[ { "key": "XBLE9D9V", "version": 588, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/XBLE9D9V", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/XBLE9D9V", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Collins and Ketter", "parsedDate": "2022-12-01", "numChildren": 0 }, "data": { "key": "XBLE9D9V", "version": 588, "itemType": "journalArticle", "title": "Power TAC: Software architecture for a competitive simulation of sustainable smart energy markets", "creators": [ { "creatorType": "author", "firstName": "John", "lastName": "Collins" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Ketter" } ], "abstractNote": "Power TAC (www.powertac.org) is a discrete-time competitive simulation that models a retail electricity market. Since 2012 it has been the foundation of an annual competition, challenging teams from around the world to build autonomous trading agents that communicate with the simulation over the internet. These “retail brokers” offer energy services to customers through tariff contracts, and must then serve those customers by trading in a wholesale market. Hourly differences between wholesale market positions and net consumption by their subscribed customers must be cleared in a local balancing market using a combination of demand response and wholesale balancing energy. The simulation server is open source and highly modular, designed to be accessible to inexperienced student developers. It makes heavy use of annotations and aspect-oriented programming to achieve consistency and ensure that all important events are recorded, allowing simulations to be re-played and analyzed in depth.", "publicationTitle": "SoftwareX", "publisher": "", "place": "", "date": "2022-12-01", "volume": "20", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "101217", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "SoftwareX", "DOI": "10.1016/j.softx.2022.101217", "citationKey": "", "url": "https://www.sciencedirect.com/science/article/pii/S2352711022001352", "accessDate": "2022-11-05T22:12:32Z", "PMID": "", "PMCID": "", "ISSN": "2352-7110", "archive": "", "archiveLocation": "", "shortTitle": "Power TAC", "language": "en", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Competitive benchmarking", "type": 1 }, { "tag": "Open-source software", "type": 1 }, { "tag": "Simulation", "type": 1 }, { "tag": "Smart markets", "type": 1 }, { "tag": "Sustainable electricity", "type": 1 }, { "tag": "Trading agents", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:25:59Z", "dateModified": "2024-03-08T17:25:59Z" } }, { "key": "QCLS3FVE", "version": 597, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/QCLS3FVE", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/QCLS3FVE", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Milkau et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "QCLS3FVE", "version": 597, "itemType": "bookSection", "title": "Power TAC Experiment Manager: Support for Empirical Studies", "creators": [ { "creatorType": "author", "firstName": "Frederik", "lastName": "Milkau" }, { "creatorType": "author", "firstName": "John", "lastName": "Collins" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "The Power TAC Experiment Manager is a tool that supports empirical research using the Power TAC competitive simulation environment. An “experiment” in this context consists of a set of baseline games that are typically configured to be identical except for the seeds used to generate the various random values used in a simulation, along with a set of treatments. A treatment can be a configuration change in the server, such as the population of distributed solar producers, or a change in configuration of one of the brokers, or a change in the set of brokers competing with each other, or a change in the weather data sequence. The Experiment Manager is designed around the Docker container virtualization engine, simplifying setup and operation and supporting broker designs that are not easily distributed as simple “jar” files. The result is a system that greatly simplifies the process of setting up and running empirical studies that may require running tens to hundreds of multi-hour simulation session, and collecting and processing the resulting flood of large log files.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "219-235", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_12", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_12", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Power TAC Experiment Manager", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Container virtualization", "type": 1 }, { "tag": "Data management", "type": 1 }, { "tag": "Designed experiments", "type": 1 }, { "tag": "Empirical research", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:19:54Z", "dateModified": "2024-03-08T17:19:54Z" } }, { "key": "Y79APC4E", "version": 597, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/Y79APC4E", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/Y79APC4E", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Kahlen et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "Y79APC4E", "version": 597, "itemType": "bookSection", "title": "Smart Market-Driven Virtual Power Plants of Shared Electric Vehicles", "creators": [ { "creatorType": "author", "firstName": "Micha", "lastName": "Kahlen" }, { "creatorType": "author", "firstName": "Karsten", "lastName": "Schroer" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "author", "firstName": "Alok", "lastName": "Gupta" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "As the share of renewable energy becomes an increasing part of electricity generation, electric vehicles (EVs) have the potential to be used as virtual power plants (VPP) to provide reliable back-up power. This could generate additional profits for EV carsharing rental firms. We design a computational control mechanism for VPPs that decide whether EVs should be charging, discharging, or rented out. We validate our computational design by developing a discrete-event simulation platform based on real-time GPS information from 367 electric cars from Daimler’s carsharing service Car2Go in San Diego. We compute trading prices (bids and asks) for participating in secondary control reserve markets and investigate what effect the density of charging infrastructure, battery technology, and rental demand for vehicles have on the pay-off for the carsharing fleet. We show that VPPs can create sustainable revenue streams for electric vehicle carsharing fleets without compromising their rental business.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "197-218", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_11", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_11", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Electric vehicles", "type": 1 }, { "tag": "Intelligent agents", "type": 1 }, { "tag": "Smart markets", "type": 1 }, { "tag": "Virtual power plants", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:19:19Z", "dateModified": "2024-03-08T17:19:19Z" } }, { "key": "FAB4LYRT", "version": 597, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/FAB4LYRT", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/FAB4LYRT", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Rook et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "FAB4LYRT", "version": 597, "itemType": "bookSection", "title": "Incorporating Social Values for Cooperation in Energy Trading and Balancing Research", "creators": [ { "creatorType": "author", "firstName": "Laurens", "lastName": "Rook" }, { "creatorType": "author", "firstName": "Sudip", "lastName": "Bhattacharjee" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "Consumers of electricity increasingly participate in demand-side management programs aimed at shifting the demand for electricity from peak hours to non-peak hours. At present, energy corporations primarily nudge such participants toward energy reduction by providing them with monetary incentives. Drawing on the psychological literature on social values for cooperation, we will argue that it is important to also consider the use of incentives tapping prosociality. Research shows that people with a prosocial value orientation tend to exhibit an intrinsic motivation to positively contribute to the maintenance of collective goods and resources. Their behavioral response is often characterized by an alleviated willingness to make common cause. Presenting electricity as a common-pool resource—shared by all but to be used with moderation by the individual—may suffice to establish sustained peak-shaving behavior among the more prosocial consumers of electricity. In this book chapter, first, the research on social value orientation and its measurement will be presented. Second, an overview will be provided of the most relevant situational factors that influence social value orientation. Finally, recommendations will be formulated on how to include social values for cooperation in the Power Trading Agent Competition.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "179-196", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_10", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_10", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Cooperation", "type": 1 }, { "tag": "Energy balancing", "type": 1 }, { "tag": "Incentives", "type": 1 }, { "tag": "Power TAC", "type": 1 }, { "tag": "Public goods", "type": 1 }, { "tag": "Social dilemmas", "type": 1 }, { "tag": "Social value orientation", "type": 1 }, { "tag": "Sustainability", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:17:50Z", "dateModified": "2024-03-08T17:17:50Z" } }, { "key": "U54LMYC4", "version": 597, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/U54LMYC4", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/U54LMYC4", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Grgic et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "U54LMYC4", "version": 597, "itemType": "bookSection", "title": "CrocodileAgent: A Decade of Competing in the Power Trading Agent Competition", "creators": [ { "creatorType": "author", "firstName": "Demijan", "lastName": "Grgic" }, { "creatorType": "author", "firstName": "Jurica", "lastName": "Babic" }, { "creatorType": "author", "firstName": "Vedran", "lastName": "Podobnik" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "The Power Trading Agent Competition (Power TAC) is a yearly research competition that provides an open-source, smart grid simulation platform where brokers from research universities compete and test different strategies in power brokerage. CrocodileAgent is an intelligent software agent, developed at the University of Zagreb, which competed in all ten Power TAC competitions from 2012 to 2021. During that period, the CrocodileAgent evolved together with the Power TAC platform and other competing agents. We had the opportunity to experiment with different agent modelling and algorithmic approaches while measuring the success of various agent designs in a competitive and ever-changing environment. This paper presents the main principles of how the CrocodileAgent was implemented during the latest Power TAC competitions (2018–2021) when it consistently won 3rd place in the competition finals.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "171-178", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_9", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_9", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "CrocodileAgent", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Agent-based modelling", "type": 1 }, { "tag": "CrocodileAgent", "type": 1 }, { "tag": "Data science", "type": 1 }, { "tag": "Electricity trading", "type": 1 }, { "tag": "Power TAC", "type": 1 }, { "tag": "Tariff design", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:17:12Z", "dateModified": "2024-03-08T17:17:12Z" } }, { "key": "3ZK7B22A", "version": 597, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/3ZK7B22A", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/3ZK7B22A", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Chowdhury et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "3ZK7B22A", "version": 597, "itemType": "bookSection", "title": "SPOT: Strategies for Power Trading in Wholesale Electricity Markets", "creators": [ { "creatorType": "author", "firstName": "Moinul Morshed Porag", "lastName": "Chowdhury" }, { "creatorType": "author", "firstName": "Christopher", "lastName": "Kiekintveld" }, { "creatorType": "author", "firstName": "Tran Cao", "lastName": "Son" }, { "creatorType": "author", "firstName": "Enrico", "lastName": "Pontelli" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "The Power Trading Agent Competition (Power TAC) simulates numerous economic multi-agent trading scenarios where brokers trade in multiple power markets. A successful broker makes sound predictions about future energy supplies, demands, and costs in these markets and bids intelligently to gain profit. The broker who maintains the most profitable portfolio wins the competition. In this chapter, we detail some novel wholesale trading strategies of the broker SPOT used in competitions from 2015 to 2020. We present the higher-level ideas of these strategies with experimental results and discuss the experiences gained in the tournaments while playing some of these strategies. SPOT’s MCTS wholesale bidding strategy can procure energy at the lowest cost, which is presently the state-of-the-art strategy in the PDA markets. We also propose a state-of-the-art methodology to explore better strategies (applicable to the Power TAC domain) against a specific set of opponents, minimizing the agent’s regret.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "145-170", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_8", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_8", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "SPOT", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Artificial intelligence", "type": 1 }, { "tag": "Electricity brokers", "type": 1 }, { "tag": "Machine learning", "type": 1 }, { "tag": "Multi-agent system", "type": 1 }, { "tag": "Trading strategies", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:16:31Z", "dateModified": "2024-03-08T17:16:31Z" } }, { "key": "XN4745TE", "version": 597, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/XN4745TE", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/XN4745TE", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Makrodimitris and Symeonidis", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "XN4745TE", "version": 597, "itemType": "bookSection", "title": "Upgrading a Winning Agent to Not Winning: The Case of Agent Mertacor in Power TAC", "creators": [ { "creatorType": "author", "firstName": "Lampros", "lastName": "Makrodimitris" }, { "creatorType": "author", "firstName": "Andreas L.", "lastName": "Symeonidis" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "Contemporary retail electricity markets dictate real-time trading, while at the same time must take into account a variety of factors for the optimization and continuous adaptation, in order to generate profit and avoid customer losses. Near-future electricity markets demand even more, since RES penetration and advanced storage and distribution systems facilitate the rise of smart grids. The Power TAC platform constitutes a realistic simulation of such near-future energy markets that enables the proper comprehension and study of potential strategies in such a competitive environment. In Power TAC, agents take the roles of brokers and compete against each other, prioritizing profitable transactions at the simulated retail and wholesale energy markets (like in a real-case scenario). Current work discusses how the efficiency of a winning strategy can be downgraded when implemented improvements disrupt the equilibrium that the agent has achieved. Specifically, the paper presents the winning strategy of Mertacor 2019 and discusses the core modules of the agent, i.e., tariff creation, wholesale market, and energy prediction modules. Based on the analysis performed on the results of Power TAC 2019, a number of changes were implemented for Mertacor 2020, which led to improving specific facets of the agent, while at the same time downgrading the performance of others. In our attempt to reinstate our agent to its “throne,” a revamp at core modules of the agent was planned and executed in a short period; without proper testing, the agent performed poorly throughout the trials, once again proving that badly tested software always leads to failure. Still, the refactoring of the agent has created an opportunity for a more robust and economy-centric strategy.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "117-144", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_7", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_7", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Upgrading a Winning Agent to Not Winning", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Autonomous trading agents", "type": 1 }, { "tag": "Energy broker", "type": 1 }, { "tag": "Power TAC", "type": 1 }, { "tag": "Renewable energy sources", "type": 1 }, { "tag": "Software design", "type": 1 }, { "tag": "Software simulation", "type": 1 }, { "tag": "Software testing", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:15:30Z", "dateModified": "2024-03-08T17:15:30Z" } }, { "key": "D4ZPHU8J", "version": 597, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/D4ZPHU8J", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/D4ZPHU8J", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Özdemir and Unland", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "D4ZPHU8J", "version": 597, "itemType": "bookSection", "title": "AgentUDE: A Smart Broker Agent for Autonomous Power Trading", "creators": [ { "creatorType": "author", "firstName": "Serkan", "lastName": "Özdemir" }, { "creatorType": "author", "firstName": "Rainer", "lastName": "Unland" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "AgentUDE is a retail energy agent that participated in the Power TAC smart grid competition for a while with some success. This article describes the milestones of its development as well as performance analyses through controlled experiments and tournament data analyses. The first part briefly reviews the development of AgentUDE from 2014 to the release of the first stable version (i.e., AgentUDE17) year by year. The second part goes into detail about the stable version that has been in use since 2017. Unlike its predecessors, AgentUDE17 is built on new concepts. On the retail side, AgentUDE17 relies mainly on genetic algorithms (GA) that optimize the parameters of the underlying consumption tariff, such as retail unit price, periodic payments, enrollment fees, and early withdrawal penalties, on the fly. In the wholesale market, AgentUDE17 uses a novel algorithm to make strategic bids in the wholesale market, taking advantage of the incentives of the balancing market. All versions of AgentUDE were successful brokers in the Power TAC competition. The older AgentUDE became, the stronger its competitors became. However, AgentUDE17 was able to maintain its position as a reliable and robust broker for years due to its self-evolving structure.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "97-116", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_6", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_6", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "AgentUDE", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Balancing market", "type": 1 }, { "tag": "Broker", "type": 1 }, { "tag": "Genetic algorithms", "type": 1 }, { "tag": "Retail market", "type": 1 }, { "tag": "Trading", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:14:48Z", "dateModified": "2024-03-08T17:14:48Z" } }, { "key": "EE3P627M", "version": 597, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/EE3P627M", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/EE3P627M", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Rook et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "EE3P627M", "version": 597, "itemType": "bookSection", "title": "Nudging the Direction of Energy Tariff Selection: Lessons Learned from an Attribute Framing Experiment with Temporal Construal Levels", "creators": [ { "creatorType": "author", "firstName": "Laurens", "lastName": "Rook" }, { "creatorType": "author", "firstName": "Jan van", "lastName": "Dalen" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "75-96", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_5", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_5", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Nudging the Direction of Energy Tariff Selection", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "abstract thinking", "type": 1 }, { "tag": "attribute framing", "type": 1 }, { "tag": "behavioral identification form", "type": 1 }, { "tag": "construal level", "type": 1 }, { "tag": "energy labeling; sustainability.", "type": 1 }, { "tag": "environmental policy", "type": 1 }, { "tag": "nudging", "type": 1 }, { "tag": "persuasion", "type": 1 }, { "tag": "pro-environmental attitudes", "type": 1 }, { "tag": "specific thinking", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:14:11Z", "dateModified": "2024-03-08T17:14:11Z" } }, { "key": "PQF8CZQD", "version": 596, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/PQF8CZQD", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/PQF8CZQD", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Naseri et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "PQF8CZQD", "version": 596, "itemType": "bookSection", "title": "Designing Retail Electricity Tariffs Using Reinforcement Learning", "creators": [ { "creatorType": "author", "firstName": "Nastaran", "lastName": "Naseri" }, { "creatorType": "author", "firstName": "Saber", "lastName": "Talari" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "author", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "The replacement of reliable fossil fuel generators with less predictable renewable power generation challenges energy systems and markets. Among these challenges, procuring electricity and maintaining system reliability during peak times induce high costs to power systems. Therefore, system operators charge electricity aggregators for their contributions to peak demand, referred to as capacity costs. This chapter proposes an autonomous trading agent (aggregator) model to profit from participation in retail markets. Using offline and online Reinforcement Learning, the aggregator develops tariffs that minimize its contribution to peak demand by applying market segmentation to consumers group. In addition, a sophisticated prediction service is designed for demand forecast. The market to implement the proposed aggregator should contain the characteristics of a smart retail market. Hence, in this work, Power Trading Agent Competition (Power TAC) is employed as an open-source smart grid simulation platform with real-world data to evaluate the performance of the agent (aggregator). It is concluded from the implementation that tariffs incorporating usage-based charges combined with fixed periodic charges result in a portfolio of primarily non-residential customers and reduce the aggregator’s capacity costs.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "57-73", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_4", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_4", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Electricity markets", "type": 1 }, { "tag": "Multi-agent competition", "type": 1 }, { "tag": "Reinforcement learning", "type": 1 }, { "tag": "Tariff design", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:13:24Z", "dateModified": "2024-03-08T17:13:24Z" } }, { "key": "GF2ELIGK", "version": 596, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/GF2ELIGK", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/GF2ELIGK", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Chandlekar et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "GF2ELIGK", "version": 596, "itemType": "bookSection", "title": "VidyutVanika: AI-Based Autonomous Broker for Smart Grids: From Theory to Practice", "creators": [ { "creatorType": "author", "firstName": "Sanjay", "lastName": "Chandlekar" }, { "creatorType": "author", "firstName": "Bala Suraj", "lastName": "Pedasingu" }, { "creatorType": "author", "firstName": "Susobhan", "lastName": "Ghosh" }, { "creatorType": "author", "firstName": "Easwar", "lastName": "Subramanian" }, { "creatorType": "author", "firstName": "Sanjay", "lastName": "Bhat" }, { "creatorType": "author", "firstName": "Praveen", "lastName": "Paruchuri" }, { "creatorType": "author", "firstName": "Sujit", "lastName": "Gujar" }, { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "We present the design, implementation, and analysis of autonomous brokers for a smart grid ecosystem, in the context of PowerTAC. PowerTAC simulates the real-world smart grid ecosystem through wholesale, retail, and balancing markets. The complexity of grid operations makes designing broker components using artificial intelligence (AI) inevitable. We begin with the challenges prevalent in devising such autonomous brokers. Then, we describe the design, implementation, and performance of our AI-based autonomous agent VidyutVanika (VV). We discuss two variants of VV: VV18 and VV21, which were successful in the annual PowerTAC tournaments, 2018 and 2021, respectively.", "bookTitle": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "Cham", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "25-56", "ISBN": "978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3_3", "citationKey": "", "url": "https://doi.org/10.1007/978-3-031-39707-3_3", "accessDate": "2024-03-08T17:00:27Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "VidyutVanika", "language": "en", "libraryCatalog": "Springer Link", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "DDPG for learning equilibrium bidding strategy", "type": 1 }, { "tag": "Equilibrium analysis", "type": 1 }, { "tag": "Multi-unit PDA", "type": 1 }, { "tag": "Reinforcement learning", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:12:16Z", "dateModified": "2024-03-08T17:12:16Z" } }, { "key": "BIN8TSG8", "version": 596, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/BIN8TSG8", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/BIN8TSG8", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266075, "username": "grampajohn", "name": "John Collins", "links": { "alternate": { "href": "https://www.zotero.org/grampajohn", "type": "text/html" } } }, "creatorSummary": "Collins et al.", "parsedDate": "2023", "numChildren": 0 }, "data": { "key": "BIN8TSG8", "version": 596, "itemType": "book", "title": "Energy Sustainability through Retail Electricity Markets: The Power Trading Agent Competition (Power TAC) Experience", "creators": [ { "creatorType": "editor", "firstName": "John", "lastName": "Collins" }, { "creatorType": "editor", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "editor", "firstName": "Andreas L.", "lastName": "Symeonidis" } ], "abstractNote": "", "series": "Applied Innovation and Technology Management", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2023", "publisher": "Springer International Publishing", "place": "", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "numPages": "", "ISBN": "978-3-031-39706-6 978-3-031-39707-3", "DOI": "10.1007/978-3-031-39707-3", "citationKey": "", "url": "https://link.springer.com/10.1007/978-3-031-39707-3", "accessDate": "2024-03-08T17:00:26Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Energy Sustainability through Retail Electricity Markets", "language": "en", "libraryCatalog": "DOI.org (Crossref)", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Competitive simulation", "type": 1 }, { "tag": "Energy System modeling", "type": 1 }, { "tag": "Intelligent agents", "type": 1 }, { "tag": "Machine Learning", "type": 1 }, { "tag": "Power Trading Agent Competition (Power TAC)", "type": 1 }, { "tag": "Sustainable energy", "type": 1 }, { "tag": "Virtual power plants", "type": 1 }, { "tag": "retail electricity markets", "type": 1 }, { "tag": "statistical modeling", "type": 1 } ], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-08T17:01:55Z", "dateModified": "2024-03-08T17:04:56Z" } }, { "key": "YKSJ7ZL7", "version": 573, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/YKSJ7ZL7", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/YKSJ7ZL7", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266604, "username": "wolfketter", "name": "Wolf Ketter", "links": { "alternate": { "href": "https://www.zotero.org/wolfketter", "type": "text/html" } } }, "creatorSummary": "Kahlen et al.", "parsedDate": "2012", "numChildren": 0 }, "data": { "key": "YKSJ7ZL7", "version": 573, "itemType": "conferencePaper", "title": "A profitable business model for electric vehicle fleet owners", "creators": [ { "creatorType": "author", "firstName": "Micha", "lastName": "Kahlen" }, { "creatorType": "author", "firstName": "Konstantina", "lastName": "Valogianni" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "author", "firstName": "Jan", "lastName": "Van Dalen" } ], "abstractNote": "", "proceedingsTitle": "2012 International Conference on Smart Grid Technology, Economics and Policies (SG-TEP)", "conferenceName": "2012 International Conference on Smart Grid Technology, Economics and Policies (SG-TEP)", "publisher": "IEEE", "place": "Nuremberg", "date": "2012", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "1-5", "series": "", "seriesNumber": "", "DOI": "10.1109/SG-TEP.2012.6642395", "ISBN": "9781467359320", "citationKey": "", "url": "https://ieeexplore.ieee.org/document/6642395/", "accessDate": "2024-03-07T09:14:23Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "DOI.org (Crossref)", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "3BYPAVD3" ], "relations": {}, "dateAdded": "2024-03-07T09:14:24Z", "dateModified": "2024-03-07T09:14:37Z" } }, { "key": "VGG243NA", "version": 565, "library": { "type": "group", "id": 485203, "name": "Power TAC Website Publist", "links": { "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/485203/items/VGG243NA", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/power_tac_website_publist/items/VGG243NA", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1266604, "username": "wolfketter", "name": "Wolf Ketter", "links": { "alternate": { "href": "https://www.zotero.org/wolfketter", "type": "text/html" } } }, "creatorSummary": "Ahadi et al.", "parsedDate": "2023-05", "numChildren": 0 }, "data": { "key": "VGG243NA", "version": 565, "itemType": "journalArticle", "title": "Cooperative Learning for Smart Charging of Shared Autonomous Vehicle Fleets", "creators": [ { "creatorType": "author", "firstName": "Ramin", "lastName": "Ahadi" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Ketter" }, { "creatorType": "author", "firstName": "John", "lastName": "Collins" }, { "creatorType": "author", "firstName": "Nicolò", "lastName": "Daina" } ], "abstractNote": "We study the operational problem of shared autonomous electric vehicles that cooperate in providing on-demand mobility services while maximizing fleet profit and service quality. Therefore, we model the fleet operator and vehicles as interactive agents enriched with advanced decision-making aids. Our focus is on learning smart charging policies (when and where to charge vehicles) in anticipation of uncertain future demands to accommodate long charging times, restricted charging infrastructure, and time-varying electricity prices. We propose a distributed approach and formulate the problem as a semi-Markov decision process to capture its stochastic and dynamic nature. We use cooperative multiagent reinforcement learning with reshaped reward functions. The effectiveness and scalability of the proposed model are upgraded through deep learning. A mean-field approximation deals with environment instabilities, and hierarchical learning distinguishes high-level and low-level decisions. We evaluate our model using various numerical examples based on real data from ShareNow in Berlin, Germany. We show that the policies learned using our decentralized and dynamic approach outperform central static charging strategies. Finally, we conduct a sensitivity analysis for different fleet characteristics to demonstrate the proposed model’s robustness and provide managerial insights into the impacts of strategic decisions on fleet performance and derived charging policies. \n Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.1187 .", "publicationTitle": "Transportation Science", "publisher": "", "place": "", "date": "2023-05", "volume": "57", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "613-630", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Transportation Science", "DOI": "10.1287/trsc.2022.1187", "citationKey": "", "url": "https://pubsonline.informs.org/doi/10.1287/trsc.2022.1187", "accessDate": "2024-03-06T22:28:42Z", "PMID": "", "PMCID": "", "ISSN": "0041-1655, 1526-5447", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "DOI.org (Crossref)", "callNumber": "", 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The wholesale market is a relatively simple call market, similar to many existing wholesale electric power markets, such as Nord Pool in Scandinavia or FERC markets in North America, but unlike the FERC markets we are modeling a single region, and therefore we do not model location-marginal pricing. Customer models include households and a variety of commercial and industrial entities, many of which have production capacity (such as solar panels or wind turbines) as well as electric vehicles. All have “real-time” metering to support allocation of their hourly supply and demand to their subscribed brokers, and all are approximate utility maximizers with respect to tariff selection, although the factors making up their utility functions may include aversion to change and complexity that can retard uptake of marginally better tariff offers. The distribution utility models the regulated natural monopoly that owns the regional distribution network, and is responsible for maintenance of its infrastructure and for real-time balancing of supply and demand. The balancing process is a market-based mechanism that uses economic incentives to encourage brokers to achieve balance within their portfolios of tariff subscribers and wholesale market positions, in the face of stochastic customer behaviors and weather-dependent renewable energy sources. 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