Consensus-based approach to peer-to-peer electricity markets with product differentiation

With the sustained deployment of distributed generation capacities and the more proactive role of consumers, power systems and their operation are drifting away from a conventional top-down hierarchical structure. Electricity market structures, however, have not yet embraced that evolution. Respecting the high-dimensional, distributed and dynamic nature of modern power systems would translate to designing peer-to-peer markets or, at least, to using such an underlying decentralized structure to enable a bottom-up approach to future electricity markets. A peer-to-peer market structure based on a Multi-Bilateral Economic Dispatch (MBED) formulation is introduced, allowing for multi-bilateral trading with product differentiation, for instance based on consumer preferences. A Relaxed Consensus+Innovation (RCI) approach is described to solve the MBED in fully decentralized manner. A set of realistic case studies and their analysis allow us showing that such peer-to-peer market structures can effectively yield market outcomes that are different from centralized market structures and optimal in terms of respecting consumers preferences while maximizing social welfare. Additionally, the RCI solving approach allows for a fully decentralized market clearing which converges with a negligible optimality gap, with a limited amount of information being shared.Comment: Accepted for publication in IEEE Transactions on Power System

Exogenous Cost Allocation in Peer-to-Peer Electricity Markets

International audienceThe deployment of distributed energy resources, combined with a more proactive demand side management, is inducing a new paradigm in power system operation and electricity markets. Within a consumer-centric market framework, peer-to-peer approaches have gained substantial interest. Peer-to-peer markets rely on multi-bilateral negotiation among all agents to match supply and demand. These markets can yield a complete mapping of exchanges onto the grid, hence allowing to rethink the sharing of costs related to the use of common infrastructure and services. We propose here to attribute such costs through exogenous network charges in several alternative ways i.e. uniformly, based on the electrical distance between agents and by zones. This variety covers the main grid physical and regulatory configurations. Since attribution mechanisms are defined in an exogenous manner to affect each P2P trade, they eventually shift the market issue to cover the grid exploitation costs. It can even be used to release the stress on the grid when necessary. The interest of our approach is illustrated on a test case using the IEEE 39 bus test system, underlying the impact of attribution mechanisms on trades and grid usage

Procurement Auctions and Negotiations: An Empirical Comparison

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of Organizational Computing and Electronic Commerce on Aug. 2, 2017, available online: http://www.tandfonline.com/10.1080/10919392.2017.1363576.Real world procurement transactions often involve multiple attributes and multiple vendors. Successful procurement involves vendor selection through appropriate market mechanisms. The advancement of information technologies has enabled different mechanisms to be applied to similar procurement situations. Advantages and disadvantages of using such mechanisms remain unclear. The presented research compares two types of mechanisms: multi-attribute reverse auctions and multi-attribute multi-bilateral negotiations in e-procurement. Both laboratory and online experiments were carried out to examine their effects on the process, outcomes and suppliers’ assessment. The results show that in procurement, reverse auctions were more efficient than negotiations in terms of the process. Auctions also led to greater gains for the buyers than negotiations but the suppliers’ profit was lower in auctions. The buyer and the winning supplier jointly reached more efficient and balanced contracts in negotiations than in auctions. The results also show that the suppliers’ assessment was affected by their outcomes: the winning suppliers had a more positive assessment towards the process, outcomes and the system. The findings are consistent in both the laboratory and online settings. The implications of this study for practitioners and researchers are discussed

Human-Agent Negotiations: The Impact Agents’ Concession Schedule and Task Complexity on Agreements

Employment of software agents for conducting negotiations with online customers promises to increase the flexibility and reach of the exchange mechanism and reduce transaction costs. Past research had suggested different negotiation tactics for the agents, and had used them in experimental settings against human negotiators. This work explores the interaction between negotiation strategies and the complexity of the negotiation task as represented by the number of negotiation issues. Including more issues in a negotiation potentially allows the parties more space to maneuver and, thus, promises higher likelihood of agreement. In practice, the consideration of more issues requires higher cognitive effort, which could have a negative effect on reaching an agreement. The results of human–agent negotiation experiments conducted at a major Canadian university revealed that there is an interaction between chosen strategy and task complexity. Also, when competitive strategy was employed, the agents\u27 utility was the highest. Because competitive strategy resulted in fewer agreements the average utility per agent was the highest in the compromising–competitive strategy

Negotiation or Auction? The NorA project

Negotiation or Auction? The NorA projec

Three Studies on Multi-attribute Market Mechanisms in E-procurement

Successful e-procurement depends on selecting the appropriate mechanisms that comprise rules governing and facilitating transaction process. Existing mechanisms have theoretical or practical limitations such as limited number of attributes, disclosure of buyer’s preferences and costly processes. The present research addresses these issues through three studies. Study 1 presents two feasible mechanisms for multi-attribute multi-supplier transactions. They allow buyers to control preference representation and information revelation, assuring that suppliers obtain sufficient information in making effective proposals while protecting confidential information. Following the design-science approach, the mechanisms are implemented to support multi-attribute reverse auctions and multi-bilateral negotiations. Study 2 examines the revelation of information in multi-attribute reverse auctions. Three revelation rules are formulated with admissible bids, winning bids and all bidders’ bids. Their effects on the process, outcomes and bidders’ assessment are tested in two experiments. The results show significant improvement in process efficiency when more information is revealed. The suppliers reached better outcomes with either admissible bids only or all bidders’ bids, while the buyers gained more when revealing the winning bids only. Bidders were more satisfied with the outcomes and system when more information was provided. Study 3 compares multi-attribute reverse auctions and multi-bilateral negotiations in both laboratory and online experiments. The results show that auctions are more efficient than negotiations in terms of the process. Auctions led to greater gains for the buyers, whereas more balanced contracts were reached in negotiations. Suppliers’ assessment was affected by their outcomes, and the winning suppliers were more satisfied with the process, outcomes and system. The buyer’s role was also examined. Different types of information conveyed from buyer influence suppliers’ behavior in making bids/offers and concessions, which in turn affected buyer’s gains. This research provides implications to future studies and practices in e-procurement, in particular, the formulation of a procedure of two multi-attribute mechanisms and the formulation of general guidelines for strategic use of different mechanisms in various e-procurement contexts

Negotiation-Style Recommender Based on Computational Ecology in Open Negotiation Environments.

The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality, but with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems, as well as related services like open-id, trust management, monitors and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up Open Negotiation Environments that are stable, a basic condition for predictable business and reliable business environments. Aiming to build stable digital business ecosystems by means of improved collective intelligence, we introduce a model of negotiation style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor as well as a novel negotiation style recommender. The ecosystem monitor provides hints to the negotiation style recommender to achieve greater stability of an open negotiation environment in a digital business ecosystem. The greater stability provides the small companies with higher predictability, and therefore better business results. The negotiation style recommender is implemented with a simulated annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of an open negotiation environment populated by Italian companies.Fil: De La Rosa, Josep Lluis. Universidad de Girona; EspañaFil: Hormazábal, Nicolás. Universidad de Girona; EspañaFil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Lopardo, Gabriel Alejandro. Universidad de Girona; EspañaFil: Trias, Albert. Universidad de Girona; EspañaFil: Montaner, Miquel. No especifíca

Incorporating an Element of Negotiation into a Service-Oriented Broker Application

The Software as a Service (SaaS) model is a service-based model in which a desired service is assembled, delivered and consumed on demand. The IBHIS broker is a ‘proof of concept’ demonstration of SaaS which is based on services that deliver data. IBHIS has addressed a number of challenges for several aspects of servicebased software, especially the concept of a ‘broker service’ and service negotiation that is only used in establishing end-user access authorizations. This thesis investigates and develops an extended form of service-based broker, called CAPTAIN (Care Planning Through Auction-based Information Negotiation). It extends the concepts and role of the broker as used in IBHIS, and in particular, it extends the service negotiation function in order to demonstrate a full range of service characteristics. CAPTAIN uses the idea of the integrated care plan from healthcare to provide a case study. A care planner acting on behalf of a patient uses the broker to negotiate with providers to produce the integrated care plan for the patient with the broker and the providers agreeing on the terms and conditions relating to the supply of the services. We have developed a ‘proof of concept’ service-oriented broker architecture for CAPTAIN that includes planning, negotiation and service-based software models to provide a flexible care planning system. The CAPTAIN application has been evaluated that focuses on three features: functions, data access and negotiation. The CAPTAIN broker performs as planned, to produce the integrated care plan. The providers’ data sources are accessed to read and write data records during and after service negotiation. The negotiation model permits the broker to interact with the providers to produce an adaptable plan, based on the client’s needs. The primary outcome is an extendable service-oriented broker architecture that can enable more scalable and flexible distributed information management by adding interaction with the data sources

The effects of interplay between negotiation tactics and task complexity in software agent to human negotiations

Modern networked business environment enables design of flexible and effective mechanisms of exchange between economic parties. Online negotiations allow geographically and temporally separated participants to engage in exchange of offers in search for acceptable agreements. The digital medium enables development of software agents, which can assist with negotiation tasks while saving time and human effort. The current paper investigates the prospects of utilizing software agents in negotiations with the human counterparts. It presents the findings from experiment where human subjects acted as buyers negotiating with software agent sellers over a mobile phone plan. An electronic negotiation system incorporating software agents was used in the experiment. The agents employed various concession-making schedules while engaging in negotiation tasks involving one of two complexity levels. Negotiation task complexity was manipulated using different number of issues involved in the negotiations. Subjects were recruited among university students. Negotiations between the subjects and agents took place during a two-day period in an asynchronous mode through the web. The findings suggest that interaction between negotiation task complexity and negotiation tactic has significant effects on negotiation outcomes and subjective assessments by the human participants. In particular, task complexity had a higher impact on the agreement rate when agents employed a competitive tactic vs. when they used a conceding one

Local Energy Markets - Simulative Evaluation and Field Test Application of Energy Markets on Distribution Grid Level

Widespread introduction of Distributed Energy Resources (DERs) such as volatile renewable generation, electric vehicles, heat-pumps and battery storages causes a paradigm shift of the power system. Traditional power systems with few large-scale power plants are expanded or replaced by millions of small- to medium-size DERs. Local Energy Markets (LEMs) are a promising approach to facilitate the optimal operation and dispatch of DERs and enhance grid-integration on regional grid levels. In this Thesis, a novel linear-optimization-based market model for LEMs is developed. The market matching problem aims to maximize the social welfare of participants while considering technical and financial aspects of participants’ assets and the distribution grid. A simulative framework is set-up to evaluate the model with regards to its capabilities to foster the optimal use of flexibilities, to provide sufficient financial incentives for participants and to improve grid-integration. Yearly simulations of LEMs and a benchmark case are carried out for three different grid types (rural, semiurban, urban) and scenario years ranging from 2020 until 2035 in 5 year steps. The simulation results reveal that self-consumption and self-sufficiency of the local energy system can be increased by 4 ... 23 and 1 ... 9 percentage points depending on the grid type when compared to a business as usual benchmark case. An analysis of possible designs for regulated electricity price components in LEMs shows that a reduction of feed-in and load peaks of 30 ... 64 % can be achieved when considering power fees in the market matching problem. The simulative evaluation also shows that the market model is able to generate temporal, spatial, and asset-specific prices signals. Depending on the grid type and its load-generation ratio, participants with generation assets have higher benefits in urban, load-dominated grids whereas consumers have higher benefits in generation-dominated rural and semiurban grids. Load forecast uncertainty is identified as one of the major challenges in LEMs. Compared to simulations with perfect foresight, benefits of market participants are substantially decreased taking into account typical electric load forecast errors on the level of individual households. The application of the market model in a six months field-test in Southern Germany demonstrates the real world applicability of the developed approach. The field-test confirms findings from the simulative evaluation regarding the implication of forecast errors and generated price signals. It additionally shows that market interfaces to the Distribution System Operator (DSO) might further increase grid-integration capabilities of LEMs. By taking into account active power constraints of the DSO, 1499 events of critical grid load could be avoided