Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches

Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.Comment: 38 pages, single column, double spac

Monopolistic and game-based approaches to transact energy flexibility

The appearance of the flexible behavior of end-users based on demand response programs makes the power distribution grids more active. Thus, electricity market participants in the bottom layer of the power system, wish to be involved in the decision-making process related to local energy management problems, increasing the efficiency of the energy trade in distribution networks. This paper proposes monopolistic and game-based approaches for the management of energy flexibility through end-users, aggregators, and the Distribution System Operator (DSO) which are defined as agents in the power distribution system. Besides, a 33-bus distribution network is considered to evaluate the performance of our proposed approaches for energy flexibility management model based on impact of flexibility behaviors of end-users and aggregators in the distribution network. According to the simulation results, it is concluded that although the monopolistic approach could be profitable for all agents in the distribution network, the game-based approach is not profitable for end-users.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

A Typology for Characterizing Human Action in MultiSector Dynamics Models

The role of individual and collective human action is increasingly recognized as a prominent and arguably paramount determinant in shaping the behavior, trajectory, and vulnerability of multisector systems. This human influence operates at multiple scales: from short-term (hourly to daily) to long-term (annually to centennial) timescales, and from the local to the global, pushing systems toward either desirable or undesirable outcomes. However, the effort to represent human systems in multisector models has been fragmented across philosophical, methodological, and disciplinary lines. To cohere insights across diverse modeling approaches, we present a new typology for classifying how human actors are represented in the broad suite of coupled human-natural system models that are applied in MultiSector Dynamics (MSD) research. The typology conceptualizes a “sector” as a system-of-systems that includes a diverse group of human actors, defined across individual to collective social levels, involved in governing, provisioning, and utilizing products, goods, or services toward some human end. We trace the salient features of modeled representations of human systems by organizing the typology around two key questions: (a) Who are the actors in MSD systems and what are their actions? (b) How and for what purpose are these actors and actions operationalized in a computational model? We use this typology to critically examine existing models and chart the frontier of human systems modeling for MSD research

An integrated approach to value chain analysis of end of life aircraft treatment

Dans cette thèse, on propose une approche holistique pour l’analyse, la modélisation et l’optimisation des performances de la chaîne de valeur pour le traitement des avions en fin de vie (FdV). Les recherches réalisées ont débouché sur onze importantes contributions. Dans la première contribution, on traite du contexte, de la complexité, de la diversité et des défis du recyclage d’avions en FdV. La seconde contribution traite du problème de la prédiction du nombre de retraits d’avions et propose une approche intégrée pour l’estimation de ce nombre de retraits. Le troisième et le quatrième articles visent à identifier les parties prenantes, les valeurs perçues par chaque partenaire et indiquent comment cette valeur peut affecter les décisions au stade de la conception. Les considérations relatives à la conception et à la fabrication ont donné lieu à quatre contributions importantes. La cinquième contribution traite des défis et opportunités pouvant résulter de l’application des concepts de la chaîne logistique verte, pour les manufacturiers d’avions. Dans la sixième contribution, un outil d’aide à la décision a été développé pour choisir la stratégie verte qui optimise les performances globales de de toute la chaîne de valeur en tenant compte des priorités et contraintes de chaque partenaire. Dans la septième contribution, un modèle mathématique est proposé pour analyser le choix stratégique des manufacturiers en réponse aux directives en matière de FdV de produits comme le résultat des interactions des compétiteurs dans le marché. La huitième contribution porte sur les travaux réalisés dans le cadre d’un stage chez le constructeur d’avions, Bombardier. Cette dernière traite de l’apport de « l’analyse du cycle de vie » au stade de la conception d’avions. La neuvième contribution introduit une méthodologie d’analyse de la chaîne de valeur dans un contexte de développement durable. Finalement, les dixième et onzième contributions proposent une approche holistique pour le traitement des avions en FdV en intégrant les concepts du « lean », du développement durable et des contraintes et opportunités inhérentes à la mondialisation des affaires. Un modèle d’optimisation intégrant les modèles d’affaires, les stratégies de désassemblage et les structures du réseau qui influencent l’efficacité, la stabilité et l’agilité du réseau de récupération est proposé. Les données requises pour exploiter le modèle sont indiquées dans l’article. Mots-clés: Fin de vie des avions, analyse de la chaîne de valeurs, développement durable, intervenants.The number of aircrafts at the end of life (EOL) is continuously increasing. Dealing with retired aircrafts considering the environmental, social and economic impacts is becoming an emerging problem in the aviation industry in near future. This thesis seeks to develop a holistic approach in order to analyze the value chain of EOL aircraft treatment in the context of sustainable development. The performed researches have led to eleven main contributions. In the first contribution, the complexity and diversity of the EOL aircraft recycling including the challenges and problem context are discussed. The second contribution addresses the challenges for estimation of retired aircrafts and proposes an integrated approach for prediction of EOL aircrafts. The third and fourth contributions aim to identify the players involved in EOL recycling context, values perceived by different shareholders and formulate that how such value can affect design decisions. Design stage consideration and manufacture’s issues are discussed and have led to four main contributions. The fifth contribution addresses the opportunities and challenges of applying green supply chain for aircraft manufacturers. In the sixth contribution, a decision tool is developed to aid manufactures in early stage of design for their green strategy choices. In the seventh contribution, a mathematical model is developed in order to analyze the strategic choice of manufacturers in response to EOL directives as the result of the interaction of competitors in the market. An internship project has been also performed in Bombardier and led to the eighth contribution, which addresses life cycle approach and incorporating the sustainability in early stage of design of aircraft. The ninth contribution introduces a methodology for analyzing the value chain in the context of sustainable development. Finally, the tenth and eleventh contributions propose a holistic approach to EOL aircraft treatment considering lean principals, sustainable development, and global business environment. An optimization model is developed to support decision making in both strategic and managerial level. The analytical approaches, decision tools and step by step guidelines proposed in this thesis will aid decision makers to identify appropriate strategies for the EOL aircraft treatment in the sustainable development context. Keywords: End of life aircraft, value chain analysis, sustainable development, stakeholders

New actor types in electricity market simulation models: Deliverable D4.4

Project TradeRES - New Markets Design & Models for 100% Renewable Power Systems: https://traderes.eu/about/ABSTRACT: The modelling of agents in the simulation models and tools is of primary importance if the quality and the validity of the simulation outcomes are at stake. This is the first version of the report that deals with the representation of electricity market actors’ in the agent based models (ABMs) used in TradeRES project. With the AMIRIS, the EMLab-Generation (EMLab), the MASCEM and the RESTrade models being in the centre of the analysis, the subject matter of this report has been the identification of the actors’ characteristics that are already covered by the initial (with respect to the project) version of the models and the presentation of the foreseen modelling enhancements. For serving these goals, agent attributes and representation methods, as found in the literature of agent-driven models, are considered initially. The detailed review of such aspects offers the necessary background and supports the formation of a context that facilitates the mapping of actors’ characteristics to agent modelling approaches. Emphasis is given in several approaches and technics found in the literature for the development of a broader environment, on which part of the later analysis is deployed. Although the ABMs that are used in the project constitute an important part of the literature, they have not been included in the review since they are the subject of another section.N/

EmC-ICDSST 2019: 5th International Conference on Decision Support System Technology - ICDSST 2019 & EURO Mini Conference 2019 on "Decision Support Systems: Main Developments & Future Trends"

info:eu-repo/semantics/publishedVersio

An Investigation into Factors Affecting the Chilled Food Industry

With the advent of Industry 4.0, many new approaches towards process monitoring, benchmarking and traceability are becoming available, and these techniques have the potential to radically transform the agri-food sector. In particular, the chilled food supply chain (CFSC) contains a number of unique challenges by virtue of it being thought of as a temperature controlled supply chain. Therefore, once the key issues affecting the CFSC have been identified, algorithms can be proposed, which would allow realistic thresholds to be established for managing these problems on the micro, meso and macro scales. Hence, a study is required into factors affecting the CFSC within the scope of Industry 4.0. The study itself has been broken down into four main topics: identifying the key issues within the CFSC; implementing a philosophy of continuous improvement within the CFSC; identifying uncertainty within the CFSC; improving and measuring the performance of the supply chain. However, as a consequence of this study two further topics were added: a discussion of some of the issues surrounding information sharing between retailers and suppliers; some of the wider issues affecting food losses and wastage (FLW) on the micro, meso and macro scales. A hybrid algorithm is developed, which incorporates the analytic hierarchical process (AHP) for qualitative issues and data envelopment analysis (DEA) for quantitative issues. The hybrid algorithm itself is a development of the internal auditing algorithm proposed by Sueyoshi et al (2009), which in turn was developed following corporate scandals such as Tyco, Enron, and WorldCom, which have led to a decline in public trust. However, the advantage of the proposed solution is that all of the key issues within the CFSC identified can be managed from a single computer terminal, whilst the risk of food contamination such as the 2013 horsemeat scandal can be avoided via improved traceability

Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

Peer-to-Peer Energy Trading in Smart Residential Environment with User Behavioral Modeling

Electric power systems are transforming from a centralized unidirectional market to a decentralized open market. With this shift, the end-users have the possibility to actively participate in local energy exchanges, with or without the involvement of the main grid. Rapidly reducing prices for Renewable Energy Technologies (RETs), supported by their ease of installation and operation, with the facilitation of Electric Vehicles (EV) and Smart Grid (SG) technologies to make bidirectional flow of energy possible, has contributed to this changing landscape in the distribution side of the traditional power grid. Trading energy among users in a decentralized fashion has been referred to as Peer- to-Peer (P2P) Energy Trading, which has attracted significant attention from the research and industry communities in recent times. However, previous research has mostly focused on engineering aspects of P2P energy trading systems, often neglecting the central role of users in such systems. P2P trading mechanisms require active participation from users to decide factors such as selling prices, storing versus trading energy, and selection of energy sources among others. The complexity of these tasks, paired with the limited cognitive and time capabilities of human users, can result sub-optimal decisions or even abandonment of such systems if performance is not satisfactory. Therefore, it is of paramount importance for P2P energy trading systems to incorporate user behavioral modeling that captures users’ individual trading behaviors, preferences, and perceived utility in a realistic and accurate manner. Often, such user behavioral models are not known a priori in real-world settings, and therefore need to be learned online as the P2P system is operating. In this thesis, we design novel algorithms for P2P energy trading. By exploiting a variety of statistical, algorithmic, machine learning, and behavioral economics tools, we propose solutions that are able to jointly optimize the system performance while taking into account and learning realistic model of user behavior. The results in this dissertation has been published in IEEE Transactions on Green Communications and Networking 2021, Proceedings of IEEE Global Communication Conference 2022, Proceedings of IEEE Conference on Pervasive Computing and Communications 2023 and ACM Transactions on Evolutionary Learning and Optimization 2023