Market-based Control Research Articles

A cooperative transactive multi-carrier energy control mechanism with P2P energy + reserve trading using Nash bargaining game theory under renewables uncertainty

Transactive Energy Control (TEC) as a market-based control is a critical notion for scheduling Multi-Carrier Energy Systems (MCESs) in local networks and forming an Energy Hub (EH). Nevertheless, implementing TEC for scheduling and controlling MCESs is extremely difficult due to the lack of a cooperative TEC model that accounts for network constraints and the uncertainty of Renewable Energy Sources (RESs). This paper defines and formulates Prosumer-Based Multi-Carrier Energy Systems (PB-MCESs), which include electricity, heat, cooling, and gas hubs to enable internal coordination of resources and flexibility extraction for PB-MCESs. Subsequently, Nash Bargaining Game Theory is employed to construct a cooperative TEC that prioritizes P2P energy trade. In addition to P2P energy trading, PB-MCESs can trade their reserve in a P2P fashion to mitigate their uncertainty. PB-MCESs estimate the level of uncertainty using stochastic programming and allot a reserve capacity based on this estimation in order to manage their uncertainty via P2P reserve trading and internal reserves. PB-MCES can also control their risk by altering their risk-taking factor in accordance with the Conditional Value-at-Risk (CVAR) index. Implementations have demonstrated that the proposed cooperative TEC decreases total costs by 17.14% and that the proposed P2P reserve trading reduces total costs by 16.32%.

A Survey on Market-Inspired Intersection Control Methods for Connected Vehicles

Recent advances in wireless communication technology allow for the cooperative coordination of vehicles and infrastructures under vehicle-to-everything (V2X) communication protocols. V2X communication protocols are shaping a new reality for intersection control, allowing for individual driver preferences to be taken into account, such as heterogeneity in terms of value of time and willingness to pay to reduce individual delay. In this context, different economic instruments have been proposed for intersection control under connected vehicles, including various types of auctions, direct payments, and credit schemes. This study offers a comprehensive review on market-inspired control approaches under connected vehicles for both signalized and unsignalized intersections, focusing on auction-based and direct transaction schemes among drivers as incentive mechanisms for aligning user and system objectives. A structured way of analyzing the existing literature is introduced, underlining relevant methodological and practical issues. The key aspects of market-based control schemes are outlined, including priority allocation, types of agents employed, incentive compatibility, solution approaches, and validation. Emerging challenges for the implementation of such approaches and future research directions are then identified and discussed.

Transactive Energy Rationing in Islanded Electric Power Systems

Extreme weather events, many of which are climate-change related, are occurring with increasing frequency and intensity and causing catastrophic outages. One of the major modern-day concerns of utilities is dealing with such extreme outages and consequently, its repercussions on the lives of people in society and social aspects. Traditionally, operators have been using rolling blackouts as a contingency plan to serve critical loads during such events when electricity supply is scarce. However, such blackouts practices are executed on a last-minute mandatory basis, depriving customers having low-capacity high-priority loads (i.e. refrigeration, water, telecommunication, etc) that should also be serviced if at all possible. Historically, policymakers have often adopted quota-based regulatory actions or rationing for other commodities (such as gasoline, butter, sugar) to handle scarcity situations. Motivated from such quota-based systems, our contribution presented in this work is an alternative transactive rationing mechanism that would provide some minimum level of service to all of the customers and serve the critical loads using market-based control during such scarcity-based contingencies. This is in contrast to the state-of-art TE mechanisms that allocate resources to customers solely based on their willingness-to-pay. The effectiveness of the proposed mechanism is demonstrated through simulation-based evaluation on two real-life use cases having feeder-level and microgrid-level configurations respectively. Simulation results clearly demonstrate the capability of the rationing scheme to serve customers' high-priority loads through prolonged outages even during extreme scarcity scenarios.

Application of market-based control with thermal energy storage system for demand limiting and real-time pricing control

Imbalances in energy demand and supply related to increased use of renewable energy sources will eventually cause problems with the reliability of the power grid. The reliability of the grid requires ancillary services for power generation, as well as flexible consumption via demand response. In this paper, a multi agent-based distributed control strategy is proposed for commercial buildings to coordinate the flexible building loads with thermal energy storage systems (TESS). The distributed control uses the market mechanisms and price/incentive signals to engage self-interested responsive loads to provide services to the electrical power grid and managing buildings’ electricity consumption. The proposed strategy was validated in a simulation environment to provide two grid service use cases. One is to limit the peak demand of building in which a market clearing strategy with respect to the demand limit is proposed. The other one is to perform price responsive control, in which the peak demand of building responds to the time of use price signals. The peak load reduction is calculated as a percentage of baseline peak load measured in the baseline for the same day. Energy consumption cost saving is defined as the percentage change from the baseline over the entire 5-day simulation. The results show that: (1) the demand limit control can reduce by up to 14% of building energy cost and 13% of peak demand and (2) the price response control can reduce by up to 16% of building energy cost. Overall, the results demonstrate that the distributed control with TESS proposed in this study is effective in reducing electricity use and peak building electric demand.

Distributed coordination of deferrable loads: A real-time market with self-fulfilling forecasts

Increased uptake of variable renewable generation and further electrification of energy demand necessitate efficient coordination of flexible demand resources to make most efficient use of power system assets. Flexible electrical loads are typically small, numerous, heterogeneous and owned by self-interested agents. Considering the multi-temporal nature of flexibility and the uncertainty involved, scheduling them is a complex task. This paper proposes a forecast-mediated real-time market-based control approach (F-MBC) for cost minimizing coordination of uninterruptible time-shiftable (i.e. deferrable) loads. F-MBC is scalable, privacy preserving, and usable by device agents with small computational power. Moreover, F-MBC is proven to overcome the challenge of mutually conflicting decisions from equivalent devices. Simulations in a simplified but challenging case study show that F-MBC produces near-optimal behaviour over multiple time-steps.

Unified Control Strategy of Heterogeneous Thermostatically Controlled Loads with Market-based Mechanism

This paper studies the coordination of heterogeneous thermostatically controlled loads (TCLs) to provide the real-time ancillary services. A market-based control framework is adopted for its advantages. The first advantage is that the demand curve-oriented approach makes it possible to form a unified control scheme for heterogeneous loads without identifying their different characteristics. The second one is that the broadcast price signal helps simplify the downlink control and reduce the implementation cost. Then, the separate demand curve construction strategies based on a virtual price for different types of TCLs are presented. The flexibility of each TCL is reflected through the curve, and its practical constraints, i.e., comfort requirements of users and operation constraints of devices, are satisfied explicitly. To ensure the control fairness and full utilization for the regulation ability of TCL cluster, a comfort-level-equality principle is applied in demand curve construction. Simulations are carried out to verify the effectiveness of the proposed method in providing frequency regulation services, for which a regulation capacity estimation method is developed. Finally, a series of case studies are conducted considering the practical situations, e.g., model errors, imperfect communication and sudden load change after the end of services.

A novel transactive energy control mechanism for collaborative networked microgrids

Collaboration of networked microgrids (NMGs) with diverse generation sources is a promising solution to smooth volatile generation output and enhance the utilization efficiency of renewable energies. In addition to centralized and decentralized collaboration mechanisms, transactive energy control (TEC) is an emerging and effective market-based control to enable energy transactions among distributed entities such as NMGs. However, existing studies on TEC suffer from several major weaknesses such as unconstrained/simplified model formulations and slow convergence rates. This paper proposes a novel TEC mechanism to tackle these weaknesses. First, the centralized mechanism, decentralized mechanism, and subgradient-based TEC mechanism to coordinate the operation of NMGs are briefly reviewed and modeled by a scenario-based stochastic optimization method. A new TEC mechanism is then proposed, consisting of a TEC framework, mathematical model, pricing rule, and algorithm. The optimality of the proposed TEC mathematical model and pricing rule is demonstrated. The effectiveness of the proposed TEC mechanism is verified in case- studies where the NMGs operate in grid-connected, islanded, and congested modes. The advantages of the proposed TEC mechanism are also illustrated through comparisons with the centralized mechanism, decentralized mechanism, and subgradient-based TEC mechanism.

Transactive Control Design for Commercial Buildings to Provide Demand Response

Abstract Transactive control is a new type of distributed control strategy that is designed to engage various self-interested distributed energy resources such as controllable loads, distributed generators, and energy storage for providing demand response. In this paper, a novel transactive control design is proposed for commercial buildings to coordinate the electricity demand of the package rooftop air conditioning units (RTUs) for demand response. Such a control is realized by introducing a local relationship between the temperature setpoint and the market clearing price. With the proposed market-based control, the demand of individual RTUs is adjusted by changing their temperature setpoints in response to the market clearing price. Two different scenarios of demand response are considered herein. One is to limit the peak demand of commercial buildings, in which a new market clearing strategy based on proportional-integral-derivative control with respect to the demand limit is proposed. The other one is to perform price responsive control, in which the total demand of commercial buildings responds to the real-time pricing. The proposed transactive strategy is also tested and demonstrated on a real occupied building located in the eastern Washington State, U.S. The field testing results confirm the effectiveness of the proposed transactive control for commercial building with RTUs to provide demand response.

Fuzzy logic-based bidding strategies in dynamic double auctions

PurposeDouble auctions are widely used market mechanisms on the world. Communication technologies such as internet increased importance of this market institution. The purpose of this study is to develop novel bidding strategies for dynamic double auction markets, explain price formation through interactions of buyers and sellers in decentralized fashion and compare macro market outputs of different micro bidding strategies.Design/methodology/approachIn this study, two novel bidding strategies based on fuzzy logic are presented. Also, four new bidding strategies based on price targeting are introduced for the aim of comparison. The proposed bidding strategies are based on agent-based computational economics approach. The authors performed multi-agent simulations of double auction market for each suggested bidding strategy. For the aim of comparison, the zero intelligence strategy is also used in the simulation study. Various market outputs are obtained from these simulations. These outputs are market efficiencies, price means, price standard deviations, profits of sellers and buyers, transaction quantities, profit dispersions and Smith’s alpha statistics. All outputs are also compared to each other using t-tests and kernel density plots.FindingsThe results show that fuzzy logic-based bidding strategies are superior to price targeting strategies and the zero intelligence strategy. The authors also find that only small number of inputs such as the best bid, the best ask, reference price and trader valuations are sufficient to take right action and to attain higher efficiency in a fuzzy logic-based bidding strategy.Originality/valueThis paper presents novel bidding strategies for dynamic double auction markets. New bidding strategies based on fuzzy logic inference systems are developed, and their superior performances are shown. These strategies can be easily used in market-based control and automated bidding systems.

Three-Phase Optimal Power Flow for Market-Based Control and Optimization of Distributed Generations

The ever-increasing penetration of distributed generation in recent years brings challenges as well as opportunities for distribution companies as the smart grid paradigm evolves. A new three-phase unbalanced optimal power flow algorithm is developed for steady state system analysis to minimize the cost of serving loads in a distribution network. The algorithm is developed based on primal-dual interior point method. Comprehensive system components and constraints are modeled in a generalized fashion. In tests performed on the IEEE test feeder systems, the proposed algorithm is able to solve for optimal solutions under various system conditions and constraints. The potential applications of the program for distribution system design, reconfiguration, and control are also highlighted.

Synthesis of an intelligent rural village microgrid control strategy based on smartgrid multi-agent modelling and transactive energy management principles

Humanitarian and other development organisations are calling for replicable self-sustaining solutions to shared micro-utilities to ensure equitable modern energy delivery to energy-deprived village communities. Distributed smart microgrid technology allows for the efficient integration of sustainable resources to provide localised energy delivery at improved levels of reliability and resilience. Smart energy management in decentralised renewable systems requires computational intelligence to implement pivotal energy-aware/cost-aware procedures in decision-making for a conceptualised next generation Smart Village microgrid platform. Smart Village microgrid control automation aims at offering pragmatic and, intelligent control capabilities to perform price-based demand response energy management. This paper proposes the use of cascaded control abstraction in the implementation of a price-sensitive cyber-physical Smart Grid approach in a rural off-grid microgrid environment. The modular microgrid design integrates renewable energy resources through an adaptive control algorithm developed in a model-based design approach. The solution is based on distributed market-based control, using multi-agent transactive principles to navigate automated demand response. Multi-priority load clusters with the selective parallel control of non-intelligent device groups allow for prioritised supply/demand resource coordination. The proposed Smart Village solution operates as a self-regulating smart microgrid energy management system and by virtue of its market-based transactive reasoning approach is able to meet multiple operating requirements of rural village energy systems. Simulation results for this value-based control technique highlight the value of customer engagement combined with supply-, demand- and economic cost optimisation for hybrid renewable distributed energy microgrids.

Deep Koopman Controller Synthesis for Cyber-Resilient Market-Based Frequency Regulation

Abstract This paper investigates a data-driven countermeasure for price spoofing in the context of cyber security and market-based frequency regulation. Market-based control of transmission power networks relies on cyber-physical infrastructure, which raises questions of system vulnerability in relation to cyber-security. In this paper, we consider the challenge of engineering a robust data-driven controller in the presence of price spoofing, i.e. where hacking mechanisms adjust price signals in an ex-post market. We extend a recently developed algorithm called deep dynamic mode decomposition to learn Koopman operators of nonlinear systems with affine inputs. Based on the learned input-Koopman operator model, a design algorithm for nonlinear controller synthesis is devised to compute optimal dynamic pricing policies that restore the nominal frequency and recover economic efficiency in the presence of price spoofing. The efficacy of the proposed data-driven Koopman controller synthesis approach is validated through tests on a IEEE 39-bus benchmark.

Market-based control strategy for long-span structures considering the multi-time delay issue

To solve the different time delays that exist in the control device installed on spatial structures, in this study, discrete analysis using a 2N precise algorithm was selected to solve the multi-time-delay issue for long-span structures based on the market-based control (MBC) method. The concept of interval mixed energy was introduced from computational structural mechanics and optimal control research areas, and it translates the design of the MBC multi-time-delay controller into a solution for the segment matrix. This approach transforms the serial algorithm in time to parallel computing in space, greatly improving the solving efficiency and numerical stability. The designed controller is able to consider the issue of time delay with a linear controlling force combination and is especially effective for large time-delay conditions. A numerical example of a long-span structure was selected to demonstrate the effectiveness of the presented controller, and the time delay was found to have a significant impact on the results.

Preventing Distribution Grid Congestion by Integrating Indirect Control in a Hierarchical Electric Vehicles’ Management System

In this paper, a hierarchical management system is proposed to integrate electric vehicles (EVs) into a distribution grid. Three types of actors are included in the system: distribution system operators (DSOs), fleet operators (FOs), and EV owners. In contrast to a typical hierarchical control system where the upper level controller directly controls the lower level subordinated nodes, this study aims to integrate two common indirect control methods: market-based control and price-based control into the hierarchical EVs’ management system. Specifically, on the lower level of the hierarchy, the FOs coordinate the charging behaviors of their EV users using a price-based control method. A parametric utility model is used on the lower level to characterize price elasticity of EVs and thus used by the FO to coordinate the individual EV charging. On the upper level of the hierarchy, the DSO uses the market-based control strategy to coordinate the limited power capacity of power transformer with FOs. To facilitate the application of the two indirect control methods into the system, a model describing decision tasks in control is used to specify the essential functions that are needed in the control system. The simulations illustrate the effectiveness of the proposed solutions.

Robust market-based control method for nonlinear structure

For a nonlinear control system, there are many uncertainties, such as the structural model, controlled parameters and external loads. Although the significant progress has been achieved on the robust control of nonlinear systems through some researches on this issue, there are still some limitations, for instance, the complicated solving process, weak conservatism of system, involuted structures and high order of controllers. In this study, the computational structural mechanics and optimal control theory are adopted to address above problems. The induced norm is the eigenvalue problem in structural mechanics, i.e., the elastic stable Euler critical force or eigenfrequency of structural system. The segment mixed energy is introduced with a precise integration and an extended Wittrick-Williams (W-W) induced norm calculation method. This is then incorporated in the market-based control (MBC) theory and combined with the force analogy method (FAM) to solve the MBC robust strategy (R-MBC) of nonlinear systems. Finally, a single-degree-of-freedom (SDOF) system and a 9-stories steel frame structure are analyzed. The results are compared with those calculated by the <TEX>$H{\infty}$</TEX>-robust (R-<TEX>$H{\infty}$</TEX>) algorithm, and show the induced norm leads to the infinite control output as soon as it reaches the critical value. The R-MBC strategy has a better control effect than the R-<TEX>$H{\infty}$</TEX> algorithm and has the advantage of strong strain capacity and short online computation time. Thus, it can be applied to large complex structures.

Market-Based Multi-Agent Coordination to Manage Energy Balance in Smart Grids

Widespread adoption of sustainable energy sources is driving electricity grid operators to supplement hierarchical control regimes with market-based control that better motivates stakeholder involvement. However, to prevent market failures, such controls require testing before real-world implementation. The Power Trading Agent Competition is a competitive simulation of distribution grids that mirrors real-world scenarios and tests alternative policy and business scenarios. In Power TAC, broker agents acquire energy through bidding in a forward wholesale market to satisfy their customers’ overall demand on an hourly basis. In addition, a balancing market is intended to resolve real-time energy imbalances caused by broker prediction errors using demand response resources. As part of the annual alignment process, we discovered that brokers in the 2015 competition were persistently buying insufficient energy on the wholesale market to satisfy their customer demand. Instead, the balancing market made up the deficit, charging brokers a premium over the wholesale price. Also, demand response resources were heavily underused. We studied the economic impact of this systematic imbalance on brokers and discovered that they were behaving rationally, given the prices they faced in the two markets. We present the process and results of this analysis, and show how the balancing market’s pricing mechanism can be adjusted for the 2016 competition to make it rational for brokers to achieve an overall neutral imbalance.

Sustainable Coffee Marketing:Challenges and the Way Forward

This paper analyzed markets for sustainable coffee by taking into account five individual sustainable coffee initiatives, that is, 4C (Common Codes for Coffee Community), Utz, Rainforest Alliance (RFA), Fair-trade Labeling Organization (FLO), and Organic coffee. The sustainable coffee production experienced a phenomenal growth over the past decade. However, the volumes of sales represent only a minor portion of production. Less than 25% of sustainable coffee produced was 'actually sold' as sustainable, while the remaining was just sold as 'ordinary' conventional coffee, without receiving any extra market benefits. Among the individual coffee certification initiatives, 4C (Common Codes for Coffee Community) signaled a more serious over-supply in the global market, wherein only 6% of its overall sustainable production was actually sold as sustainable over 2008-12. During the same period, Utz coffee certification could sell 25%, Rainforest Alliance (RFA) could trade 50%, and organic certified coffee could sell 55% of its standard-compliant production as sustainable. The study revealed that global sustainable coffee market is characterized by massive 'over-supply'; demand being a major constraint. Underpinning this issue is the need for sustainable coffee market. The current market challenge is to stabilize mismatch between demand and supply for sustainable coffee. From a sustainable development perspective, this remains a serious matter of concern for policy makers, public institutions, and multi-stakeholders to engage in market-based control mechanism in constructing effective 'supply- management base' as a strategy for price-stabilization and to enhance further sustainable growth. At a micro level in India, coffee certification is still at an infancy stage, contributing to just 2% of total global sustainable production. The Indian Coffee Board and apex coffee organizations need to work in this direction to encourage both sustainable production and marketing, so as to assist growers in assessing preferential market benefits, besides supporting high quality 'Indian coffee' being traded at both the global and domestic levels.

Combining Market-Based Control with Distribution Grid Constraints when Coordinating Electric Vehicle Charging

ABSTRACT The charging of electric vehicles (EVs) impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based control algorithm to coordinate the charging of these vehicles, in order to minimize the costs. In such an optimization, the operational parameters of the distribution grid, to which the EVs are connected, are not considered. This can lead to violations of the technical constraints of the grid (e.g., under-voltage, phase unbalances); for example, because many vehicles start charging simultaneously when the price is low. An optimization that simultaneously takes the economic and technical aspects into account is complex, because it has to combine time-driven control at the market level with event-driven control at the operational level. Different case studies investigate under which circumstances the market-based control, which coordinates EV charging, conflicts with the operational constraints of the distribution grid. Especially in weak grids, phase unbalance and voltage issues arise with a high share of EVs. A low-level voltage droop controller at the charging point of the EV can be used to avoid many grid constraint violations, by reducing the charge power if the local voltage is too low. While this action implies a deviation from the cost-optimal operating point, it is shown that this has a very limited impact on the business case of an aggregator, and is able to comply with the technical distribution grid constraints, even in weak distribution grids with many EVs.

A Method for Analyzing Pollution Control Policies: Application To SO&lt;sub&gt;2&lt;/sub&gt; Emissions in China

Market-based pollution control mechanisms such as pollution levy and cap and trade have received increasing attention from both academics and practitioners. A good understanding of the optimal pollution price under these mechanisms is a premise for regulators to make sound pollution control policies. In this paper, we propose a method for deriving the optimal pollution price for a given pollution target. This method consists of two steps that integrate cost function estimation and market equilibrium analysis: First, historical data is used to estimate the pollution abatement cost functions of the polluters; second, market models are used to solve the equilibrium pollution price under each control mechanism. For illustration, we apply the method to investigate SO2 emission control policies in China, using a dataset of SO2 emissions and abatement costs from three major industry sectors (Electricity, Gas, and Water Supply; Manufacturing; and Mining). Our analysis shows that the optimal levy rate is significantly higher than the actual rate adopted by the Chinese government. For example, the optimal levy rate should be 4.92 RMB/kg, while the actual rate is 1.26 RMB/kg in 2010. As a result, the actual emission structure is much less efficient: The overall cost savings would be 49.7% for all three sectors during 2006-2010 if the optimal emission structure is achieved. These findings have useful policy implications for the Chinese government. In addition, the method may be applied to analyze control policies at different aggregate levels (for example, provincial economies) or for other pollutants (for example, CO2 and chemical oxygen demand).

Tying It All Together: The Potential of Legal, Social and Market-Based Control Mechanisms to Enforce Integrated and Sustainable Decision-Making

Integrated and sustainable decision-making, which requires directors of corporations to take into account environmental, social and economic issues into their decision process, is the “keystone” of the legal principles of corporate social responsibility. A voluntary form of the principle of integrated and sustainable decision-making is part of Canadian corporate law since the enlargement of corporate directors’ duties of loyalty in the BCE decision. Although socio-legal literature has shown that voluntary principles may have a real regulatory impact, the effectiveness of a voluntary principle of integrated decision-making in furthering social and economic issues has still not been assessed. This article will argue that in order to determine the potential of integrated decision-making in ensuring greater corporate social responsibility, it is necessary to study the legal, social and market-based control mechanisms by which integrated decision-making is implemented. To what extent do these control mechanisms enforce the principle of integrated decision-making, given the unequal access of stakeholders to these control mechanisms and the competing norms of shareholder primacy and share value maximization they carry? We find that while each of the regulatory mechanisms could be used to implement the principle of integrated decision-making, no mechanism alone is sufficient to ensure that social responsibility will trump financial considerations if a choice has to be made. The analysis concludes on the regulatory courses of action that could be taken to strengthen the principle of sustainable and integrated decision-making.