The Australian National Electricity Market (NEM) and the Texas wholesale electricity market (ERCOT) are two of the most prominent examples of energy-only wholesale electricity markets in the world. ...In early 2021 and mid 2022 these markets suffered from unprecedented crises, prompting some commentators to question the energy-only market design. Both markets are now considering implementing a form of capacity mechanism. Are these crises evidence of a fundamental flaw in the energy-only market design, or something else? We argue that, although the crises were very different in form, both crises arose in part from the effect of price caps in the wholesale market. We set out a model of the optimal mix of generation technologies in a framework in which generators can invest to protect against extreme weather events. We show that a price cap (below VoLL) reduces incentives for investment in hardening generation. Rather than further lowering the price caps – as was done in Texas – we propose a range of reforms to strengthen and enhance the confidence in the wholesale market.
•In early 2021 and mid 2022, NEM and ERCOT markets suffered from unprecedented crises.•Are these crises evidence of a fundamental flaw in the energy-only market design?•We argue that both crises arose in part from the effect of price caps.•We propose a range of reforms to enhance the confidence in the wholesale market.
Contrary to liberalized U.S. electricity markets that apply nodal pricing, European power markets rely on uniform pricing within bidding zones. Europe's zonal pricing model is challenged by an ...increasing mismatch between network and generation expansion within bidding zones, as well as the complexity of adequately redefining the existing bidding zone configuration. A potential solution is to transition to nodal pricing. The academic literature provides strong evidence of significant cost savings from such a transition. The question is: Why has nodal pricing persistently been discarded in Europe? It cannot be denied that implementing nodal pricing would require significant changes to the European market design. However, the debate in Europe has mostly focused on perceived flaws of the concept of nodal pricing. In this paper, we identify the main arguments against the concept of nodal pricing brought forward by European stakeholders. We group the arguments into the six categories: susceptibility to market power, barriers to unlock flexibility, market liquidity concerns, increased investment risks, unmanageable complexity, and political undesirability of locational price differentiation. Our contribution is to critically assess each of the arguments. We demonstrate that they do not explain, nor justify, the opposition to nodal pricing.
•We identify six arguments against nodal power markets put forward by European stakeholders.•We analyze these arguments based on interviews, academic literature, and case studies.•Most perceived challenges have been addressed in systems with a nodal market.•We recommend reconsidering a nodal market design and to focus future research on feasible pathways.
This paper proposed a hierarchical structure for the electricity market to facilitate the coordination of energy markets in distribution and transmission networks. The proposed market structure ...enables the integration of microgrids, which provide energy and ancillary services in distribution networks. In the proposed hierarchical structure, microgrids participate in the energy market at the distribution networks settled by the distribution network operator (DNO), and load aggregators (LAs) interact with microgrids and generation companies (GENCOs) to import/export energy to/from the distribution network electricity markets from/to the wholesale electricity market. The proposed approach addressed the synergy of energy markets by introducing dynamic game with complete information for GENCOs, microgrids, and LAs. The proposed hierarchical competition is composed of bi-level optimization problems in which the respective upper-level problems maximize the individual market participants' payoff, and the lower-level problems represent the market settlement accomplished by the DNO or the independent system operator. The bi-level problems are solved by developing sensitivity functions for market participants' payoff with respect to their bidding strategies. A case study is employed to illustrate the effectiveness of the proposed approach.
•The study proposes a scenario-driven method to be used in the QEEM of CMGs on energy markets.•The structure entails developing a stochastic method for controlling fluctuations in return profits ...arising mainly from variations in RER and the resulting variations in transaction costs;•This paper evaluates the impact of cooperative coalitions on the financial performance of the collaborating MGs during the program's lifespan;•Bat optimization algorithm (BOA) is used to solve the optimization problem;•Lastly, an evaluation of sensitivity is used to evaluate how the multi-dimensional risk and return affect the optimum solutions.
A quantitative energy trading model for cooperatively operating several connected microgrids (MGs) in the energy market environments is presented in the paper. The model emphasizes the coordination and management of coalition MGs and utilities to optimize smart grids to maximize their profit returns. Energy transfer plans are the sole control signals that are deployed for achieving optimum control within MGs. Case studies are used to describe uncertainty regarding renewable power production and load demands. Using conditional value-at-risk, the stochastic method reduces the likelihood of aggregators being affected by fluctuations in power prices associated with these uncertainties. Furthermore, the model evaluates the impact of cooperative operations on the performance of the MG portfolio during the lifespan of the scheme. The suggested risk-limited approach is validated by the digital twin and simulating a number of scenarios. According to the study findings, the suggested model limits the profit return variation possibility for MGs at the expense of a slight decrease in predicted profits.
The alignment between electricity market liberalisation and consumer participation is essential to improve market efficiency, increase system flexibility and support the transition to a low-carbon ...electricity system. However, consumer-side market participants, especially large energy consumers, remain passive actors in electricity markets and have little or no market participation strategy. Therefore, this paper aims to examine the alignment status between market liberalisation properties and industrial consumer participation criteria, and investigate the influence of market design and market intervention on consumer-side market participation. A multi-criteria market participation suitability evaluation is proposed for the examination and investigation of two electricity markets, the Nordic region and China. The results show that the more liberalised Nordic electricity market provides good participation incentives for cost savings but fails to address other criteria such as financial security or ease of adoption; the more regulated and less competitive submarkets in the Chinese market provide less opportunities for strategic cost savings but are easier to adopt and give consumers better long-term financial overviews. In general, market context strongly influences the preferred market type for consumer participation. Nonetheless, market intervention is essential to ensure consumer-side market participation, irrespective of the stage of liberalisation. The required amount of market intervention depends amongst others on the type of submarket, and the service it provides to the grid. The developed evaluation method is applicable to different electricity markets and industrial consumer types, and can be used by policymakers for market liberalisation design and by industrial consumers for market participation strategy planning.
•Market parametrisation allows consistent evaluation of different market contexts.•Market liberalisation enables savings but complexifies participation.•Market intervention is necessary even in a liberalised market context.•The amount of market intervention needed depends on the submarket type.•Multi-market participation strategies can meet multi-criteria consumers' needs.
Electricity market time series include several systematic components describing the long-term dynamics, the annual, weekly and daily periodicities, calendar effects, jumps, etc. As a result, ...modelling electricity variables requires the estimation of these components. For this purpose two main approaches have been proposed in the literature: the deterministic and the stochastic. Although an inappropriate modelling of systematic components could have important consequences on the prediction of loads and prices, in the literature it has not yet been assessed, which approach is more appropriate for electricity markets time series.
This work aims at filling this gap by comparing the deterministic and the stochastic approach in a systematic way and in a homogeneous framework, both for loads and prices. In the deterministic case, components are represented by smoothing splines and dummy variables, while in the stochastic case they are described by stochastic processes common to the unobserved component modelling literature. As systematic components are not observable, the comparison is based on the prediction implications of the two procedures. This allows us to account for possible compensations among estimated components on the final result.
Predictive performance is mainly assessed with respect to the one-day-ahead horizon, but also seven-day-ahead predictions are considered. The two approaches are evaluated on loads and prices of four important wholesale electricity markets: the Italian IPEX, the Scandinavian Nord Pool, the British EPEX SPOT UK and North American PJM.
•Unobserved component models vs. regression splines for electricity load and prices•The stochastic approach produces more season-reactive weekly periodic components.•The deterministic approach yields more uncorrelated residuals.•In terms of prediction, both approaches are similar and effective. No clear winner•Removing outliers does not improve predictions.
Integrating intermittent renewable generation with near zero private marginal costs for generating electricity will change market outcomes, but this article emphasizes that this integration does not ...change the fundamental economic principles behind market design. Market designs still need to adequately price scarcity and all network constraints and services. Such pricing is required to deliver investment incentives for the right technologies to locate at the right locations to efficiently maintain a stable and reliable electrical network.
I evaluate the effect of the 2011 Swedish electricity market splitting reform on the allocation of wind power, exploiting a unique data set of all Swedish applications for wind power since 2003. By ...comparing investments in each price zone before and after the reform using a difference-in-differences estimator, I find that 18 percent of all projects constructed by large developers after the reform were allocated to the high price zone due to the reform. This effect is not driven by geographic differences in approval rates, suggesting that the estimated effect also captures investors’ locational choices. Small, sometimes locally owned developers, did not react to the reform. A likely reason is that the locational choice set of small developers usually only includes one of the price zones. A nearest neighbor matching estimator comparing areas with similar prerequisites for wind power, largely confirms the main DiD results.
•I evaluate the effect of a market splitting reform on the allocation of wind power.•The effect is identified using a difference-in-differences estimator.•Large developers reacted to the reform, but small developers did not.•A nearest neighbor matching estimator confirms the main DiD results.
The annual compliance cycle of the carbon trading system gives generation companies (GenCos) the flexibility to buy allowances at preferred times rather than the same time that emissions happen. How ...to estimate the actual emission cost under fluctuating carbon prices and make better generation decisions become challenges for GenCos. A synergistic generation and carbon trading optimization method is proposed in this paper with a non-speculative dynamic (NSD) carbon trading strategy. The NSD strategy utilizes stochastic dynamic programming to make optimal carbon trading decisions and to provide accurate emission cost estimations for GenCos to make generation decisions. To control risks, the NSD strategy forbids intentional speculations in the carbon market but allows both buying and selling of allowances according to the yearly total emissions estimated by the generation strategy. A risk control scheme by adjusting the allowance-emission balancing period is proposed so that GenCos can smoothly shift between the traditional daily-balanced carbon trading strategy and the NSD strategy. Properties of the NSD strategy are analyzed and proved theoretically under some sufficient conditions, which makes the strategy interpretable and trustworthy. Numerical simulations verify that the proposed method can help GenCos lower their emission costs and improve their overall profits in a year.
•The annual compliance cycle of the carbon trading system is considered in the synergistic daily generation and carbon trading decisions of generation companies.•Stochastic dynamic programming is used to optimize daily carbon trading transactions and estimate the actual emission cost in a year.•Risks are controlled by setting the allowance-emission balancing periods.
The impact of electric vehicles (EV) charging strategy will not be limited to power systems as integrated electricity, natural gas and thermal energy systems have become increasingly interconnected. ...We introduce a three-level framework for the aggregated electric vehicle-owning households (AEVH) to strategically participate in local electricity and thermal energy markets as a price-maker, while considering the strategic behavior of the integrated energy service provider (IESP) in the wholesale electricity market (WEM) also as a price-maker. The AEVH operator forms the first level, while IESP and WEM operators are integrated at the second and third levels, respectively. To solve the three-level problem, the second and third levels are modified as a single-level problem through the Karush–Kuhn–Tucker (KKT) conditions, then the equilibrium point of the resulting single-level problem and the first level is achieved through two-step iterative method. At the first level, the arrival/departure time and daily traveled miles of EV fleets are modeled via stochastic scenarios, while renewable energy production at the second level is dealt with by information gap decision theory (IGDT). Ultimately, different case studies verify that AEVHs can deploy their thermal flexibility together with the smart charging strategy of the EVs to influence the local electricity, thermal energy and even WEM prices. Using the proposed three-level optimization framework reaches the best point of equilibrium between different market players. The outcomes prove the effectiveness of the proposed model. Based on the results, the AEVH can deploy the proposed model to diminish the WEM price by 2.1%, while the local electricity price was dropped by 18.85%. Furthermore, the thermal energy price was reduced by 5.82%, which illustrates that EVs can influence the thermal energy market through the combined heat and power units.
•The participation of AEVH in local electricity and thermal energy markets presented.•The strategic behavior of the IESP in WEM as a price-maker is considered.•A three-level framework for the aggregated EV-owning households is proposed.•The second and third levels is modeled as single-level problem through KKT condition.
