Analyzing and Auditing Locational Price Calculations in Electricity Markets
Jan 21, 2019
Location-based pricing is adopted in many modern bulk power system electricity markets. That is, the pricing for any given grid power injection or withdrawal is biased by its tendency to relieve or exacerbate network congestion, and sometimes by its increase or decrease in network MW losses. This is an issue in real-time and forward markets, and it reaches into system operational and longer-term planning.
In general, the process involves two central network calculations:
State Estimation utilizes all available real-time and forecast information to produce the statistically most reliable model of the power system operating state. This model, whose accuracy is also critical to system security monitoring and control, is passed on to the following market calculation.
Security-Constrained Optimal Power Flow (SCOPF) uses the above-derived model to determine the locational marginal costs for each network MW injection and withdrawal. There are many different ways of conducting this calculation. The values that it produces can be severely distorted by errors in either or both of the model estimation and SCOPF processes.
The above processes need to be checked periodically for reliability and veracity in order to promote market confidence and to comply with regulatory audit requirements.
During state estimation evaluation, you want your software to help you discover if it is providing a reliably accurate network model. Advanced techniques of statistical analysis for multiple snapshots are used to detect and identify poor metered measurements, forecast measurements, and network parameters. Recommendations for improving, strengthening and maintaining the state estimation process are provided.
In location-based energy pricing, be sure to study how the results are impacted for reliability and accuracy: (a) by imperfections in the model that it uses, (b) by approximations in network model used by the entity’s pricing calculation module, noting that this model is frequently a linearized version of the estimated model, and (c) by the calculation algorithms and software.
The Nexant Grid Management Group’s long experience and in-house software make it ideally equipped to perform such checking studies on behalf of Independent System Operators and Transmission System Operators, and where appropriate for market participants.
Nexant’s assignments in this area have included evaluations and recommendations for ERCOT’s state estimation (see slide 28 in particular), the pricing calculations at Nodal Exchange, and the overall estimation-and-pricing process at COES, the Peruvian National Interconnected-System Operating Authority, whose final report was issued in 2018. The success and timely completion of all these projects has been the combined result of Nexant’s expertise in these fields, the advanced and generalized nature of its commercial software, and the availability of the relevant functions in off-line study forms for easy-to-use analysis.