Operating Reserve Demand Curve Research Articles

Application of an Operating Reserve Demand Curve in ERCOT in the South Korean Electricity Market to Accommodate High Penetration Levels of Renewable Energy

Application of an Operating Reserve Demand Curve in ERCOT in the South Korean Electricity Market to Accommodate High Penetration Levels of Renewable Energy

Estimating the Operating Reserve Demand Curve for Efficient Adoption of Renewable Sources in Korea

As the proportions of variable renewable sources (VRSs) such as solar and wind energy increase rapidly in the power system, their uncertainties inevitably undermine power supply reliability and increase the amount of operating reserve resources required to manage the system. However, because operating reserves have the characteristics of a public good and their value is related to the social cost of blackouts, it is difficult to determine their market price efficiently, which leads to inefficiencies in procuring operating reserves. This study estimates the operating reserve demand curve (ORDC) of the Korean power system to provide an effective basis for measuring the proper value and quantity of operating reserves needed to meet the reliability standard. A stochastic dynamic optimization model is applied to incorporate the probabilistic characteristics of VRS and the inter-hour constraint, which is necessary for analyzing load-following reserves. An econometric model and the Monte Carlo simulation method are used to generate the forecast profiles of solar and wind generation. The results indicate that the proper amount of hourly operating reserves needed in 2034 is approximately 4.4 times higher than that in 2020 at the current reserve offer price. The ORDC of 2020 has a price-inelastic shape, whereas the ORDC of 2034 has a price-elastic shape because the reserve requirement varies considerably with its offer price level in the high-VRS penetration case. This variability is due to alternatives, such as VRS curtailment or load shedding, which can replace the reserve requirement. This study also showed that VRS curtailment is an effective balancing resource as an alternative to reserves.

Calibration of Operating Reserve Demand Curves Using a System Operation Simulator

The objective of this paper is to analyse the trade-off between the cost of operation and system reliability resulting from different shapes of Operating Reserve Demand Curves under scarcity pricing. We implement a model of the short-term operation of Belgium and we validate it against historical realisations of operation. The model of short-term operation is implemented using 4 embedded optimization problems. The model simulates the trade-off between the lag and cost of mobilizing flexible resources versus the increased reliability that these resources ensure for system operation and allows us to quantity the resulting effect on the level of scarcity pricing adders. We compare eight variants of operating reserve demand curves, and use them as the basis for supporting a recommendation to the Belgian regulatory authority for the implementation of scarcity pricing in Belgium.

Quasi-Stochastic Electricity Markets

With wind and solar becoming major contributors to electricity production in many systems, wholesale market operators have become increasingly aware of the need to address uncertainty when forming prices. Although implementing theoretically ideal stochastic market clearing to address uncertainty may be impossible, the use of operating reserve demand curves allows market designers to inject an element of stochasticity into deterministic market clearing formulations. The construction of these curves, which alter the procurement of reserves and therefore the pricing of both reserves and energy, relies on contentious administrative parameters that lack strong theoretical justification. This paper proposes instead to link their construction to outcomes that would be expected in efficient stochastic markets. The analysis considers the potential of these “quasi-stochastic” market clearing approaches to improve efficiency relative to the deterministic status quo as well as ways in which they are unable to fully replicate the stochastic ideal. Further, the paper argues that efficiently managing uncertainty entails a reexamination of the discriminatory uplift payments and enhanced pricing schemes currently employed to address nonconvexity.

Don't Mess With Texas Solar

2020 was the year of the unexpected, but one constant in the energy industry remained the exponential growth of solar generation in Texas, which largely continued its expansion as predicted. Electric Reliability Council of Texas’s (“ERCOT”) 2019 State of the Grid Report noted that installed solar generation capacity in ERCOT stood at 2,281 megawatts (MW) at year-end 2019, with over 67,000 MW of further solar capacity under study, exceeding even the amount of wind generation capacity under study. By July 2020, installed capacity of solar generation increased by almost 1 gigawatt (GW) to a total of 3,275 MW, representing approximately 2.2% of generating capacity in ERCOT. Solar accounted for 43% of new installed capacity in 2020, the largest share among generation types. The Solar Energy Industries Association (“SEIA”) ranked Texas fifth among the states in installed solar generation capacity in 2019, but based on its high growth rate, Texas is projected to be second only to California within the next five years. Abundant land and consistent sun make Texas an obvious candidate for significant solar generation investment, but ERCOT’s energy-only market makes solar generation with its nonexistent fuel costs especially competitive. Adjustments to the Operating Reserve Demand Curve in 2019 by the Public Utility Commission of Texas have also increased scarcity pricing and made returns more lucrative for a resource that is at its apex when demand is highest on hot, sunny summer afternoons. As this Article was being finalized for publication, the ramifications to the electric power industry in Texas of Winter Storm Uri are not yet clear. However, a preliminary assessment by Pecan Street highlighted the benefits of solar generation in a such a crisis and may spur further interest both at the generation side and behind-the-meter.

A Decentralized Market Framework for Procurement of Operating Reserves From District Energy Systems

District energy system (DES) has become a popular form of supplying comprehensive energy demands in local buildings. For DESs, the operational flexibility can be maintained by energy conversion and storage facilities. Hence, DESs are capable of providing operating reserves to local power systems. This paper addresses the implementation challenges of allowing DES to be deployed alongside conventional generators for providing operating reserves. A two-level hierarchical market framework is proposed which involves a wholesale energy-reserve market for conventional power plants and a subordinate DES operating reserve market. The subordinate operating reserve market determines the quantity and the marginal price of operating reserves provided by DESs. The two markets are linked by the price elastic-quantity provided in the operating reserve demand curve (ORDC) to achieve the stated market coordination. A decentralized decision-making structure is proposed to clear the subordinate operating reserve market considering DES privacy and security requirements. A nested dual-loop solution process is proposed to solve the decentralized optimization problem. A test system is used to illustrate the benefits of the proposed technique in supplying operating reserves through DESs.

Operating reserve demand curve, scarcity pricing and intermittent generation: Lessons from the Texas ERCOT experience

Resolving the resource adequacy problem has been usually entrusted to the imposition of some kind of long-term capacity requirements or to forward markets. The Operating Reserve Demand Curve (ORDC), which is linked to short-term market conditions and does not require central planning, has been presented as an alternative system with which to ensure long-term resource adequacy in the market. Using hourly data from the Texas ERCOT market between January 2015 and February 2019, we empirically show that ORDC prices are significantly negatively affected by wind generation. We find that, if wind generation is relatively low, a 1% increase in wind generation decreases the ORDC price by around 0.15–0.1%. This fact may preclude the ORDC from providing long-term price signals and price stability to generators. Moreover, we also find that if wind generation is greater than 9000 MW, the ORDC price is expected to be zero, which may further disincentive to increase generation capacity –especially dispatchable capacity that may be needed as a backup if the wind is not blowing.

Scarcity pricing and the missing European market for real-time reserve capacity

Scarcity pricing is a valuable step towards the evolution of electricity markets that rely increasingly on reserves for enabling the large-scale penetration of renewable resources. A real-time market for reserve capacity is essential in the implementation of scarcity pricing, in order to enable the back-propagation of the value of reserve capacity to forward markets for energy and reserve. Such a market for real-time reserve capacity does not exist currently in Europe. Consequently, the existing design of the European balancing market creates challenges for the valuation of reserves. We argue that the implementation of a real-time market for reserve capacity can be aligned with European legislation, and we describe how scarcity pricing based on operating reserve demand curves can be integrated in such a design. We discuss the ongoing scarcity pricing debate in Belgium, and highlight various implementation challenges.

Dynamic operating reserve procurement improves scarcity pricing in PJM

Competitive electricity markets can procure reserve generation through a market in which the demand for reserves is administratively established. A downward sloping or stepped administrative demand curve is commonly termed an operating reserve demand curve (ORDC). We propose a dynamic formulation of an ORDC with generator forced outage probabilities conditional on ambient temperature to implement scarcity pricing in a wholesale electricity market. This formulation improves on common existing methods used by wholesale market operators to articulate ORDCs by explicitly accounting for a large source of observed variability in generator forced outages, whereby for a fixed load, more reserves are required during times of extreme heat and cold to maintain a constant risk of reserve shortage. Such a dynamic ORDC increases social welfare by $17.1 million compared to current practice in the PJM Interconnection during a high load week in a welfare-maximizing electricity market with co-optimized procurement of energy and reserves. A dynamic ORDC increases reserve prices under scarcity conditions, but has minimal effects on total market payments. The results are directly relevant to the modeled two-settlement electricity market in PJM, which is currently undergoing enhancements to its ORDC.

Effect of Loss of Load Probability Distribution on Operating Reserve Demand Curve Performance in Energy-Only Electricity Market

In energy-only electricity markets, the operational reserve demand curve is a scarcity pricing mechanism adopted to address the shortage of reserves and incentivize the generators. It is constructed based on the assumption of the normality of loss of load probability, which is estimated from reserve error data. In this Letter, the historical record of reserve error is collected and analyzed to test the assumption and find the fittest probability distribution. It is found that the normal distribution is generally not as good as other distributions like log-logistic, general gamma, and Weibull. Using a dynamic simulation framework, the installed reserve margins with different distributions are evaluated over a fifty-year period, demonstrating that the choice of distribution could significantly impact the subsequent pricing calculations and therefore the reserve margin in an energy-only electricity market. This work is of potential importance and immediate relevance to system reliability and resource adequacy in power systems.

Texas's operating reserve demand curve's generation investment incentive

Faced with reserve margin projections well below the adopted target of 13.75% of the system peak forecast, the Public Utility Commission of Texas on 01/17/2019 ordered the state's grid operator, the Electric Reliability Council of Texas, to “right shift” the operating reserve demand curve (ORDC) to increase generators' revenue from energy sales in ERCOT's real-time market (RTM). Using a large sample of 15-min data for the backcast period of 01/01/2015 through 12/31/2018, we calculate the ORDC shift's impact on RTM prices and investment incentives for natural-gas-fired generation (NGFG). Had the ORDC shift been in effect in the backcast period, the resulting RTM price increases in 2018 could suffice to justify NGFG investment, though not in the prior years of 2015, 2016 and 2017. While the actual ORDC shift occurred on 03/01/2019 had a large impact on RTM prices in the ensuing six-month period of March–August 2019, Texas's planned renewable generation is expected to erode NGFG's operating profit, thus diminishing the ORDC's investment incentive over time. Hence, Texas's energy-only market design will likely need further refinements to solve the missing money problem of inadequate NGFG investment incentive.

‘Missing Money’ and an off-ramp to the capacity debate

As weather-dependent renewables increase, energy revenues in the wholesale market diminish, even as the need for dispatchable resources remains. Such resources are otherwise compensated by forward capacity markets, but those markets are poorly matched to customers’ real needs and the operational realities of a renewable-heavy world. The solution to these issues in market design may be found in an Operating Reserve Demand Curve, intended to pay capacity when and where it is available and needed, as a complement to real-time energy pricing.

Operating Reserve Demand Curve, Scarcity Pricing and Intermittent Generation: Lessons from the Texas ERCOT Experience

Resolving the resource adequacy problem has been usually entrusted to the imposition of some kind of long-term capacity requirements or to forward markets. The Operating Reserve Demand Curve (ORDC), which is linked to short-term market conditions and does not require central planning, has been presented as an alternative system with which to ensure resource adequacy. Using hourly data from the Texas ERCOT market, we empirically show that ORDC prices are significantly negatively affected by wind generation. We find that, if wind generation is relatively low, a 1% increase in wind generation decreases the ORDC price by around 0.2-0.1%. Moreover, if wind generation is greater than 8,000-9,000 MW, the ORDC price is expected to be zero. This may preclude investors from obtaining clearly perceivable long-term price signals, such as capacity requirements intent.

Better Forecasting by ERCOT has Reduced the ORDC LOLP Even As Intermittent Generation Capacity has Increased

The suggestion of multiplying the standard deviation () used in the Electric Reliability Council of Texas’ (ERCOT) Operating Reserve Demand Curve (ORDC) loss of load probability (LOLP) by a factor greater than 1.0 has been posited to solve the “missing money argument.” Historical data from 2015 through 2017 supports this theory, although the calculated factor is only 1.02. This working paper compares the ERCOT 2015 LOLP distributions with the 2018 distributions. 21 of 24 distributions have seen their standard deviation decrease, despite the historical data that shows that the standard deviation of distribution of one hour change in wind generation has increased. Additionally, the change in the mean of the summer time distributions result in a shifting away from the minimum contingency level. These two outcomes both produce a lower LOLP for a given reserve level in 2018 compared to 2015. This is caused by more accurate forecasting by ERCOT. The greater forecasting accuracy overcomes the increase in change of wind generation over an hour resulting in a reduced LOLP. Further evidence suggests that in the windy, low load months, when wind generation makes up a larger percentage of total energy produced, the change in the mean of the distributions does reflect the increase in LOLP caused by intermittent generation. An analysis of the proposal to “shift the mean error by one standard deviation” is performed showing that is identical to increasing MCL by one standard deviation. Variations on this proposal are analyzed. ERCOT 2015 data (linked in references and recorded with Mendeley) is evaluated with the proposal to shift the mean error of the distribution by a standard deviation and the variations, and the increase electricity cost from the proposals ranges from $2.4 billion to $5.75 billion per year. Finally, the foundational problem of using a forecasted error distribution to model a scarcity pricing mechanism instead of a market driven change in price model is briefly discussed.

Modeling of Operating Reserve Demand Curves and System-Level Price Adders in Real-Time Energy-Only Market

In order to support an appropriate level of resource adequacy in the long term and also to achieve a reliable operation in the short term, a new pricing design and mechanism is needed as a key success factor of real-time energy-only market. This paper proposes optimization-based mathematical models to explore operating reserve demand curves (ORDCs) and two price adders in real-time energy-only market, including dispatch correction and extended security-constrained economic dispatch. The Lagrangian multipliers of the dispatch correction problem are used to construct the ORDCs. Then, the derivative of the ORDCs’ social welfare is formulated as real-time online reserve price adders such as the scarcity adder and the price-lift adder. In case studies, we justify the effectiveness of the proposed ORDCs and two price adders by a simple example with two aggregated units and the Electric Reliability Council of Texas data.

Fundamental Problems with ERCOT's Operating Reserve Demand Curve and a Proposed Solution

The methodology employed by the Electric Reliability Council of Texas (ERCOT) in its Operating Reserve Demand Curve (ORDC) as its scarcity pricing mechanism assumes that ERCOT’s distribution of the hour-ahead forecasted reserve level error can be used to accurately model a loss of load probability (LOLP). Because the hour-ahead forecasted reserve level error varies greatly throughout the day and year, ERCOT attempts to compensate by producing six curves a day, four seasons a year for a total of 24 different loss of load probability distributions. By introducing six different curves each day, the ORDC introduces a pricing change that acts identically like a reliability unit commitment (RUC). The ORDC, the scarcity pricing mechanism used by ERCOT, introduces out-of-market actions (pricing RUCs) six times a day. The out-of-market actions are equivalent to 100’s of MWs of RUCs, and with the recent retirement of thousands of MWs of generating capacity, the RUC effects will only be greater. The methodology employed by ERCOT to calculate the LOLP incorrectly applies the hour-ahead forecasted reserve level error distribution to the real-time reserve level. There is no basis in probability theory to apply a forecasted reserve level error distribution to the real-time reserve level. Consequently, the LOLP calculated by the ORDC is incorrect and without a mathematical foundation. Basically, it is a math mistake (explained in the body with empirical proof provided in the appendix). The proposed solution is a simple curve fit of the form f(x)=e^(-(x/σ)^2 ) as a better model of loss of load probability and satisfies the boundary conditions of: as real-time reserve level approaches zero, loss of load probability approaches 1.0 and as real-time reserve level approaches infinity (or very large) loss of load probability approaches zero. Finally, a third boundary condition equating the rate of change of system lambda with the rate of change of LOLP at a given reserve level is introduced. The rate of change of system lambda can be determined empirically by using the historical values of system lambda as reserve level changes. By correlating the rate of change of system lambda at a given reserve level with the slope of the curve fit at that same reserve level (f^' (x)= -2x/σ^2 e^(-(x/σ)^2 )) the rate of change of LOLP will be equal to the rate of change of system lambda. Keywords: Electric Reliability Council of Texas, ERCOT, Operating Reserve Demand Curve, ORDC, loss of load probability, LOLP, forecasted reserve level error, real-time reserve level, out-of-market, reliability unit commitment, RUC, scarcity conditions, finite limits, normal distribution, first principles, boundary conditions.

Why the ERCOT ORDC Splatters on the 2,000 MW Cliff: A Mathematical and Graphical Explanation

The Electric Reliability Council of Texas (ERCOT) operating reserve demand curve (ORDC) is a complex mathematical tool used as the ERCOT market’s scarcity pricing mechanism. For it to be improved, it must first be understood. This work explains why the curve does not produce a loss of load probability equal to 1.0 when reserve level equals zero or the administratively imposed zero at the minimum contingency level (MCL or X).

An Extended Analysis on the Remuneration of Capacity under Scarcity Conditions

This paper extends a recent analysis which investigated the impact of scarcity adders produced by operating reserve demand curves on the financial viability of generation units in the Belgian market. Our paper is inspired by practical considerations related to the implementation of the mechanism in European electricity markets. We are specifically interested in: (i) the extent to which the mechanism rewards flexible resources for being available 'when and where' needed, as required by European competition law; (ii) the sensitivity of the mechanism to certain parameters that require regulatory judgment; (iii) the interaction of the mechanism with indirect capacity mechanisms; and (iv) the ability of the mechanism to provide long-term investment signals. We find that the restoration of nuclear capacity in the Belgian market would suppress scarcity adders to near-zero values. We show that the increase in value of lost load would have a minor impact on scarcity adders when capacity shortages are negligible. We find that the removal of strategic reserve from the Belgian market would have a significant impact on scarcity adders. We find strong positive correlation in consecutive imbalance increments, and show that this correlation can result in noticeable impact on the computation of scarcity adders. We demonstrate that the back-propagation of scarcity adders is essential for providing a long-term investment signal to flexible resources.

Does The Increase in Wind Generation in ERCOT Justify An Arbitrary Increase to its ORDC LOLP Calculation

A suggestion of multiplying the standard deviation () used in the Electric Reliability Council of Texas’ (ERCOT) Operating Reserve Demand Curve (ORDC) loss of load probability (LOLP) by a factor greater than 1.0 has been posited to solve the “missing money argument.” After the fact justification for this position has been given by the rational assumption that the increase in intermittent generation in ERCOT (mostly wind) has increased the LOLP but has not resulted in a corresponding increase in the standard deviation used in the equation. No supporting data has been provided for this rational hypothesis. This paper provides some supporting data of increased intermittency and provides an analysis (with assumptions) of the data to estimate the factor (calculated to be 1.02 to no more than 1.08) to be applied to the standard deviation to account for the increase in intermittent generation in ERCOT. Other less controversial methods of eliminating this perceived shortcoming of the ERCOT LOLP are also discussed.

Remuneration of Flexibility using Operating Reserve Demand Curves: A Case Study of Belgium

ABSTRACT Flexibility is becoming an increasingly important attribute of conventional generators due to the challenges imposed by the unpredictable, highly variable and non-controllable nature of renewable supply. Paradoxically, flexible units are currently being mothballed or retired in Europe due to financial losses. Weinvestigate an energy-only market design, referred to as operating reserve demand curves, that rewards flexibility by adjusting the real-time energy price to a level that reflects the value of capacity under conditions of scarcity. We test the performance of the mechanism by developing a model of the Belgian electricity market, which is validated against the historical outcomes of the market over a study period of 21 months. We verify that (i) based on the observed market outcomes of our study period, none of the existing combined cycle gas turbines of the Belgian market can cover their investment costs, and (ii) the introduction of price adders that reflect the true value of scarce flexible capacity restores economic viability for most combined cycle gas turbines in the Belgian market.