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Vehicle to grid (V2G) is one the most important ways to effectively integrate electric vehicles (EVs) with electric power systems. The important benefits can be made by V2G such as reducing/increasing the cost/revenue of EV owners and technically sup-porting electric power systems. Concerning technical and regulatory constraints, EV owners must participate in electricity mar-kets via aggregators. This paper proposes a robust optimal coordinated charging (OCC) model including bidding ancillary ser-vices for regulation and spinning reserve markets. The presented work handles the uncertain behavior of the electricity market that are ancillary service prices and their deployment signals by the robust optimization approach. The aim of optimization is the maximization of the aggregator's profits from V2G by joining the ancillary services markets. The recommended robust OCC model which is a robust linear problem (RLP) model is simulated by the CPLEX solver in GAMS software. An assumed set of 10000 EVs in the electric reliability council of Texas (ERCOT) electricity markets is considered for doing simulations. Employing the presented model in this test system shows the efficacy of the proposed model in comparison to other deterministic and stochastic models. [ABSTRACT FROM AUTHOR]

Electricity demand forecasting plays a vital role in power system planning, operation, transmission design, and financial risk management. In this study, we employ a Gaussian Process model to estimate the probability distributions of short‐term electricity demand. To account for input uncertainty in multi‐period ahead forecast, we adopt an error propagation procedure that improves upon the naive recursive forecasting. This method is shown to perform well in terms of multi‐step ahead point and probabilistic forecasts. We illustrate the usefulness of the suggested estimator with an application to short term demand forecasting of Texas electricity market. [ABSTRACT FROM AUTHOR]

Motivated by the relatively infrequent but very large price spikes in the day-ahead and real-time energy markets operated by the Electric Reliability Council of Texas, this paper proposes an insurance that a small and risk-averse retailer in Texas (i.e., a retail electric provider (REP)) may buy to prevent financial insolvency caused by inadequate risk management. It also demonstrates the insurance's practical design, pricing, and implementation. As participation in the REP's procurement auction is voluntary, the insurance is mutually beneficial for the REP and the insurance seller. Hence, the proposed insurance is a newly developed wholesale market product that deserves consideration by REPs in Texas and competitive retailers elsewhere. [ABSTRACT FROM AUTHOR]

During the 2011 drought, Texas electricity prices rose as generators with water-intensive cooling technologies cut back production. We investigate the effect of exceptional drought on electricity supply and emissions using a fixed-effects model on intra-hourly ERCOT data from 2010 to 2017. We find that the effect of exceptional drought on electricity supply varies with the cooling technology type used by the generator. Generators with water-intensive cooling technologies respond to exceptional drought conditions by raising their average offer prices. However, generators that use dry cooling technologies do not raise offer prices but do increase the total quantity offer during exceptional drought periods. These changes in offer prices lead to lower emissions plants being dispatched during exceptional drought in ERCOT. Given that exceptional drought intensity and duration are forecasted to increase over the coming decades, our findings provide valuable insights for state policymakers seeking to regulate the electricity market in our study area. [ABSTRACT FROM AUTHOR]

In the transition to decarbonized energy systems, Power-to-Gas (PtG) processes have the potential to connect the existing markets for electricity and hydrogen. Specifically, reversible PtG systems can convert electricity to hydrogen at times of ample power supply, yet they can also operate in the reverse direction to deliver electricity during times when power is relatively scarce. Here we develop a model for determining when reversible PtG systems are economically viable. We apply the model to the current market environment in both Germany and Texas and find that the reversibility feature of unitized regenerative fuel cells (solid oxide) makes them already cost-competitive at current hydrogen prices, provided the fluctuations in electricity prices are as pronounced as currently observed in Texas. We further project that, due to their inherent flexibility, reversible PtG systems would remain economically viable at substantially lower hydrogen prices in the future, provided recent technological trends continue over the coming decade. Reversible Power-to-Gas systems can convert electricity to hydrogen at times of ample and inexpensive power supply and operate in reverse to deliver electricity during times when power is relatively scarce. Here, the authors show that such systems can already be economically viable relative to current hydrogen prices in the context of the German and Texas electricity markets. [ABSTRACT FROM AUTHOR]

As renewable energy penetration increases and system inertia levels drop, primary frequency control is becoming a critical concern in relatively small interconnections such as the Electric Reliability Council of Texas (ERCOT). To address this problem ERCOT is implementing a number of market rule changes including the introduction of a new Fast Frequency Response (FFR) reserve type to the electricity market. This FFR reserve type aims to help the traditional Primary Frequency Response (PFR) reserve type in arresting frequency decline in the event of a large generator outage. This paper derives reserve requirements to ensure sufficient reserve to arrest frequency decline before reaching the critical frequency threshold while coupling PFR reserve, FFR reserve, and system inertia. The general reserve requirement places limits on the amount of PFR reserve that can be provided by each unit based on its ramping capabilities. Two such limits are derived from first principles and another is proposed that is capable of accommodating the equivalency ratio introduced in previous work. These PFR reserve limits also provide first principles insight into equivalency ratios, which have only been studied empirically in the past. High-level insights are provided on a large Texas test case. [ABSTRACT FROM AUTHOR]

This discussion with the president and CEO of San Antonio CPS Energy, one of the nation's largest municipal electric and gas utilities, covers the February 2021 Texas winter storm and the failure of ERCOT and the deregulated natural gas and power market during and after the storm. It provides perspectives with regard to utility preparedness for future extreme weather and reviews what investors need to know about climate change impacts on municipal electric utilities in Texas. [ABSTRACT FROM AUTHOR]

Scarcity pricing is a mechanism for improving the valuation of reserve capacity in real-time electricity markets. The goal of scarcity pricing is to mitigate the missing money problem and enhance investment in flexible resources. The implementation of scarcity pricing is underway in a number of U.S. markets, including Texas and PJM. The implementation is also currently under consideration in Belgium. As the mechanism was originally conceived in the context of a U.S.-style two-settlement system, its implementation in a European setting poses a number of interesting market design dilemmas which can affect the back-propagation of scarcity prices to forward day-ahead markets for energy and reserve capacity. We propose a modeling framework for analyzing these market design choices based on stochastic equilibrium, and use this modeling framework in order to represent and analyze a wide range of market design proposals. We report results on a case study of the Belgian electricity market. [ABSTRACT FROM AUTHOR]

Texas electricity market saw a recent integration of electricity transmission as a part of Competitive Renewable Energy Zones (CREZ). Exploiting the commissioning date of CREZ based transmission integration as an exogenous shock, we analyze the effect of transmission expansion on market clearing prices of Congestion Revenue Rights (CRR). Reduced form estimates suggest that excess transmission led to a lowering of CRR prices for contracts at all Times of Use. We find strong evidence of spatial, distributional, and firm specific heterogeneity. The paper shows that transmission expansion enhanced efficiency of the CRR market in terms of a spatial convergence in prices and a decrease in aggregate auction expenditure of approximately $260 million over a period of 4.5 years post CREZ. [ABSTRACT FROM AUTHOR]

Using data from Texas's wholesale electricity market, we investigate the relationship between nodal prices and investment location decisions of utility-scale generation. We find some evidence that new investment arises in areas with recently elevated nodal prices. However, we find no evidence that new generation resources receive a nodal price premium post-entry as projected by the expectation of higher nodal prices. Further, a logit regression analysis suggests that the probability of natural-gas-fired generation investments tends to increase with expected nodal prices in peak hours. However, the estimated relationship is statistically and economically weak and sensitive to model specification. These findings suggest other factors are more important drivers than nodal prices of location decisions for utility-scale generation investments in Texas. [ABSTRACT FROM AUTHOR]

• Siting model that directly incorporates a measure of uncertainty into decisions. • Proven that this model of the wind farm siting problem finds an optimal solution on the Pareto front. • Demonstration of accurate prediction of wind farm power output at a location without historical wind farm power data. Both increasing power output and minimizing the variability of that output are key factors in a highly utilized wind farm. Finding a location that offers this type of wind resource requires the use of stochastic methods to explicitly model the uncertainty of wind power output. While the literature is rich with wind speed resource assessments, this work moves the field to wind farm power assessment at undeveloped locations. A wind farm power prediction is achieved with improved spatial process representation. The power prediction results are utilized directly in a wind farm location siting optimization model which endogenously incorporates uncertainty in wind power output. The overall framework for siting new wind farms, termed the Farm Finder tool, is demonstrated in a case study in the Electric Reliability Council of Texas (ERCOT). It is shown that the formulation of this model will find an optimal solution to the siting problem on the Pareto front of high power output, with high reliability. Such location decisions improve the overall social welfare in the electricity market. [ABSTRACT FROM AUTHOR]

Our study conducts an innovative analysis of the power grid from a network perspective, shedding light on crucial aspects of the wholesale electricity market in Texas. By employing a power system engineering model, we construct a transmission network representation, presenting a novel contribution to the economics literature. Through our analysis of the network matrix, we delve into the characteristics of the Texas power grid, specifically focusing on the structural changes resulting from the Competitive Renewable Energy Zone (CREZ) project and their impacts on nodal prices. The empirical analysis provides additional evidence that ignoring changes in the transmission grid leads to biased estimates of various coefficients. This includes the spatial dependence coefficient, as well as the coefficients associated with control variables such as wind production and load. These empirical findings underscore the significance and distinctive value of network analysis in studying power grids. [ABSTRACT FROM AUTHOR]

The ongoing energy transition, including the rapid electrification of energy services, reinforces the importance of secure and reliable electricity infrastructure. Electricity as a critical energy carrier cuts across sectoral boundaries, including but not limited to public health, national security, education, and transportation. Electricity markets treat electricity as a commodity bought and sold in the different restructured markets of the United States and are a critical feature of power systems shaping the energy transition. However, current electricity market developments primarily rely on techno-economic indicators and fall short of incorporating ethical considerations to spur energy transition towards 100% renewable electricity as end-use energy. Even though electricity markets are designed based on the assumption that they are socially valuable, they essentially go unmeasured based on social and ethical parameters and are largely measured using technical and economic tools and criteria. These inadequacies in the development of electricity markets fail to provide energy and other allied services, particularly during and in the aftermath of a disaster, to the people who need them the most. This paper aims to provide an analytical framework using the foundational approach of energy justice for looking at the electricity market development. The paper utilizes the case of the Texas electricity market and its role in dealing with the electricity crisis in Texas during the winter storm of 2021 from the critical lens of energy justice. The paper shows that using the foundational approach of energy justice, the electricity market can be designed more ethically by considering electricity as means rather than only a market commodity. [ABSTRACT FROM AUTHOR]

In areas of Texas where energy consumers can choose among retail providers of electricity, we find that the prices offered by companies which are involved in both power generation and retail sales ("gentailers") tend to be higher than the prices offered by Retail Electric Providers (REPs) which are independent of any generation company. Yet, within the group of gentailers, we find significant differences in their pricing levels and patterns. These findings are based on graphical and regression analysis of pricing plans advertised on the Power to Choose website. We offer hypotheses that might explain these pricing behaviors. As retail competition in electricity markets is considered or refined in other regions, these findings from Texas may prove instructive. [ABSTRACT FROM AUTHOR]

We analyze the characteristics of the Northeast US's PJM wholesale electricity market production cost and supply curve during the most extreme winter weather event in modern meteorological history within the PJM territory. It is seemingly ironic that the cause of such extremely cold weather events is global warming. The experience from this event demonstrates that the annual-summer-peak-centric nature of the PJM capacity planning process does not address the adequacy of supply during the winter. The PJM production cost curve is estimated and compared across recent winter season peak months to understand how large the price responsiveness to load changes can be during extreme winter weather events and how winter weather events can reduce system reliability for a summer-capacity-planning-centric power market. Therefore, PJM and other power pools (such as ERCOT in Texas) have not considered secondary peak seasons in capacity planning. [ABSTRACT FROM AUTHOR]

[Display omitted] • CO 2 -emission risk caused by wind power uncertainty should be considered. • Ten-year emissions may exceed expected levels by 100 megatons in the two markets. • CO 2 -emission risk comes from annual generation uncertainty and hourly volatility. • Installed capacity required should raise to hedge against the CO 2 -emission risk. • Energy storage and controllable zero-carbon energy help manage the risk. Wind power is a significant source of renewable energy, supporting reductions in emissions. However, the intermittency of wind power will cause uncertain carbon emissions and risks greenhouse-gas emission reduction. To address this issue, we analyzed the mechanism that converts wind-energy intermittency to carbon-emission uncertainty and developed metrics to assess the consequential risks of excessive carbon emissions. According to our empirical analyses on two American electricity markets, the Electric Reliability Council of Texas (ERCOT) and Pennsylvania-New Jersey-Maryland Interconnection (PJM), we found their carbon-emission risk is significant over the coming decade. The ten-year aggregated CO 2 emissions between 2020 and 2030 have a 10% chance of exceeding their expected levels by 100 megatons. Our further analysis also shows that the CO 2 -emission risk is induced by the uncertainty of annual generation uncertainties and volatilities in the hourly wind power supply. Particularly, the two driving forces contribute heterogeneously to the carbon-emission risk in the two studied markets. Although the annual-generation randomness causes similar degrees of carbon-emission uncertainty in the two markets, the volatility-driven risk is only significant in the PJM market. According to the risk analyses, we suggested two types of investigations that are foundations for risk management: assessing the necessary installed capacity of wind energy that limits CO 2 -emission risk at desired confidence levels, and exploring hours when carbon emission is sensitive to wind-power volatility. The former helps set renewable-energy targets, while the latter is critical for designing policies hiring energy storage and zero-carbon generation technologies. [ABSTRACT FROM AUTHOR]

We present an empirical analysis of a supply function equilibrium model in the Texas spot electricity market. We derive conditions for optimal bidding behavior in a spot market with ex ante bilaterally contracted sales. By estimating costs, we are able to derive a set of ex post-and ex ante-optimal supply functions and use a non-parametric behavioral model to compare our theoretically optimal supply functions to actual offers made. Our results show that with the exception of the largest generators, firms make offers with markups and markdowns far in excess of what a model of profit-maximizing behavior suggests. [ABSTRACT FROM AUTHOR]

This paper reviews the procured capacity of operating reserves and its relationship with increasing penetration of wind energy in the top three United States power markets that have most wind generation, including Electric Reliability Council of Texas (ERCOT), Midcontinent Independent System Operator (MISO), and Southwest Power Pool (SPP). Using hourly data for the period of January 1, 2014, to October 31, 2019, we find there was a stable or even declining trend of procured operating reserve quantities among these three markets, while wind energy production collectively grew by more than 80% during the study period. Our study finds that in all three markets the growing wind energy production has not yet significantly increase the magnitude and temporal pattern of net-load ramp, hence potentially rendering a stable or even declining need of operating reserves. The empirical results in this paper support arguments in extant literature that the impact of wind on the operating reserves is more likely related to deviations from normal operation conditions but not for a contingency event. The geographical distribution of wind resources in all three markets could have also helped to reduce the need of additional operating reserves. • Review operating reserves in ERCOT, MISO, and SPP markets in the U.S. • Investigate the relationship between operating reserves and wind generation. • All three markets did not procure more operating reserves to date. • Operating reserves quantity is potentially related to net-load ramp. [ABSTRACT FROM AUTHOR]

In this paper, we document rising market concentration in Texas's retail electricity market. Given recent acquisitions, we question whether a retail market with higher levels of concentration can continue to offer the low prices, an expansive array of creative pricing plans, and new consumer technologies that were promised when the forces of competition were unleashed twenty years ago. [ABSTRACT FROM AUTHOR]

• Test system models centrally-managed wholesale power market and grid operations. • Default settings for Texas energy region can easily be modified for other regions. • Market and grid run for successive days with internally updated system conditions. • User-set parameters permit flexible configuration of market and grid attributes. • Reported 8-bus and 200-bus test cases demonstrate the test system's capabilities. An open source test system is developed that permits the dynamic modeling of centrally-managed wholesale power markets operating over high-voltage transmission grids. In default mode, the test system models basic operations in the Electric Reliability Council of Texas (ERCOT): namely, centrally-managed day-ahead and real-time markets operating over successive days, with congestion handled by locational marginal pricing. These basic operational features characterize all seven U.S. energy regions organized as centrally-managed wholesale power markets. Modeled participants include dispatchable generators, load-serving entities, and non-dispatchable generation such as unfirmed wind and solar power. Users can configure a broad variety of parameters to study basic market and grid features under alternative system conditions. Users can also easily extend the test system's Java/Python software classes to study modified or newly envisioned market and grid features. Finally, the test system is integrated with a high-level simulation framework that permits it to function as a software component within larger systems, such as multi-country systems or integrated transmission and distribution systems. Detailed test cases with 8-bus and 200-bus transmission grids are reported to illustrate these test system capabilities. [ABSTRACT FROM AUTHOR]