By Scott Stallard, Vice President, Black & Veatch and Mike Curley, Manager, GADS Services, North American Electric Reliability Corp.
Since the 1970’s, the World Energy Council Performance of Generating Plant committee (WEC PGP) has collected power plant performance statistics from various countries with the goal of identifying means to collect/disseminate data as well as means for evaluating performance and identifying performance opportunities. This allowed the industry to evaluate reliability impacts associated with major technological segments (for example, technology, fuel, vintage, size and so on). These efforts were instrumental in developing standards for sharing data across disparate systems and operators.
“Performance improvement of existing power plants is the most cost-effective way to increase the energy-producing capabilities of a utility, improve the overall energy efficiency of the industry and produce substantial environmental benefits,” said Dr. Karl Theis, executive managing director of VGB PowerTech e.V., (Germany) and chair of WEC’s Performance of Generating Plant Committee. He said availability is a critical indicator for assessing the overall performance of the power plant in both technical and commercial terms. “Moreover, it is a public demonstration of the service the plant provides to its customers. The importance of reliable service should not be underestimated, especially in the increasingly competitive market environment in which many utilities around the world are operating today.”
During the 1970’s and through the 1980’s, this data was used to evaluate a number of key industry trends and quantify their impacts on overall power supply reliability. For example, WEC studied reliability impacts across industry due to changes in technology such as the addition of flue gas desulphurization (FGD) systems to coal-fired plants. Aggregate data that had been collected and disseminated was able to meet industry needs and expectations.
However, beginning in earnest in the 1990’s, increasing competition and deregulation of the electricity sector began to have significant implications for plant operations and associated metrics—and for the value of historical data collection/analysis techniques. At that point, attention turned to how to better leverage data and analysis to improve individual unit performance. Benchmarking and other similar techniques that focus on comparison of unit performance against that of its peers became critical.
Three important distinctions arose:
- Collecting adequate and complete unit-specific data is increasingly challenging given the competitive nature of the industry
- Data distributions can provide significant insight to measure performance gaps and “opportunity” for improvement
- More work is required to translate technical performance “gaps” into financial terms as well as consider other cost-based performance issues such as efficiency.
To address these issues, over the last six years, WEC PGP embarked on a three-step process to match to “data” and “analysis” capabilities to address these industry needs. This process includes:
- Development and deployment of web-based data collection system that will allow entry of unit-specific performance and equipment parameters
- Focus on expanding use of benchmarking and other analytical tools to demonstrate value of data and its role in improving plant performance
- Development of methodology and tools to evaluate differences in “value” associated with different markets, regulation, and technology; this can be coupled to technical data derived from benchmarking to provide financial perspective.
This article will briefly describe each of the key phases of the WEC effort and its role in leveraging plant data to improve plant and, more broadly, generation sector performance.
Getting the Right Data
For over 30 years, PGP has collected and published power plant availability statistics from various countries as average indices for several groups of units. Starting as early as 1994, PGP began identifying ways to open the data collection process to include unit-by-unit information; since that time it has collected such data, to the degree feasible. As of 2007, the latest version of WEC PGP database has been expanded further to include individual unit design and performance indices. This expansion brings with it the reality that, on a global basis, it will soon be possible not only to consider macro industry trends but identify peer groups and consider distribution of performance indicators across peers.
The database’s design section provides a number of characteristics for filtering the data to allow the investigator to define what constitutes a peer unit for their particular analysis. This would include factors such as technology, age, size, air quality equipment, duty cycle, and so on. By combining performance indices and design characteristics, utility engineers and operators can set realistic goals for their units based on a peer group of units of similar design and operating mode.
In terms of operations data, the PGP database collects unit-by-unit performance hours per megawatthour lost versus performance indices. This allows the PGP database to calculate various performance indices, including:
- Energy Availability Factor (EAF)
- Unit Capability Factor (UCF)
- Unplanned Capability Loss Factor (UCLF)
- Planned Capability Loss Factor (PCLF)
- Load Factor (LF)
- Unplanned Automatic Grid Separations per 7,000 hours of operation (UAGS-7)
- Utilization Factor (UF)
- Unplanned Energy Loss Rate (UELR).
Data Value and Analysis
Benchmarking is a process used to evaluate various aspects of their performance in relation to best practice, as compared to their peers. This allows organizations to develop plans on how to adopt such best practices, usually with the aim of increasing some aspect of performance.
Benchmarking has been recognized across industry as a key tool for assessing what is possible in terms of performance. For decades, generating companies have been comparing their plant’s performance against other plants in order to 1) set realistic goals, 2) identify opportunities for improvement, 3) give advance warning of threats, 4) set appropriate incentives, 5) trade knowledge and experiences with their peers (and sometimes to brag about their successes) and 6) quantify and manage performance risks (an increasingly vital action in an increasingly competitive business environment).
Benchmarking is a powerful management tool because it opens organizations to new methods, ideas and tools to improve bottom-line results. It helps crack through resistance to change by demonstrating how different processes and approaches can realistically yield improved results.
The benchmarking process simultaneously considers the impact design and operational variables have on the reliability of an electric generating unit or group of similar units. The process uses the design characteristics and operational factors of the target unit groups as its starting point. The result is a statistically valid group of units having similar design and operational variables.
While the focus of such analysis historically has been plant reliability, the concepts can readily be extended to address efficiency, emissions and cost objective, presuming adequate data availability.
Industry “best practices” often associate performance with ranking. Hence, it is often useful to measure performance within the context of industry ranking, or often more simply, within the context of “deciles” or “quartiles.”
The average performance for EAF and EFOR for this analysis are 85.8 percent and 8.2 percent, respectively (see Figures 1 and 2). Based on these values, the “improvement” required to elevate performance from average to top quartile or top decile would correspond with the values shown in Table 1 on page 78. (Note that the table results are for U.S. coal-fired generation from 2002 to 2007.)
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This type of analysis is not possible to perform without unit-specific data. Yet confidentiality concerns have continued to make the collection process a challenging. PGP’s new web-based data collection process should ease challenges with data entry and verification; on-site peer group analysis and reporting will soon become a reality, thus, contributors the opportunity to directly benefit from participation.
Continuing the Journey
Today, one must think in strategic and economic rather than purely technical terms. The reality is that mixed regulatory, ownership and market perspectives correspond to mixed goals, objectives and priorities for generation entities. Varying business models, varying risk profiles and different “obligations to serve” complicate the issue even further
While the challenge remains essentially the same—to improve the performance of the existing generating plant—the complexity and dynamics of the market require one to re-evaluate the means for collecting, analyzing and benchmarking performance. Specifically, one must consider how to evaluate performance in the context of multiple objectives—reliability, availability, efficiency, environmental performance and flexibility.
Building on the benchmarking framework discussed above, one can quickly see that to move from average EFOR performer to top-quartile and top-decile would require improvements of 7.7 and 10.4 percent, respectively. This provides concrete means for “defining capital investment and changes in O&M that to reach such targets and to define the costs/risks associated with such aspirations. Yet, economics must play a role—how much is the value—in terms of increased net margin from power sales worth?
To address this issue, in 2007, PGP introduced the initial version of a spreadsheet-based tool to help place technical performance within the context of financial performance. The model provides means for the user to analyze many facilities, even for technologies that the user does not fully understand. It provides a medium for analyzing and presenting a thorough availability and economic comparison for various facilities, technologies, markets and obligations. It serves as an educational tool that facilitates the quick comparison of plants that are difficult to compare side-by-side.
By applying this model, it is possible to better understand implications of revenue gains that would be associated with improvements in EAF or EFOR. For example, let’s consider the impacts of “value” vs. whether or not an average baseload coal plant is operating within a regulated or de-regulated market. While specifics of the market and demand need to be tailored to the actual situation, as modeled, the comparative analysis yields some interesting results.
- A large part of the financial benefits for achieving top decile performance are realized by achieving top quartile performance.
- Deregulated markets will yield potentially higher benefits to generators for incremental improvement.
As the issue of performance becomes increasingly complex, the ability to “measure” and analyze performance is even more challenging. There is no clear “right” way to address this issue; different entities, different facilities, different markets and different obligations will yield different needs. It should not be surprising, therefore, that the ESI is somewhat at a crossroads both in terms of how it measures itself and also what data or information is necessary to support such measures.
The ability to understand magnitude of opportunity associated with improved performance is unquestionably a key challenge for the future, given the critical role of existing plant to both produce needed power as well as support larger environmental performance objectives. The ability to evaluate one power plant’s performance in the context of its peers will be key. The industry’s challenge is to continue to find ways not only to collect and analyze the necessary data but also to provide the framework to extend the analysis across markets, across technology choices and across financial realities.
In terms of the potential impact on the energy sector, the benefits of the global comparison system are numerous and obvious. Information exchange will help improve the performance of power generating plants around the world and provide access to electricity to larger populations thus improving the quality of life for many people.
Authors: Scott Stallard is vice president, Asset Management Services for B&V Energy. He has served on the World Energy Council Performance of Generating Plant committee (PGP) for over 18 years and is chairman of Working Group 1 whose principal goal is to improve the value of international data exchange in the increasingly competitive global power sector by evaluating “commercial availability” issues, indicators and definitions, cost comparisons and benchmarking methodologies.
G. Michael Curley is manager of GADS Services at the North American Electric Reliability Corp. He is chairman of Working Group 2 for the Performance of Generating Plants Committee of the World Energy Council.