Current Market Design Research Articles

A Linked Swing Contract Market Design With High Renewable Penetration and Battery Firming

As renewable generation and energy storage systems become increasingly cost-effective, modern power systems are increasingly reliant on variable energy resources (VERs) to meet demand. However, the variability and uncertainty of VERs' generation require additional flexibility to mitigate their impacts. Unfortunately, the current power market designs rigidly define different power and reserve products, making it difficult to fully recognize and compensate for this flexibility. Furthermore, since the marginal operating costs of the system quickly approach zero, current marginal cost-based market mechanisms struggle to provide price signals that allow independent power producers to make informed decisions about constructing, operating, and retiring plants. To address these issues, this paper proposes a new linked electricity market design based on swing contracts for operating power systems with high penetration of VERs and energy storage resources. The feasibility of the proposed approach is demonstrated through study results on the modified IEEE 118-bus test system.

Consumer-centric electricity markets: Six design principles

Key to the necessary decarbonization of energy systems is the large-scale expansion of renewable energy sources and their integration into the electricity system. This integration is challenging because the feed-in from renewable energy sources is highly intermittent and largely dependent on uncontrollable factors such as weather patterns. To maintain grid stability, which refers to the required balance between demand and supply in the electricity system, flexibility is key. Large flexibility potentials can be found on the electricity demand side. However, current electricity market design in Europe, while providing major flexibility incentives, often neglects small-scale electricity consumers and distributed energy resources. We contribute to shape future electricity markets with consumers at the heart by developing six design principles for a consumer-centric electricity market design. We proceed by conducting a systematic literature review and evaluate the findings by expert interviews. Based on the developed design principles, we define a consumer-centric electricity market design as a set of market rules that align with the rules of other relevant energy markets and allow for the efficient matching of electricity demand and supply, with consumers having nondiscriminatory market access, being exposed to fine-grained price signals, being able to express their preferences, and having sufficient possibilities to protect themselves against unexpected price spikes. By actively incorporating consumers into electricity markets, we contribute to the overarching goal of integrating renewable energy sources while promoting energy justice, i.e., supporting a balanced mix of economic, political, environmental, and social interests.

Optimal Electricity Imbalance Pricing for the Emerging Penetration of Renewable and Low-Cost Generators

Problem definition: With the rise of renewables and the decline of fossil fuels, electricity markets are shifting toward a capacity mix in which low-cost generators (LCGs) are dominant. Within this transition, policymakers have been considering whether current market designs are still fundamentally fit for purpose. This research analyses a key aspect: the design of real-time imbalance pricing mechanisms. Currently, markets mostly use either single pricing or dual pricing as their imbalance pricing mechanisms. Single-pricing mechanisms apply identical prices for buying and selling, whereas dual-pricing mechanisms use different prices. The recent harmonization initiative in Europe sets single pricing as the default and dual pricing as the exception. This leaves open the question of when dual pricing is advantageous. We compare the economic efficiency of two dual-pricing mechanisms in current practice with that of a single-pricing design and identify conditions under which dual pricing can be beneficial. We also prove the existence of an optimal pricing mechanism. Methodology/results: We first analytically compare the economic efficiency of single-pricing and dual-pricing mechanisms. Furthermore, we formulate an optimal pricing mechanism that can deter the potential exercise of market power by LCGs. Our analytical results characterize the conditions under which a dual pricing is advantageous over a single pricing. We further compare the economic efficiency of these mechanisms with respect to our proposed optimal mechanism through simulations. We show that the proposed pricing mechanism would be the most efficient in comparison with others and discuss its practicability. Managerial implications: Our analytical comparison reveals market conditions under which each pricing mechanism is a better fit and whether there is a need for a redesign. In particular, our results suggest that existing pricing mechanisms are adequate at low/moderate market shares of LCGs but not for the high levels currently envisaged by policymakers in the transition to decarbonization, where the optimal pricing mechanism will become more attractive.Funding: R. Belo acknowledges funding by Fundação para a Ciência e a Tecnologia [UIDB/00124/2020, UIDP/00124/2020 and Social Sciences DataLab – PINFRA/22209/2016], POR Lisboa, and POR Norte [Social Sciences DataLab, PINFRA/22209/2016].Supplemental Material: The e-companion is available at https://doi.org/10.1287/msom.2021.0555 .

Coordinated and decentralized trading of flexibility products in Inter-DSO Local Electricity Markets via ADMM

Local Electricity Markets (LEMs) arise as new layers of current market designs, enabling local trading of flexibility products. In many cases, LEMs encompass several networks, involving different Distribution System Operators (DSOs). This setting raises intrinsic concerns regarding the information privacy of the involved DSOs while trying to achieve system-wide efficiency. In this paper, a market design for the trading of flexibility products in inter-DSO LEMs is proposed where the DSOs are allowed to trade among the areas under the coordination of a Local Market Operator (LMO). A coordinated and decentralized approach based on the Alternating Direction Multiplier Method is proposed. The novel aspect of this work is that each DSO self-schedules its own assets in response to market signals (optimal dual variables) to fulfil the flexibility requests from itself or from other DSOs. An illustrative case study based on the IEEE 123 bus test systems is used for testing the proposed framework.

Electricity market modeling considering a high penetration of flexible heating systems and electric vehicles

The electrification of the heating and transportation sectors is a major building block in Germany’s effort to reduce carbon dioxide emissions. The additional loads and flexibilities resulting from the anticipated large-scale integration of the heating and transportation sectors necessitate an adequate representation in electricity market modeling. First, the paper presents a comprehensive modeling approach of the heating sector in a pan-European electricity market simulation considering both small-scale building heat pumps and large-scale conversion units with thermal energy storages in district heating networks. The operation of small-scale building heat pumps is emulated using an electro-thermal 1R1C building model integrated into the economic dispatch formulation while the operation of units in district heating networks is restricted by additional constraints resulting from the combined heat and power output, local heat load coverage and possible heat power transfer between heating networks. The transportation sector is mapped using previously published models by the authors including both controlled and fast charging processes. Subsequently, the load shift potentials resulting from the market-integration of the heating and transportation sectors and their impact on the pan-European electricity market with focus on Germany based on the three target years 2030, 2040 and 2045 are examined. Furthermore, by applying a Monte Carlo simulation to map possible future primary energy source prices a major uncertainty dimension is addressed. Considering the current German electricity market design, the integration of the two sectors lead to a moderate increase in future annual electricity demands and a substantial increase in market-based peak load. The resulting annual peak load from power-to-heat devices account to 22 GW (2030), 53 GW (2040) and 102 GW (2045) and from electric vehicles to 12 GW (2030), 36 GW (2040) and 96 GW (2045) for the target years. Further results demonstrate the larger load-shift potentials of electric vehicles compared to building heat pumps by comparing the weighted annual average market price of the flexible loads. The primary fuel price uncertainty is examined based on the 0.25, 0.50 and 0.75 quantiles for the target years which result in annual average electricity market price spreads of over 2.16 (2030), 2.97 (2040) and 3.44 (2045) between the 0.25 and 0.75 quantile scenarios.

BATTPOWER application: Large-scale integration of EVs in an active distribution grid – A Norwegian case study

With the considerable increase of Distributed Energy Resources (DER), reliable and cost-effective operation of distribution grids becomes challenging. The efficient operation relies on computationally dependable and tractable optimisation solvers, which may handle: 1) non-linear AC power flow constraints, and 2) time-linking variables and constraints and objectives of DER, over the operational horizon. In this paper, we introduce an application of a high-performance MultiPeriod AC Optimal Power Flow (MPOPF) solver, called “BATTPOWER”, to simulate active distribution grids for a near-future scenario. A large-scale Norwegian distribution grid along with a large population of Electric Vehicles (EV) are here taken as the case-study. We suggest and analyse three operational strategies (in terms of control of charge scheduling fleet of EV) for the Distribution System Operator (DSO): (a) uncoordinated charge scheduling, (b) coordinated charge scheduling with the objective of energy cost-minimisation without operational constraints of the grid, and (c) coordinated charge scheduling with the objective of energy cost-minimisation along with the operational constraints of the grid. The results demonstrate that the uncoordinated charging would lead to: 1) overloading of lines and transformers when the share of EVs is above 20%, and 2) higher operational costs than the proposed control strategies of (b) and (c). In strategy (b) operational line/transformer limits are violated when the populations of EVs are growing above 36%. This implies that current market design must be altered to allow active control of a large proportion of DERs within grid operational limits to achieve cost minimization at system level. To our knowledge, the work presented in this paper is the first ever attempt to do a comprehensive analysis of the impact of EV charging demand on a real Norwegian distribution grid. Moreover, the inference of the analysis says that the Norwegian distribution networks are more prone to congestion problems than the voltage problems for the EV demand which includes a smart charging scheme accounting for grid conditions.

Scarcity events analysis in adequacy studies using CN2 rule mining

Dealing with scarcity events is nowadays gaining relevance in electricity market studies, as traditionally predictable generation and consumption patterns are fading. Policymakers and system planners use therefore adequacy studies to a) understand if the current market design will attract sufficient generation capacity to meet electricity demand in the future and b) to comprehend what drives system inadequacy or resource scarcity when future scenarios lack adequate capacity. This work addressed the latter and showcases a first in-its-kind rule-based methodology that filters scarcity events from a large set of electricity market simulations. In this proof-of-concept, a rule-mining algorithm is applied to outputs from ENTSO-E's Pan-European electricity market model, which is run for 700 model scenarios, each covering 8760 time steps. The developed methodology shows how to unveil potential reasons behind scarcity events in an automated, interpretable, and scalable manner.

Beyond Control: Policy Incoherence of the EU Emissions Trading System

In this article, we explain why the current climate policy mix of the European Union (EU), consisting of the EU Emissions Trading System (ETS) and overlapping policies, is incoherent with respect to emission abatement and cost-effectiveness. The concept of policy coherence guides our analysis in identifying the EU ETS’ current dynamic supply adjustment mechanism, the Market Stability Reserve (MSR), to be at the heart of the shortcomings of current market design. Incoherence emerges due to the MSR’s quantity-based indicator for scarcity. It only works well for current and past demand fluctuations, but not for anticipated changes in demand, e.g., caused by a member state’s fossil-fuel phase-out. As a result, instead of fostering synergies as intended, the MSR undermines coherence by creating backfiring interactions and making precise predictions of overlapping policies’ impacts close to impossible. Considering the European Commission’s reform proposal of July 2021, we argue that a change in the MSR’s parametrisation leaves the fundamental cause of incoherence unaddressed. Based on recent findings in the economics literature, we propose introducing a price-based indicator for scarcity as a solution to substantially reduce the current incoherence of the policy mix.

An Intraday Market Design for Colombia’s Energy Transition

The massive promotion of intermittent renewable resources as a decarbonization strategy for economies has led to the need to reconsider current market designs in order to facilitate the integration of this kind of production technology. The intraday market has established itself as an efficient mechanism for these purposes, as has been seen in diverse international experiences, principally Europe. The Colombian electricity market is no stranger to the needs of these reforms, as the National Energy and Mining Planning Office of Colombia (UPME in Spanish) estimates that by 2034 almost 30% of the electricity generation matrix will be comprised of intermittent renewable resources. This paper develops several elements to be considered for the implementation of an intraday market in Colombia, backed with quantitative information, contrary to previous studies that have based their recommendations on qualitative elements. The number of discrete intraday sessions, the effect of changing from a sequential energy and reserve allocation scheme to a co-optimized one, as well as the adjustment mechanism – or a balance mechanism – after the gate closure are, among other aspects, analyzed in this study. The computational simulations executed with real data from two operating months with different characteristics in terms of prices, unavailable assets – a liquidity factor for the new market – and system contingencies support the design elements developed in this study. That is, the proposed design – four sections, co-optimization of energy and reserve, and an adjustment mechanism that is not based only on the use of reserves – tested with real data confirm that this proposal is more convenient than the other kind of design from an operating cost and unavailability management perspective. The results reveal market design elements that must be considered in Colombia and serve as input for other countries – particularly Latin American countries – that are in the process of updating their electricity market designs as part of the current energy transition.

A Novel Ventilator Design for COVID-19 and Resource-Limited Settings

There has existed a severe ventilator deficit in much of the world for many years, due in part to the high cost and complexity of traditional ICU ventilators. This was highlighted and exacerbated by the emergence of the COVID-19 pandemic, during which the increase in ventilator production rapidly overran the global supply chains for components. In response, we propose a new approach to ventilator design that meets the performance requirements for COVID-19 patients, while using components that minimise interference with the existing ventilator supply chains. The majority of current ventilator designs use proportional valves and flow sensors, which remain in short supply over a year into the pandemic. In the proposed design, the core components are on-off valves. Unlike proportional valves, on-off valves are widely available, but accurate control of ventilation using on-off valves is not straightforward. Our proposed solution combines four on-off valves, a two-litre reservoir, an oxygen sensor and two pressure sensors. Benchtop testing of a prototype was performed with a commercially available flow analyser and test lungs. We investigated the accuracy and precision of the prototype using both compressed gas supplies and a portable oxygen concentrator, and demonstrated the long-term durability over 15 days. The precision and accuracy of ventilation parameters were within the ranges specified in international guidelines in all tests. A numerical model of the system was developed and validated against experimental data. The model was used to determine usable ranges of valve flow coefficients to increase supply chain flexibility. This new design provides the performance necessary for the majority of patients that require ventilation. Applications include COVID-19 as well as pneumonia, influenza, and tuberculosis, which remain major causes of mortality in low and middle income countries. The robustness, energy efficiency, ease of maintenance, price and availability of on-off valves are all advantageous over proportional valves. As a result, the proposed ventilator design will cost significantly less to manufacture and maintain than current market designs and has the potential to increase global ventilator availability.

The Brazilian electricity market architecture: An analysis of instruments and misalignments

Brazil's current electricity market design heavily relies on auctions, long-term contracts, and central coordination mechanisms. Combining these instruments has proved to be effective in ensuring resource adequacy, a key policy objective. However, the implications of the dominance of the centrally coordinated auctions for long-term contracts are worth examining. This paper argues that the current market architecture may not represent the optimum long-term solution for a sustainable market as it ignores consumer preferences to drive investment decisions, transfers risks to consumers, has made the short-term market less relevant, and suffers from regulatory and design complexities.

Development of customized support for the prevention of Pressure Ulcer (PU) using multi-materials printing

Pressure Ulcers (PU) seems to be one of the most challenging healthcare problems around the world. It may result in significant morbidity, mortality and is associated with high cost in terms of treatment and care. PU is considered to be the third most expensive disorder after cancer and cardiovascular diseases. Though, modern medical science has launched a variety of treatment methods, prevention is the best way to overcome. As it could be seen from the current market design, most of the products provide a cushioning effect to the end user, but this lacks in product customization. Further, these products are not custom made to meet the end user needs and these products are expensive to be used. Understanding the above intricacies, the current research is focused entirely to be different from the existing product design, working, manufacturing methods and materials for the development of a product to redistribute the pressure for the reduction of PU. The projected design purely depends only on mechanical materials and mechanical behaviors. In this work, the number of phases of design was carried out through Solid Works software. The deformation and stress analysis was carried for all the design phases for obtaining the better design. Finally, the prototype is developed through Additive Manufacturing (AM) technology with the multi-material combination. The final prototype was evaluated experimentally using emed® sensing platform for the flexibility and pressure distribution also compared with the existing cushions.

Modeling zonal exchanges and nodal system representation in multi-zonal spot electricity markets

A novel model for the solution of the flow-based market coupling problem in multi-zonal spot electricity markets with zonal exchanges is presented in this paper. The problem considers a hybrid network configuration, i.e. a zonal market layer with zonal portfolio offers / bids submitted by the participants and zonal market clearing prices, and a nodal physical layer with nodal representation of the transmission system flows and relevant constraints. The model provides the optimal supply / demand cleared quantities and zonal exchanges, endogenously bounded by grid physical constraints, e.g. branch physical limits. The model retains the intuitiveness of the zonal exchanges, namely exchanges are cleared only from low-price zones to high-price zones. The model exhibits a dynamic/optimal allocation of zonal to nodal volumes. This market setup is fully compliant with the current market design in Europe, where portfolio participation in spot market with zonal prices, intuitive exchanges and with nodal flow-based constraints is the preferred scheme of the European Commission based on Regulation 2015/1222. The model is compared in terms of overall social welfare, pricing and cleared exchanges with the currently applied approach in Europe plus a “tuning” model for the simulation of redispatching to avoid congestion in physical branches.

Deleterious effects of strategic, profit-seeking energy storage operation on electric power system costs

Energy storage will play a key role in the unfolding energy transition, but current market design and the modeling efforts that inform discussions surrounding its role broadly assume that these systems will not be deployed in ways deleterious to the objectives of the wider power grid. This is myopic: there are plausible and strategic modes of storage operation that clash with wider grid objectives while maximizing profits for storage system owners. Here we compare three modes: one that is commonly modeled and is broadly beneficial to the power system—peak shaving—with two plausible but deleterious ones—load leveraging and ramp augmenting—and show how the latter two increase system costs and help generators earn substantial profits even when they bid at marginal cost. Our work adds to a growing literature about the unintended consequences of energy storage on the power system and elaborates the essential role of policy makers and regulators in mitigating these effects.

Re-Designing GB’s Electricity Market Design: A Conceptual Framework Which Recognises the Value of Distributed Energy Resources

The design of electricity markets determines the technologies, services and modes of operation that can access value, consequently shaping current and future electricity landscapes. This paper highlights that the efficacy of Great Britain’s electricity market design in facilitating net zero is inadequate and must be reconfigured. The rules of the current electricity market design are remnants of an electricity sector dominated by large-scale, centralised, fossil fuel technologies. Therefore, routes to market for the provision of necessary services to support net zero, not least flexibility, are largely inaccessible for distributed energy resources and, despite their benefits to the system, are thus undervalued. Based upon a review and consolidation of 30 proposed electricity market designs from liberalised electricity sectors, this paper proposes a new electricity market design for Great Britain. This design is presented alongside a new institutional framework to aid in the efficient operation of the market. Specifically, this paper proposes a new local balancing and coordinating market located at each grid supply point (the transmission and distribution interface). This is realised through the implementation of a distributed locational marginal pricing structure which is governed by the evolution of the current distributed network operator, known as the distributed service provider (DSP). The DSP also operates a local balancing and ancillary market for their geographical area. The wholesale market is reconfigured to coordinate with these new local markets and to harmonise the actors across the distribution and transmission network.

The impact of variable renewable energy technologies on electricity markets: An analysis of the Turkish balancing market

As global investment in renewable energy technologies continue to trend upward, the effects of variable (intermittent) renewable energy technologies on power markets have created serious challenges for regulators and policymakers. The literature on the effects of these technologies on day-ahead markets has been well established; however, further research is required on intra-day and real-time (balancing) markets to understand how these technologies are changing electricity market dynamics. In this respect, this study aims to assess the effects of the variable renewable energy technologies (wind and run-of-river hydro) on Turkish balancing market prices using quantile regression. In addition, ordered logistic regression is used to evaluate how system imbalances are changing as a result of these technologies. Model results show that system marginal price declines as variable renewable energy generation increases. Moreover, there is a higher probability of positive imbalance as the positive difference between real-time and projected variable renewable energy generation increases. Overall, an increase in variable renewable energy generation implies lower prices, but higher positive imbalances for the system. Hence, we recommend that Turkey should revise its current market design to incorporate the geographical and temporal generation characteristics of these technologies.

Characteristics of locational uncertainty marginal price for correlated uncertainties of variable renewable generation and demands

With the rapid increase of variable renewable energy sources in power systems, how to manage and price the uncertainty of renewable resources’ power outputs is becoming an urgent issue. Current market designs considering the uncertainties are mainly based on the probabilistic scenario set of demand and renewable energy resources power outputs. This consideration makes market designs vulnerable to three significant challenges when put into practice. First, the accurate probability distribution of renewable generation is hard to obtain in real-time. Second, it is challenging to clear the market timely with many scenarios to guarantee accuracy. Third, generation cost recovery cannot be guaranteed for some scenarios. To overcome these challenges, this paper proposes a locational uncertainty marginal price model to price the uncertainty explicitly based on a scenario-free stochastic market-clearing model. Instead of using the probabilistic scenario set, the uncertainty of renewable energy sources and loads is modeled with distributionally-robust chance constraints. The correlation of uncertainties can be endogenously modeled in both the market-clearing and the locational uncertainty marginal price formation. Furthermore, this paper proves that generation cost recovery, revenue adequacy, and partial market equilibrium can be achieved using the locational uncertainty marginal price model. Numerical results from both the small and large systems simulations validate that the generation cost recovery is maintained no matter the generation participates in uncertainty mitigation or not. The transmission congestion surplus is also allocated appropriately among loads, renewable energy sources, and financial transmission right owners.

Transmission Network Investment Using Incentive Regulation: A Disjunctive Programming Approach

A well-planned electric transmission infrastructure is the foundation of a reliable and efficient power system, especially in the presence of large scale renewable generation. However, the current electricity market designs lack incentive mechanisms which can guarantee optimal transmission investments and ensure reliable integration of renewable generation such as wind. This paper first proposes a stochastic bilevel disjunctive program for optimal transmission investment based on the newly proposed theoretical H-R-G-V incentive mechanism. The upper level is a profit-maximization problem of an independent transmission company (Transco), while the lower level is a welfare maximization problem. The revenue of the Transco is bounded by a regulatory constraint set by the regulator in order to induce socially optimal investments. The application of the H-R-G-V mechanism allows the regulator to ensure social maximum transmission investments and helps to reduce transmission congestion and wind power spillage. The transmission investment under the H-R-G-V mechanism is modeled as a stochastic bilevel disjunctive program. To solve the developed mathematical model we first propose a series of linearization and reformulation techniques to recast the original model as a stochastic mixed integer linear problem (MILP). We exploit the disjunctive nature of the reformulated stochastic MILP model and further propose a Bean decomposition algorithm to efficiently solve the stochastic MILP model. The proposed decomposition algorithm is also modified and accelerated to improve the computational performance. The computational performance of our MILP modeling approach and modified and accelerated Bean decomposition algorithm is studied through several examples in detail. The simulation results confirm a promising performance of both the modeling approach and its solution algorithm.

Evolving Bidding Formats and Pricing Schemes in USA and Europe Day-Ahead Electricity Markets

This paper compares the evolution of USA and European power markets and evaluates the suitability and future challenges of their designs in the context of the transition to a low-carbon power system. The analysis focuses on bidding formats (the way in which organized electricity markets allow participants to express their operational constraints) and pricing schemes (how agents recover their short-term costs from market prices). The radical evolution of the power mixes worldwide already experienced in the last decade and the larger one to come, with even greater shares of renewable energy and a more prominent role for storage resources, exposes limitations in current market designs. We develop an in-depth and comprehensive review of best practices from both sides of the Atlantic, and learning from them, we draw recommendations to evolve these market design elements.

The impact of market design on transmission and generation investment in electricity markets

In this paper we propose an equilibrium model in order to analyze the impact of electricity market design on generation and transmission expansion in liberalized electricity markets. In a multi-level structure, our framework takes into account that generation investment and operation is decided by private investors, while network expansion and redispatch is decided by a regulated transmission system operator — as well as the different objectives of firms (profit maximization) and the regulator (welfare maximization). In order to illustrate the possibilities to quantify long term economic effects with our framework, we calibrate our model for the German electricity market. We consider various moderate adjustments of the market design: (i) the division of the market area into two price zones, (ii) the efficient curtailment of renewable production and (iii) a cost-benefit-driven balance between network expansion and network management measures. We then analyze the impact of these market designs on generation and transmission investment in case those design elements are anticipated upon network development planning. The resulting investment and production decisions are compared to a benchmark that reflects the current German electricity market design and to an overall optimal first-best benchmark. Our results reveal that price zones do have a significant impact on locational choice of generators and result in a reduced need for network expansion, but lead to only moderate annual welfare gains of approximately 0.9% of annual total system costs. Anticipation of optimal curtailment of renewables and a cost-benefit-driven use of redispatch operations upon network expansion planning, however, implies a welfare gain of over 4.9% of annual total system costs per year as compared to the existing market design, which equals 85% of the maximum possible welfare gain of the first-best benchmark.