4. Systematic Evaluation of Integration Costs
2.0 Project Approach
2.1. Data Requirements
2.1.1. One Minute Data
2.1.2. One Hour Data
2.2. Database Management
2.3. Data Quality
3.0 Project Outcomes
3.1. Capacity Credit Analysis
3.1.1. Power Demand
3.1.2. Definition of Capacity Credit
3.1.3. Effective Load Carrying Capability
3.1.4. ELCC Model Revisions and Updated Results
3.1.5. Step-by-Step ELCC Capacity Analysis Methodology
3.1.6. Limitations of the ELCC Method for Steam-Constrained Geothermal
3.1.7. Simplified Capacity Credit Methodologies
3.2. Regulation Analysis
3.2.1. Ancillary Services
3.2.2. Definition of Regulation and Load Following
3.2.3. Regulation Analysis Methodology
3.2.4. Data Requirements
3.2.5. Step-by-Step Regulation Analysis Methodology
3.3. Load Following Analysis
3.3.1. Definition of Load Following
3.3.2. Market Settled Costs
3.3.3. Load Following Analysis Methodology
3.3.4. Step-By-Step Load Following Analysis Methodology
3.4. Incorporating Generator Attributes
3.4.2. Assessing Impacts from Historical Data
3.4.3. Assessing Impacts Using Computational Models
3.4.4. Incorporating Generator Attributes of Specific Renewable Resource Types
3.5. Application of Integration Cost Results
3.5.1. CPUC Rank Ordering Process
3.5.2. Application of Existing Study Results
3.5.3. Application of Future Integration Cost Analysis Results
4.1. Integration Cost Analyst
4.2. Generation Data Reporting
4.3. Integration Cost Reporting
4.4. Technology Attributes
Appendix A: Simplified Capacity Credit Methodologies
Appendix B: Control Performance Standards
Appendix C: Regulation Allocation Methodology
Appendix D: Geothermal Energy Technology Attributes
Appendix E: Wind Energy Technology Attributes
List of Figures
Figure 1.1 How Integration Costs Fit In The Least-Cost, Best-Fit Process.
Figure 1.2 A Schematic Of The Recommended Integration Cost Analysis Process
Figure 1.3 A Schematic Of The Recommended Integration Cost Analysis Data Flow
Figure 1.4 A Schematic Of The Integration Analysis Data Processing Pathway
Figure 3.1 Comparison In Demand Factor For Three Years From 2001 To 2003
Figure 3.2 Comparison In Demand Factor For Three Years From 2001 To 2003
Figure 3.3 California Power Demand For 2001 Through 2003
Figure 3.4 Difference In LOLP With And Without Hydro Resources
Figure 3.5 Decomposition Of Hypothetical Weekday Morning Load
Figure C.1 The relationships among the regulation components (A and B) and the total if A and B are positively correlated (top), negatively correlated (middle), or uncorrelated (bottom).
Figure C.2 The relationship among the regulation impacts of loads A and B and the total (T) when A and B are neither perfectly correlated nor perfectly uncorrelated
Figure C.3 Application of vector-allocation method to the case with more than two loads.
Figure C 4 Example of base-load production from a flash-steam plant.
Figure C 5 Performance history of the Geysers Field in California.
Figure C 6 Performance history of the Coso Field, Inyo County, California (Source: Caithness Energy LLC, used by permission).
Figure C 7 Seasonal variation in output of an air-cooled binary plant.
Figure D 8 Typical daily oscillation in output of an air-cooled binary plant.
Figure E 9 Estimated share of wind energy growth by resource area for both RPS scenarios.
Figure E 10 Power curves for examples of current and past technology.
Figure E 11 Tehachapi air density variation during July and August of 2002.
Figure E 12 Power curves for variable and constant speed rotors.
Figure E 13 Turbine average annual capacity factor as a function of wind speed and rotor diameter.
Figure E 14 Turbine capacity and statewide demand during a summer peak period at the 7 m/s reference site.
Figure E 15 Turbine capacity and statewide demand during a summer non-peak period at the 7 m/s reference site.
Figure E 16 Average capacity factor as a function of demand factor at the 7 m/s reference site.
List of Tables
Table 3.1 Summary Of California Peak Demand Hours for Three Years From 2001 to 2003.
Table 3.2 Revised Capacity Credit For Wind, Solar, And Geothermal Using Actual Hourly Profiles.
Table 3.3 Revised Capacity Credit For Wind, Solar, And Geothermal Using Actual Hourly Profiles Without Hydro Resources.
Table 3.4 Step-By-Step Description Of ELCC Capacity Analysis Methodology.
Table 4.1 Verify Data Consistency
Table 4.2 Estimate Short Term Forecast From Rolling Average Surrogate
Table 4.3 Calculate Regulation Component By Subtracting Short Term Forecast
Table 4.4 Calculate Total System Regulation Less Resource Of Interest
Table 4.5 Calculate Statistical Metrics Of Regulation From Existing Data
Table 4.6 Allocate Regulation Share For Each Generator Type
Table 4.7 Calculate Actual Regulation Share For Each Generator Type
Table 4.8 Calculate Actual Regulation Cost For Each Generator Type
Table 5.1 Calculate Hour Ahead Schedule For Each Resource.
Table 5.2 Calculate The Resource Scheduling Error
Table 6.1 Example Of Geothermal Generator Aggregations By Resource Area And Type.
Table A.1 Step-by-step description of a simplified capacity credit methodology.
Table A.2 Comparison of ELCC (no hydro) and simple model results.
Table A.3 Comparison of ELCC (including hydro) and simple model results.
Table D.1 Output of nominal “25-MW” air-cooled binary plant.
Table D.2 Geothermal resource potential in California.
Table E.1 Specific power of selected wind turbines.
Table E.2 Specific power of model wind turbines.