{"type":"ScholarlyArticle","title":"VidyutVanika21: An Autonomous Intelligent Broker for Smart-grids","authors":[{"name":"Sanjay Chandlekar","slug":"sanjay-chandlekar","given":"Sanjay","family":"Chandlekar","affiliation":"International Institute of Information Technology (IIIT) , Hyderabad , India"},{"name":"Bala Suraj Pedasingu","slug":"bala-suraj-pedasingu","given":"Bala Suraj","family":"Pedasingu","affiliation":"TCS Innovation Labs , Hyderabad , India"},{"name":"Easwar Subramanian","slug":"easwar-subramanian","given":"Easwar","family":"Subramanian","affiliation":"TCS Innovation Labs , Hyderabad , India"},{"name":"Sanjay Bhat","slug":"sanjay-bhat","given":"Sanjay","family":"Bhat","affiliation":"TCS Innovation Labs , Hyderabad , India"},{"name":"Praveen Paruchuri","slug":"praveen-paruchuri","given":"Praveen","family":"Paruchuri","affiliation":"International Institute of Information Technology (IIIT) , Hyderabad , India"},{"name":"Sujit Gujar","slug":"sujit-gujar","given":"Sujit","family":"Gujar","affiliation":"International Institute of Information Technology (IIIT) , Hyderabad , India"}],"abstract":"An autonomous broker that liaises between retail customers and power-generating companies (GenCos) is essential for the smart grid ecosystem. The efficiency brought in by such brokers to the smart grid setup can be studied through a well-developed simulation environment. In this paper, we describe the design of one such energy broker called VidyutVanika21 (VV21) and analyze its performance using a simulation platform called PowerTAC (PowerTrading Agent Competition). Specifically, we discuss the retail (VV21–RM) and wholesale market (VV21–WM) modules of VV21 that help the broker achieve high net profits in a competitive setup. Supported by game-theoretic analysis, the VV21–RM designs tariff contracts that a) maintain a balanced portfolio of different types of customers; b) sustain an appropriate level of market share, and c) introduce surcharges on customers to reduce energy usage during peak demand times. The VV21–WM aims to reduce the cost of procurement by following the supply curve of the GenCo to identify its lowest ask for a particular auction which is then used to generate suitable bids. We further demonstrate the efficacy of the retail and wholesale strategies of VV21 in PowerTAC 2021 finals and through several controlled experiments.","doi":"10.24963/ijcai.2022/23","url":"https://ijcai.org/proceedings/2022/23","pdf":"https://ijcai.org/proceedings/2022/0023.pdf","markdown":"https://ijcai.org/proceedings/2022/23.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/23","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Agent-based and Multi-agent Systems","track":"Main Track","number":23,"pages":{"first":158,"last":164},"keywords":["Agent-based and Multi-agent Systems: Economic Paradigms, Auctions and Market-Based Systems","Agent-based and Multi-agent Systems: Applications"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986637","length_sec":89,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38984780","length_sec":364,"provider":"slideslive"}],"references":[{"position":1,"raw":"[Chandlekar et al., 2022] Sanjay Chandlekar, Easwar Sub- ramanian, Sanjay Bhat, Praveen Paruchuri, and Sujit Gujar. Multi-unit double auctions: Equilibrium anal- ysis and bidding strategy using ddpg in smart-grids. arXiv,2201.10127,cs.GT, 2022.","title":"Multi-unit double auctions: Equilibrium analysis and bidding strategy using ddpg in smart-grids","authors":"Sanjay Chandlekar, Easwar Subramanian, Sanjay Bhat, Praveen Paruchuri, Sujit Gujar","year":"2022","venue":null,"doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Chowdhury et al., 2018] Moinul Morshed Porag Chowd- hury, Christopher Kiekintveld, Tran Cao Son, and William Yeoh. Bidding in periodic double auctions using heuris- tics and dynamic monte carlo tree search. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18), 2018.","title":"Bidding in periodic double auctions using heuristics and dynamic monte carlo tree search","authors":"Moinul Morshed, Porag Chowdhury, Christopher Kiekintveld, Tran Cao Son, William Yeoh","year":"2018","venue":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18)","doi":null,"url":null,"internal_url":"/proceedings/2018/23"},{"position":3,"raw":"[Chung et al., 2020] Hwei-Ming Chung, Sabita Maharjan, Yan Zhang, and Frank Eliassen. Distributed deep rein- forcement learning for intelligent load scheduling in resi- dential smart grids. IEEE Transactions on Industrial In- formatics, 17(4):2752-2763, 2020.","title":"Distributed deep reinforcement learning for intelligent load scheduling in residential smart grids","authors":"Hwei-Ming Chung, Sabita Maharjan, Yan Zhang, Frank Eliassen","year":"2020","venue":"IEEE Transactions on Industrial Informatics","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Ghosh et al., 2019] Susobhan Ghosh, Easwar Subramanian, Sanjay P. Bhat, Sujit Gujar, and Praveen Paruchuri. Vidyutvanika: A reinforcement learning based broker agent for a power trading competition. Proceedings of the AAAI Conference on Artificial Intelligence, 33:914-921, 2019.","title":"Vidyutvanika: A reinforcement learning based broker agent for a power trading competition","authors":"Ghosh","year":"2019","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Ghosh et al., 2020] Susobhan Ghosh, Sujit Gujar, Praveen Paruchuri, Easwar Subramanian, and Sanjay Bhat. Bid- ding in smart grid pdas: Theory, analysis and strategy. In Proceedings of the AAAI Conference on Artificial Intelli- gence AAAI'2020, pages 1974--1981, 2020.","title":"Bidding in smart grid pdas: Theory, analysis and strategy","authors":"Ghosh","year":"2020","venue":"Proceedings of the AAAI Conference on Artificial Intelligence AAAI'2020","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Jain and Gujar, 2020] Shweta Jain and Sujit Gujar. A mul- tiarmed bandit based incentive mechanism for a subset se- lection of customers for demand response in smart grids. Proceedings of the AAAI Conference on Artificial Intelli- gence, 34(02):2046-2053, Apr. 2020.","title":"A multiarmed bandit based incentive mechanism for a subset selection of customers for demand response in smart grids","authors":"Shweta Jain, Sujit Gujar","year":"2020","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Ketter et al., 2020] Wolfgang Ketter, John Collins, and Mathijs de Weerdt. The 2020 power trading agent com- petition (march 30, 2020). ERIM Report Series Reference No. 2020-002, http://dx.doi.org/10.2139/ssrn.3564107, 2020.","title":"The 2020 power trading agent competition","authors":"Ketter","year":"2020","venue":null,"doi":"10.2139/ssrn.3564107,2020","url":"http://dx.doi.org/10.2139/ssrn.3564107,2020","internal_url":null},{"position":8,"raw":"[Kuate et al., 2013] Rodrigue T. Kuate, Minghua He, Maria Chli, and Hai H. Wang. An intelligent broker agent for energy trading: An mdp approach. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, 2013.","title":"An intelligent broker agent for energy trading: An mdp approach","authors":"T Rodrigue, Minghua Kuate, Maria He, Hai H Chli, Wang","year":"2013","venue":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":"/proceedings/2013/44"},{"position":9,"raw":"[McKelveya et al., 2014] Richard D. McKelveya, An- drew M. McLennan, and Theodore L. Turocy. Gambit: Software Tools for Game Theory, Version 16.0.1. http://www.gambit-project.org, 2014. [Online; accessed 27-December-2021].","title":"Gambit: Software Tools for Game Theory","authors":"Richard D Mckelveya, Andrew M Mclennan, Theodore L Turocy","year":"2021","venue":null,"doi":null,"url":"http://www.gambit-project.org,2014","internal_url":null},{"position":10,"raw":"[Orfanoudakis et al., 2021] Stavros Orfanoudakis, Stefanos Kontos, Charilaos Akasiadis, and Georgios Chalkiadakis. Aiming for half gets you to the top: Winning powertac 2020. In Multi-Agent Systems, 18th European Conference, EUMAS 2021, pages 144-159, 07 2021.","title":"Aiming for half gets you to the top: Winning powertac 2020","authors":"Stavros Orfanoudakis, Stefanos Kontos, Charilaos Akasiadis, Georgios Chalkiadakis","year":"2021","venue":"Multi-Agent Systems, 18th European Conference","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Reddy and Veloso, 2011] Prashant P. Reddy and Manuela M. Veloso. Strategy learning for autonomous agents in smart grid markets. In Proceedings of the Twenty-Second International Joint Conference on Ar- tificial Intelligence -Volume Two, IJCAI'11, pages 1446--1451. AAAI Press, 2011.","title":"Strategy learning for autonomous agents in smart grid markets","authors":"P Prashant, Manuela M Reddy, Veloso","year":"2011","venue":"Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence -Volume Two, IJCAI'11","doi":null,"url":null,"internal_url":"/proceedings/2011/244"},{"position":12,"raw":"[Serrano et al., 2017] Jonathan Serrano, , Ansel Y. Rodríguez González, and Munoz de Cote. Fixed- price tariff generation using reinforcement learning.","title":"Fixedprice tariff generation using reinforcement learning","authors":"Jonathan Serrano, Ansel Y Rodríguez González, Munoz De Cote","year":null,"venue":null,"doi":null,"url":null,"internal_url":null},{"position":13,"raw":"Fujita K. et al. (eds) Modern Approaches to Agent-based Complex Automated Negotiation. Studies in Computa- tional Intelligence, Springer, Cham, 674, 2017. [Techopedia.com, 2021] Techopedia.com. Smart Grid. https://www.techopedia.com/definition/692/smart-grid, 2021. [Online; accessed 27-December-2021].","title":"Modern Approaches to Agent-based Complex Automated Negotiation","authors":null,"year":"2017","venue":"Studies in Computational Intelligence","doi":null,"url":"https://www.techopedia.com/definition/692/smart-grid,2021","internal_url":null},{"position":14,"raw":"[Urieli and Stone, 2014] Daniel Urieli and Peter Stone. Tac- tex'13: A champion adaptive power trading agent. In Pro- ceedings of the Twenty Eighth AAAI Conference on Artifi- cial Intelligence, pages 465-471. Association for the Ad- vancement of Artificial Intelligence, 2014.","title":"Daniel Urieli and Peter Stone. Tactex'13: A champion adaptive power trading agent","authors":"Stone Urieli","year":"2014","venue":"Proceedings of the Twenty Eighth AAAI Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Urieli and Stone, 2016] Daniel Urieli and Peter Stone. Au- tonomous electricity trading using time-of-use tariffs in a competitive market. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16). Associa- tion for the Advancement of Artificial Intelligence, 2016.","title":"Daniel Urieli and Peter Stone. Autonomous electricity trading using time-of-use tariffs in a competitive market","authors":"Stone Urieli","year":"2016","venue":"Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16). Association for the Advancement of Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Özdemir and Unland, 2018] Serkan Özdemir and Rainer Unland. Agentude17: A genetic algorithm to optimize the parameters of an electricity tariff in a smart grid en- vironment. Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Col- lection, pages 224-236, 06 2018.","title":"Agentude17: A genetic algorithm to optimize the parameters of an electricity tariff in a smart grid environment","authors":"Unland Özdemir, Serkan Özdemir, Rainer Unland","year":"2018","venue":"Advances in Practical Applications of Agents, Multi-Agent Systems, and Complexity: The PAAMS Collection","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}