Decision Support System for the Negotiation of Bilateral Contracts in Electricity Markets (original) (raw)

2017, Advances in Intelligent Systems and Computing

https://doi.org/10.1007/978-3-319-61578-3_44

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Abstract

Currently, it is possible to find various tools to deal with the unpredictability of electricity markets. However, they mainly focus on spot markets, disfavouring bilateral negotiations. A multi-agent decision support tool is proposed that addresses the identified gap, supporting players in the pre-negotiation and actual negotiation phases.

Negotiation context analysis in electricity markets

Energy, 2015

Contextualization is critical in every decision making process. Adequate responses to problems depend not only on the variables with direct influence on the outcomes, but also on a correct contextualization of the problem regarding the surrounding environment. Electricity markets are dynamic environments with increasing complexity, potentiated by the last decades' restructuring process. Dealing with the growing complexity and competitiveness in this sector brought the need for using decision support tools. A solid example is MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), whose players' decisions are supported by another multiagent system e ALBidS (Adaptive Learning strategic Bidding System). ALBidS uses artificial intelligence techniques to endow market players with adaptive learning capabilities that allow them to achieve the best possible results in market negotiations. This paper studies the influence of context awareness in the decision making process of agents acting in electricity markets. A context analysis mechanism is proposed, considering important characteristics of each negotiation period, so that negotiating agents can adapt their acting strategies to different contexts. The main conclusion is that context-dependant responses improve the decision making process. Suiting actions to different contexts allows adapting the behaviour of negotiating entities to different circumstances, resulting in profitable outcomes.

Electronic Trading on Electricity Markets within a Multi-agent Framework

2009

Specific features of trade on electrical energy markets make the automation of certain negotiation and contracting processes attractive and desirable. Multi-agent systems are a natural solution for automating processes in a distributed environment, where individual market entities posses their own objectives. In the paper we consider a concept of a multi-agent framework for an electronic market trade. Since both energy markets and trade mechanisms are complex and permanently evolving, we require the highest expressiveness from this concept. Development of such a system involves solving several design issues related to embedding the agents in the environment, agent communications schemas, language, and offers modeling, especially in the case of the distributed, multilateral trade. We present a solution for the most important design issues. Our concept, including new information technologies supplementing multi-agent systems and Web services, are capable to support enterprises in the decision processes, to facilitate the buy/sell offers preparation, to select parties and enter into business relations with entities, and to support contract negotiations.

Multiagent negotiation models for power system applications

2003

There are a wide range of power system decision problems, traditionally falling under one of the three categories of operations, maintenance, and planning, with the delineation between categories derived from the nature of the decision and the time horizon.

A Multi-Agent System Performing One-to-Many Negotiation

2003

Emerging technologies allowing two-way communication between utility companies and their customers are changing the rules of the energy market. Deregulation makes it even more demanding for utility companies to create new business processes for the mutual benefit of the companies and their customers. Dynamic load management of the power grid is essential to make better and more cost-effective use of electricity production capabilities, and to increase customer satisfaction. In this paper, methods from Agent Technology and Knowledge Technology have been used to analyse, design, and implement a component-based multi-agent system capable of negotiation for load management. The proof-of-concept prototype system NALM (Negotiating Agents for Load Management) developed shows how under certain assumptions peaks in power load can be reduced effectively based on a negotiation process.

A new approach for multi-agent coalition formation and management in the scope of electricity markets

Fuel and Energy Abstracts, 2011

This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself.

Negotiation Models for the European Energy Market – Heletel Fast Prototype

Procedia - Social and Behavioral Sciences, 2014

For the purpose of the EU-DEEP project, a European co-funded project, which focuses on the European Energy market, a prototype was studied and developed for the management of resources that is based on transaction techniques. That is to say, the prototype examines all the possible cases and in order to make the decision, for the energy management system, which generator to use at a particular time depending from the result of negotiation with market terms using agent technologies between the energy managing system and the participating generator. The purpose of this study was to investigate the models of negotiation, the Software Agents with platforms as the JADE, as well as the requirements of the system and to develop a prototype and evaluate it.

Negotiating the Selling Price of Hydropower Energy Using Multi-Agent Systems in Bot

Journal of Civil Engineering and Management, 2019

During the feasibility study of BOT (Build-Operate-Transfer) hydropower investments, the selling price of energy is the most critical parameter that impacts the net present value (NPV) estimated by the investors. Investors usually consider the price of energy guaranteed by the government during their feasibility studies which is the worst case scenario. However, it is apparent that negotiations that take place between investor and broker determine the price of energy which is affected by various sources of uncertainty associated with the energy demand and country conditions. The objective of this study was to make a realistic estimate of the investor's selling price by modeling the negotiation process between investor and broker using a multi-agent system (MAS). Thus, the factors affecting the negotiation process were identified, a negotiation protocol between the parties was set up, negotiation scenarios were determined, and modelled by using a MAS. The model was tested on a hydropower investment in Turkey and generated more realistic results compared to the current practice. Investors and brokers may benefit from this study because it considers the potential changes in the market as well as the negotiating postures of parties under different scenarios.

A multi-agent system performing one-to-many negotiation for load balancing of electricity use

Electronic Commerce …, 2002

Emerging technologies allowing two-way communication between utility companies and their customers are changing the rules of the energy market. Deregulation makes it even more demanding for utility companies to create new business processes for the mutual benefit of the companies and their customers. Dynamic load management of the power grid is essential to make better and more cost-effective use of electricity production capabilities, and to increase customer satisfaction. In this paper, methods from Agent Technology and Knowledge Technology have been used to analyse, design, and implement a component-based multi-agent system capable of negotiation for load management. The proof-of-concept prototype system NALM (Negotiating Agents for Load Management) developed shows how under certain assumptions peaks in power load can be reduced effectively based on a negotiation process.

Developing Agents for Electricity Trade Markets

IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications (DIS'06), 2006

Electricity trade will eventually evolve into some type of an electronic commerce structure, facilitated by a group of collaborative software agents that work according to standard regulations and strict operational and security constraints. This paper presents developing agents for electricity trade markets. We follow a standard agent design requirements and standard agent communication protocols. The results of the test case show that agents facilitate electronic trade and drive the market price closer to the marginal cost of generation supply and far away from the estimated Cournot price.

Strategic bidding in electricity markets: An agent-based simulator with game theory for scenario analysis

2013

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players' actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Market are presented and discussed.

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References (3)

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Decision-support tool for the establishment of contracts in the electricity market

2003

The Pool, in many countries, was adopted for the participants of the electricity market to trade the electrical energy in a basis of each half-hour or one hour of the next day. However, like the traditional markets, the agents of electrical market are now exposed to the volatility of market price. In some countries, to face that problem and to turn the market more liquid, the derivatives markets - futures and options - were introduced to negotiate products with electrical energy as underlying active. In this context, there is a need of decision-support tools to assist those agents for the use of derivatives markets with the objective of practicing the hedge. In this paper, we present a decision model that supports producers to establish contracts with the objective to maximize the profit expected utility.

Decision Support for Negotiations among Microgrids Using a Multiagent Architecture

Energies, 2018

This paper presents a decision support model for negotiation portfolio optimization considering the participation of players in local markets (at the microgrid level) and in external markets, namely in regional markets, wholesale negotiations and negotiations of bilateral agreements. A local internal market model for microgrids is defined, and the connection between interconnected microgrids is based on nodal pricing to enable negotiations between nearby microgrids. The market environment considering the local market setting and the interaction between integrated microgrids is modeled using a multi-agent approach. Several multi-agent systems are used to model the electricity market environment, the interaction between small players at a microgrid scale, and to accommodate the decision support features. The integration of the proposed models in this multi-agent society and interaction between these distinct specific multi-agent systems enables modeling the system as a whole and thus ...

Automated combination of bilateral energy contracts negotiation tactics

2018 IEEE Power & Energy Society General Meeting (PESGM), 2018

This paper addresses the theme automated bilateral negotiation of energy contracts. In this work, the automatic combination between different negotiation tactics is proposed. This combination is done dynamically throughout the negotiation process, as result from the online assessment that is performed after each proposal and counter-proposal. The proposed method is integrated in a decision support system for bilateral negotiations, called Decision Support for Energy Contracts Negotiations (DECON), which in turn is integrated with the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM). This integration enables testing and validating the proposed methodology in a realistic market negotiation environment. A case study is presented, demonstrating the advantages of the proposed approach.

Multi-agent Simulation of Bilateral Contracting in Competitive Electricity Markets

2014 25th International Workshop on Database and Expert Systems Applications, 2014

Traditional vertically integrated power utilities around the world have evolved from monopoly structures to open markets that promote competition among suppliers and provide consumers with a choice of services. Market forces drive the price of electricity and reduce the net cost through increased competition. Electricity can be traded in both organized markets or using forward bilateral contracts. This article focuses on bilateral contracts and describes some important features of an agent-based system for bilateral trading in competitive markets. Special attention is devoted to the negotiation process, demand response in bilateral contracting, and risk management. The article also presents a case study on forward bilateral contracting: a retailer agent and a customer agent negotiate a 24h-rate tariff.

An intelligent negotiator agent design for bilateral contracts of electrical energy

Expert Systems with Applications, 2014

In this paper, an intelligent agent (using the Fuzzy SARSA learning approach) is proposed to negotiate for bilateral contracts (BC) of electrical energy in Block Forward Markets (BFM or similar market environments). In the BFM energy markets, the buyers (or loads) and the sellers (or generators) submit their bids and offers on a daily basis. The loads and generators could employ intelligent software agents to trade energy in BC markets on their behalves. Since each agent attempts to choose the best bid/offer in the market, conflict of interests might happen. In this work, the trading of energy in BC markets is modeled and solved using Game Theory and Reinforcement Learning (RL) approaches. The Stackelberg equation concept is used for the match making among load and generator agents. Then to overcome the negotiation limited time problems (it is assumed that a limited time is given to each generator-load pairs to negotiate and make an agreement), a Fuzzy SARSA Learning (FSL) method is used. The fuzzy feature of FSL helps the agent cope with continuous characteristics of the environment and also prevents it from the curse of dimensionality. The performance of the FSL (compared to other well-known traditional negotiation techniques, such as time-dependent and imitative techniques) is illustrated through simulation studies. The case study simulation results show that the FSL based agent could achieve more profits compared to the agents using other reviewed techniques in the BC energy market.

Application of Multi-Agent Systems in Electricity Market Simulators

Journal of Energy - Energija

Since the liberalization and deregulation of the electricity markets throughout the world are in full swing, the number of market participants, as well as their diversity, is sharply increasing. In the traditional monopolistic market model, all the processes that occur in a power system have been supervised by vertically integrated companies. Since market logic is changing from that oriented toward minimizing generation costs for electrical energy to the trend of maximizing profit, the risk is being distributed among all the market participants uniformly and is no longer entirely borne by the final consumers. Under such uncertain conditions, in which the prices of electrical energy change from hour to hour, each market participant wants a reliable tool to facilitate optimal and quality decisions and strategic performance.

Decision Support for Small Players Negotiations Under a Transactive Energy Framework

IEEE Transactions on Power Systems, 2018

This paper proposes a decision support model to optimize small players' negotiations in multiple alternative/complementary market opportunities. The proposed model endows players with the ability to maximize their gains in electricity market negotiations. The proposed approach is integrated in a multi-agent simulation platform, which enables experimenting different market configurations, thus facilitating the assessment of the impact of negotiation outcomes in distinct electricity markets. The proposed model is directed to supporting the actions of small players in a transactive energy environment. Therefore, the experimental findings include negotiations in local markets, negotiations through bilateral contracts, and the participation in wholesale markets (through aggregators). The validation is performed using real data from the Iberian market, and results show that by planning market actions considering the expected prices in different market opportunities, small players are able to improve their benefits from market negotiations.

Raiffa-Kalai-Smorodinsky Bargaining Solution for Bilateral Contracts in Electricity Markets

Energies

In electricity markets, bilateral contracts (BC) are used to hedge against price volatility in the spot market. Pricing these contracts requires scheduling from either the buyer or the seller aiming to achieve the highest profit possible. Since this problem includes different players, a Generation Company (GC) and an Electricity Supplier Company (ESC) are considered. The approaches to solve this problem include the Nash Bargaining Solution (NBS) equilibrium and the Raiffa–Kalai–Smorodinsky (RKS) bargaining solution. The innovation of this work is the implementation of an algorithm based on the RKS equilibrium to find a compromise strategy when determining the concessions to be made by the parties. The results are promising and show that the RKS approach can obtain better results compared to the Nash equilibrium method applied to a case study.

Agents Negotiating for Load Balancing of Electricity Use

1998

Emerging technologies allowing two-way communication between utility companies and their customers, as well as with smart equipment, are changing the rules of the energy market. Deregulation makes it even more demanding for utility companies to create new business processes for mutual benefit. Dynamic load management of the power grid is essential to make better and more cost-effective use of electricity production capabilities, and to increase customer satisfaction. The compositional development method DESIRE has been used to analyse, design, implement and verify a multi-agent system capable of negotiation for load management.