Wholesale Energy Research Articles

EUROPEAN REMIT REGULATION AS THE LATEST DETERMINANT OF CORPORATE RISK MANAGEMENT STRATEGIES IN ENERGY SECTOR

The purpose of the paper is to summarize and present the fundamental trends of the past few decades related to the financial crisis of 2008 and growing integration of European sovereign economies, including the integration of energy markets, that led to development of regulation of relationships and preventing manipulation in such markets. This regulation has become a powerful new determinant for the European multinational enterprises of the energy sector (MNE) when developing their own risk management strategies. Methodology. The analysis is based on the recent studies of the pan-European power exchange company Nord Pool Group, international organization Energy Community and relevant regulations and recommendations of the European Parliament and of the Council and European Union Agency for the Cooperation of Energy Regulators. Results of the analysis showed the growing demand for transparency and stability in the European wholesale energy markets. This demand was reflected in the EU Regulation 1227/2011 on Wholesale Energy Market Integrity and Transparency (REMIT) that was adopted by the European Parliament and the Council of the EU in 2011. While REMIT Regulation, on one hand, provides reliable and equal conditions for MNE, on the other hand, it increases the risk and burden of REMIT compliance obligations for such MNE. The consequences of misconduct can potentially be serious – both high fines and personal liability of MNE employees. Today the European multinational enterprises of the energy sector must develop the respective risk management strategies to ensure effective governance of this type of risks. Practical implications. MNE participants of the EU energy market should develop efficient risk management strategies to comply with REMIT requirements, in addition to existing commitments on the transparency of the Third Package. The REMIT compliance risk management strategies will support MNE market participants in complying with rules and policies, creating a secure structure for employees of such enterprises and promoting fair and equal conditions for trade, trusting the energy market. Furthermore, proper REMIT compliance risk management strategy will help to avoid or minimize the risk of fines and other regulatory sanctions and potential civil lawsuits. It will also help to avoid or minimize the risk of reputation loss, such as negative media reviews or poor customer experience. Value/originality. The conducted analysis provides deep understanding of the main drivers of the European wholesale energy markets regulations that create a compelling determinant for the risk management strategies of multinational enterprises of the energy sector. Ukraine has committed itself to the Energy Community to implement the REMIT Regulation in its regulatory field, which increases the relevance of developing appropriate multinational enterprises risk management strategies within the country.

Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning

To reduce global greenhouse gas emissions, the world must find intelligent solutions to maximise the utilisation of carbon-free renewable energy sources. In this paper, multi-agent reinforcement learning is used to control a microgrid in a mixed cooperative and competitive setting. The agents observe fluctuating energy demand, dynamic wholesale energy prices, and intermittent renewable energy sources to control a hybrid energy storage system to maximise the utilisation of the renewables to reduce the energy costs of the grid. In addition, an aggregator agent trades with external microgrids competing against one another and the aggregator to reduce their own energy bills. For this, the algorithm deep deterministic policy gradients (DDPG) and multi-agent DDPG (MADDPG) are used to compare the use of a single global controller versus multiple distributed agents, along with the single and multi-agent variants of distributional DDPG (D3PG) and twin delayed DDPG (TD3). The research found it is significantly more profitable for the primary microgrid to sell energy on its own terms rather than selling back to the utility grid, and is also beneficial for the external microgrids as they also reduce their own energy bills. The methods that produced the greatest profits were the multi-agent approaches where each agent has its own reward function based on the principle of marginal contribution from game theory. The multi-agent approaches were better able to evaluate their performance controlling individual components of the environment which allowed them to develop their own unique policies for the different types of energy storage system.

Robust prequalification process of a distribution system operator considering N‐1 contingency

A distributed energy resource aggregator (DERA) participates in the wholesale energy market (WEM) on behalf of aggregated distributed renewable energy sources (DRESs). The DERA manages DRESs according to the dispatch signal from the system operator (SO). However, a conventional independent SO that operates the WEM and transmission system does not monitor the distribution system. Therefore, overvoltage or overflow problems can occur during the generation of DRESs in a distribution system in which bids are accepted in the WEM. To address these problems, previous studies proposed the prequalification process. In the process, a distribution SO (DSO), which is responsible for the reliability of the distribution system, reviews DERA's bids before it is submitted to the WEM. However, these studies do not consider the outages of the system components. Therefore, we propose an N-1 contingency prequalification process (N-1 PP). The DSO manages the DERA's bid considering both the uncertainties and system states after the reconfiguration in contingency situations. In the proposed scheme, the DERA's bid is reviewed for severe faults and post-reconfiguration systems. The results indicate that the N-1 PP is more stable and durable than the prequalification process of previous studies.

ON CRIMINAL LEGAL ADEQUACY OF CRIMINALIZATION OF ABUSE IN WHOLESALE ENERGY MARKETS

The article is devoted to a critical analysis of the decision of the Verkhovna Rada of Ukraine to supplement the Criminal Code of Ukraine with two new articles 222-2 and 232-3, as a result of which scientifically based conclusions were made about the social conditionality of these changes, in particular, their compliance with such a principle of criminalization as the principle of criminal - political adequacy of criminalization. In particular, based on the results of writing the article, the erroneousness of the method of improving the criminal legislation chosen by the parliamentarians and embodied by the Law of June 19, 2020 “On Amendments to Certain Legislative Acts of Ukraine on Simplification of Attracting Investments and Introduc­tion of New Financial Instruments” was proved. It is pointed out that in Ukraine at the legislative level (by the Law of November 15, 2011 “On Amendments to Certain Legislative Acts of Ukraine on the Humanization of Responsibil­ity for Offenses in the Sphere of Economic Activity”) it was clearly fixed (by excluding Articles 228 and 230 of the Criminal of the Code of Ukraine) a provision on the inexpediency of crimi­nal law regulation of relations in the field of compliance with competition law. At the same time, it is noted that the aforementioned Law of June 19, 2020 introduces two new norms into the system of Section VII of the Special Part of the Criminal Code of Ukraine “Criminal offenses in the field of economic activity” (Articles 222-2 and 232-3), which impor­tantly, without a single justification for this step, criminal liability is established for individual manifestations of anti-competitive actions in only one area - in the wholesale energy markets. Taking into account the above arguments, a general conclusion is made that when supple­menting the Criminal Code of Ukraine with articles 222-2 and 232-3, the principle of criminal-political adequacy of criminalization was grossly violated.

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world’s electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. In this paper, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES’s bidding, scheduling, and control decisions and the energy market’s clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

Stacked Revenues Maximization of Distributed Battery Storage Units Via Emerging Flexibility Markets

Power system flexibility is seen as a key for addressing the management challenges in the future smart grids. Distributed Energy Resources (DERs) can provide the necessary flexibility to: a) maintain a stable frequency and a secure energy supply in an overall system perspective, and b) maintain bus voltages and secure transfer capacities in their local networks. In this context, Flexibility Service Providers (FSPs) facilitate the management of the transmission and the distribution network, while at the same time they optimally exploit their DERs. This work proposes a bilevel model for an FSP owning distributed Battery Storage Units and participating in: i) wholesale Energy, Reserve and Balancing Markets, and ii) a novel distribution-level Flexibility Market. The developed model is applied to the IEEE 33-bus radial distribution system and the results demonstrate that it achieves superlinear gains. Finally, a sensitivity analysis is conducted to study the impact of several externalities on the FSP's decisions.

Real-Time Control of Distributed Batteries With Blockchain-Enabled Market Export Commitments

Recent years have seen a surge of interest in distributed residential batteries for households with renewable generation. Yet, assuring battery assets are profitable for their owners requires a complex optimisation of the battery asset and additional revenue sources, such as novel ways to access wholesale energy markets. In this paper, we propose a framework in which wholesale market bids are placed on forward energy markets by an aggregator of distributed residential batteries that are controlled in real time by a novel Home Energy Management System (HEMS) control algorithm to meet the market commitments, while maximising local self-consumption. The proposed framework consists of three stages. In the first stage, an optimal day-ahead or intra-day scheduling of the aggregated storage assets is computed centrally. For the second stage, a bidding strategy is developed for wholesale energy markets. Finally, in the third stage, a novel HEMS real-time control algorithm based on a smart contract allows coordination of residential batteries to meet the market commitments and maximise self-consumption of local production. Using a case study provided by a large U.K.-based energy demonstrator, we apply the framework to an aggregator with 70 residential batteries. Experimental analysis is done using real per minute data for demand and production. Results indicate that the proposed approach increases the aggregator's revenues by 35% compared to a case without residential flexibility, and increases the self-consumption rate of the households by a factor of two. The robustness of the results to uncertainty, forecast errors and to communication latency is also demonstrated.

Energy trading efficiency in ERCOT’s day-ahead and real-time electricity markets

The efficient market hypothesis (EMH) is a fundamental tenet of active and unfettered market trading. The EMH for intertemporal trading of a commodity such as natural gas implies that today’s futures price is an unbiased predictor of a future delivery period’s spot price and that the difference between today’s futures and spot prices reflects the commodity’s cost of carrying. The EMH for inter-regional trading requires the commodity’s regional price difference to equal the inter-regional transportation cost. Using regional hourly data for January 1, 2011 to December 31, 2020 from the Electric Reliability Council of Texas (ERCOT), we investigate whether the EMH is empirically valid in all ERCOT’s wholesale electricity markets and, if not, the extent of ERCOT’s energy trading inefficiency and what can be done to reduce it. By estimating a parsimonious system of eight price-level regressions and four price-difference regressions, we reject the interday EMH for all regions and the inter-regional EMH for all regional market pairs. However, ERCOT’s extent of trading inefficiency is mild when compared to the wholesale energy prices. Our empirical examples have two policy implications: enhancing ERCOT’s interday trading efficiency entails improving the day-ahead forecasts for solar and wind generation and refining ERCOT’s indicative real-time market prices, while enhancing ERCOT’s inter-regional trading efficiency requires transmission capacity expansion to reduce transmission congestion and line losses.

A locational marginal price for frequency balancing operations in regulation markets

The integration of increasingly more renewable energy resources on the electric grid requires consideration of market design for balancing power intermittency. We propose a new locational marginal price for the frequency regulating reserves currently utilized by system operators to balance random power fluctuations on electric grids. Like the widely used wholesale energy price, our proposed price considers the locational effects of delivering electricity services across a congested transmission system. We further propose a regulation market settlement policy which requires market participants with variable power injections to pay based on their frequency regulation needs instead of their energy needs. The calculation of the proposed price and market design is demonstrated using a test case. The results of the test case are further generalized to larger systems. We find the proposed price is more efficient than current regulation market clearing prices and better aligns regulation market design with the wholesale energy market. The limitations and market implications of this proposal are discussed.

A multi-timescale operation model for hybrid energy storage system in electricity markets

The hybrid energy storage system (HESS) connecting different types of energy storage system (ESS) can be used to handle the several timescale variations of the components in power system. In this paper, a multi-timescale economic scheduling strategy for the HESSs to participate in the wholesale energy and reserve market considering the uncertainty of load and renewable generation. The economic multi-timescale HESS scheduling is a three-level model including day-ahead scheduling, intraday operation, and real-time operation. To better cover the hybrid requirements in the stochastic problem, the operation cycle limits model is introduced to avoid the frequent switching of energy-based ESS as well as the deviation cost of HESS’s capacity is used in the finer timescale to guide the future requirement. An improved algorithm that integrates the Progressive Hedging (PH) and Dual Decomposition (DD) algorithms are used to solve this problem. The proposed strategy can realize the efficient management of HESSs to reduce the energy management complexity and system operation costs with high computation efficiency, which indicates its promising application in the HESS economic scheduling.

Single electricity market forecasting and energy arbitrage maximization framework

The rapid deployment of renewable-based generation to meet the net-zero carbon targets has affected the wholesale energy paradigm. In the island of Ireland, the Single Electricity Market (SEM) aims to deliver high levels of supply security, reliability, and transparency through multiple markets with different trading time frames and clearing procedures. This paper proposes a powerful methodology to maximize the revenues from the participation in the SEM. A forecasting model of four successive stages based on neural networks is proposed to predict the demand and system marginal prices of the SEM ex-ante markets. An energy arbitrage optimization framework is proposed for battery energy storage systems (BESS) to maximize the arbitrage profits. The methodology efficacy is validated by achieving 91.1% selling accuracy, 97.9% buying accuracy, and 85.1% energy arbitrage net accuracy of the ideal case where the SEM data is perfectly-known for three consecutive months. Furthermore, the BESS degradation is evaluated and a cost-benefit analysis is introduced to evaluate the economic feasibility of BESS participating in the SEM ex-ante markets. The results reveal that the participation of BESS in the SEM solely is not profitable, however, under stacked revenues arrangement, the proposed methodology can be applied to boost the BESS revenues.

Developing a legal framework for energy storage technologies in the U.S: The case of pumped underground storage hydro

The Energy Act of 2020 authorizes $1 billion over five years from 2021 to 2025 to support energy storage development in the United States. In addition, the Federal Energy Regulatory Commission (FERC) Orders 841 and 2222 opened the wholesale energy markets for distributed energy resources, including energy storage. The statute and orders pave the way for novel energy storage technologies to participate in electricity markets as the qualifying facilities, thereby expanding opportunities for energy storage development. However, the existing policy, legal, and regulatory regime, including these much-welcomed newcomers, fails to recognize and support the entire spectrum of benefits that some forms of energy storage create. In this paper, we focus on Pumped Underground Storage Hydro (PUSH), a variant of pumped hydro storage (PHS), which currently provides over 90% of the world's energy storage capacity. PUSH operates with the same principle as PHS; however, it is an entirely underground variant of PHS. In addition to becoming competitive in the wholesale electricity market, PUSH facilities can be developed as community infrastructure in the postindustrial landscape, particularly in abandoned underground mines. Given federal energy law and policy development, this paper identifies how communities with abandoned mines, technically feasible for PUSH facilities and operating as municipal-owned utilities or cooperatives, can participate and take advantage of federal legislation. We further look into the implications through the lens of technical, economic, and social aspects of energy justice. We consider energy justice as a conceptual framework that seeks to explain the occurrence of injustice within energy system decisions and outcomes and how policymakers can respond to these injustices. We use it as a conceptual tool for understanding policy formulation and detailing the energy system's missing ethical and justice dimension. We argue that as a technically mature technology, PUSH facilities can act as a potential means to speed up the energy transition in the United States. The federal and state law along with utility market structures are vital in shaping the potential opportunities and barriers for energy storage facilities like PUSH. We show that although it supports PUSH development, there are gaps in the current market structure, specifically in the regulatory framework, when seen through the lens of justice and valuation of just energy services. These gaps limit the realization of utility-scale energy storage technology's potential to fully contribute to a decarbonized energy system that is more resilient and more just than the incumbent system.

Agent-based retail competition and portfolio optimization in liberalized electricity markets: A study involving real-world consumers

The liberalization of energy markets brought full competition to the electric power industry. In the wholesale sector, producers and retailers submit bids to day-ahead markets, where prices are uncertain, or alternatively, they sign bilateral contracts to hedge against pool price volatility. In the retail sector, retailers compete to sign bilateral contracts with end-use customers. Typically, such contracts are subject to a high-risk premium—that is, retailers request a high premium to consumers to cover their potential risk of trading energy in wholesale markets. Accordingly, consumers pay a price for energy typically higher than the wholesale market price. This article addresses the optimization of the portfolios of retailers, which are composed of end-use customers. To this end, it makes use of a risk-return optimization model based on the Markowitz theory. The article presents a simulation-based study conducted with the help of the MATREM system, involving 6 retailer agents, with different risk preferences, and 312 real-world consumers. The retailers select a pricing strategy and compute a tariff to offer to target consumers, optimize their portfolio of consumers using data from the Iberian market, sign bilateral contracts with consumers, and compute their target return during contract duration. The results support the conclusion that retail markets are more favourable to risk-seeking retailers, since substantial variations in return lead to small variations in risk. However, for a given target return, risk-averse retailers consider lower risk portfolios, meaning that they may obtain higher returns in both favourable and unfavourable situations.

Impact of Network Charge Design in an Energy System with Large Penetration of Renewables and High Prosumer Shares

The transformation of our energy system toward zero net CO2 emissions correlates with a stronger use of low energy density renewable energy sources (RES), such as photovoltaic (PV) energy. As a source of flexibility, distributed PV systems, in particular, are oftentimes installed in combination with battery storage systems. These storage systems are dispatchable, i.e., controllable by the operating owners, who can thereby take over an active market role as energy prosumers. The particular battery operation modes are based on the individual prosumer decisions, which, in turn, are strongly affected by the regulatory framework in place. Regulatory frameworks differ from country to country, but almost all regulatory frameworks feature a network charge mechanism, which allocates network infrastructure and operating costs to the end customers. This raises the question of the extent to which different network charges lead to different prosumer decisions, i.e., battery operation modes, and thus different energy system configurations (system costs). In order to evaluate this question we apply (a) a fundamental linear optimization model of the energy wholesale market, which we stringently link to (b) an analysis of peak-coincident network capacity utilization as well as (c) an evaluation of the complete costs of energy for prosumers and consumers. This stringent cycle of analysis is applied to two prototypical network allocation schemes. We demonstrate that network allocation schemes that are orientated to peak-coincident network capacity utilization could both better incentivize a distribution network-oriented behaviour and better share financial burdens between prosuming and purely consuming households than would be the case for volumetric network charge designs. This paper further demonstrates that network-oriented battery operation does not, per se, result in optimal RES integration at the wholesale market level and CO2 emissions reduction. To identify effects from increasing sector integration, an analysis is both performed for a setting without and with consideration of widespread e-mobility. As a broader conclusion, our results demonstrate that future regulatory frameworks should have a stronger focus on prosumer integration by means, among other things, of an adequate network charge design reflecting the increasingly distributed nature of our future energy system.

Does market concentration affect wholesale electricity prices? An analysis of the Indian electricity sector in the COVID-19 pandemic context

This study explores whether the market concentration affects the wholesale prices of electricity generation among Indian companies by drawing 15-min frequency data related to electricity production, wholesale prices, and electricity demand in August 2020 during the COVID-19 pandemic. The ARDL model estimates show a positive relationship between market concentration and wholesale energy prices. The study recommends the adoption of policies to reduce market concentration and enhance clean energy development.

Coordinated Operation Strategy for a Virtual Power Plant With Multiple DER Aggregators

This article proposes a coordinated operation strategy for a virtual power plant (VPP) with multiple DER aggregators under the wholesale energy and regulation service market. Considering the market clearing process, VPP operation profit, and DER aggregators’ interests, a tri-layer hierarchical framework for VPP is developed to formulate the bidding plans to the superordinate market operator and the dynamic price incentive curves for the subordinate DER owners cooperatively. By using the discrete price quota curves, big-M method, KKT optimal conditions, and strong duality theorem, the tri-layer problem is transformed into an equivalent and tractable mixed integer linear programming problem. Case study with the 141-bus system is conducted to validate the effectiveness of the proposed approach. The advantages of lower cost with operation security guarantee and higher flexibility are demonstrated by comparing with other models.

Expert survey on Energy Storage Systems: Regulation and policy from an Indian power sector perspective

A survey of Indian power-sector stakeholders on the subject of Energy Storage System (ESS) policy and regulatory issues is presented. The survey is divided into four sub-themes: the need for ESSs; ESSs in a network context; ESSs in the market; and ESSs in innovation. Respondents support the need for dedicated ESS regulation, including a definition of ESSs. In terms of networks, respondents support unrestricted ownership, and the development of dedicated grid connection standards and the provision of ancillary services for the network by ESSs; this would allow their participation in wholesale energy markets. However, opinions diverge on the level of ESS regulatory oversight needed for grid investment deferral. As far as power markets are concerned, respondents agree on the need for updating bidding formats, special treatment for ESSs regarding grid access charges to eliminate market entry barriers and to incentivise the operational versatility of ESSs. However, opinions diverge on the appropriate compensation mechanism to be applied for services provided by ESSs. There is an agreement on supporting innovative ideas such as P-to-everything (P2X) conversion and the use of regulatory sandboxes for enabling ESS.

Multi-objective energy procurement strategy of electricity retail companies based on normalized normal constraint methodology

The electricity retail market provides a marketplace for domestic consumers and retailers to buy and sell electricity in a competitive environment. Permitting final consumers to choose electricity retailers promotes suppliers’ pluralism and clients’ freedom, which leads to improvements in the quality of electricity retailing service. The main aim of a retailer and consumers is profit maximization, which highly depends on retail-selling price. Retailer’s profit may be explicitly reduced by decreasing retail selling-price or implicitly reduced by increasing retail selling-price as increasing these prices may decrease clients’ consumption. Accordingly, the retail selling-price, retailer energy procurement strategy, and clients’ consumption should be simultaneously analyzed from the viewpoints of retailer and clients. In this paper, a multi-objective optimization problem is introduced to obtain the retailer’s energy procurement strategy in terms of the profits of energy buyers and sellers. Moreover, the normalized normal constraint method as a proficient multi-objective optimization technique is utilized to solve the proposed multi-objective optimization problem determining the retailers’ energy procurement strategy and retail selling-prices. Since the wholesale energy price is a highly volatile uncertainty source affecting the retailer’s profit, the point estimate method is utilized to characterize the uncertainty of the wholesale energy price. Simulation results illustrate the effectiveness of the proposed non-deterministic multi-objective optimization problem.

Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning

As the world seeks to become more sustainable, intelligent solutions are needed to increase the penetration of renewable energy. In this paper, the model-free deep reinforcement learning algorithm Rainbow Deep Q-Networks is used to control a battery in a microgrid to perform energy arbitrage and more efficiently utilise solar and wind energy sources. The grid operates with its own demand and renewable generation, as well as dynamic energy pricing from a real wholesale energy market. Four scenarios are tested including using demand and price forecasting produced with local weather data. The algorithm and its subcomponents are evaluated against an actor-critic method and a linear programming model with Rainbow able to outperform all other methods. This research shows the importance of using the distributional approach for reinforcement learning for complex environments, as well as how it can visualise and contextualise the agents’ behaviour for real-world applications.

The Evolution of the Multitier Hierarchical Energy Market Structure: The emergence of the transactive energy model

Over the last 10 years, a combination of policy directives and technological advances has led to a rapid and significant addition of distributed energy resources (DERs), such as renewable energy source (RES) generation, demand response (DR), storage, and electric vehicles (EVs), into the distribution grid and behind the meter (BTM) in many power systems around the world. At the same time, the Internet of Things (IoT) revolution has emerged as a major market force that is expected to create massive flexible capacity, which can be harnessed to solve grid problems and assist in the integration of RESs into the grid. The penetration of DERs across various levels of the power system has created a hierarchical market structure where DERs could participate, either individually or through aggregations, in the form of virtual power plants (VPPs) in BTM markets and in distribution and wholesale markets. The landmark Federal Energy Regulatory Commission Order 2222 has further created a high-level regulatory framework for allowing DERs to bypass the distribution grid and directly participate in wholesale energy markets. In this multitier market architecture, transactive energy (TE) markets are emerging by allowing customers, either as individuals or in aggregate, to actively engage in energy markets by negotiating and responding to "value signals," based on price, demand, time of day, and other grid and local market considerations.