{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-stackelberg-game-approach-to-control-the","title":"A Stackelberg Game Approach to Control the Overall Load Consumption of a Residential Neighborhood","arxiv_id":"2306.10935","date":"2023-06-19","proceeding":null,"authors":["Erhan Can Ozcan","Ioannis Ch. Paschalidis"],"abstract":"This paper formulates a Stackelberg game between a coordination agent and participating homes to control the overall load consumption of a residential neighborhood. Each home optimizes a comfort-cost trade off to determine a load schedule of its available appliances in response to a price vector set by the coordination agent. The goal of the coordination agent is to find a price vector that will keep the overall load consumption of the neighborhood around some target value. After transforming the bilevel optimization problem into a single level optimization problem by using Karush-Kuhn-Tucker (KKT) conditions, we model how each home reacts to any change in the price vector by using the implicit function theorem. By using this information, we develop a distributed optimization framework based on gradient descent to attain a better price vector. We verify the load shaping capacity and the computational performance of the proposed optimization framework in a simulated environment establishing significant benefits over solving the centralized problem using commercial solvers.","url_abs":"https://arxiv.org/abs/2306.10935v1","url_pdf":"https://arxiv.org/pdf/2306.10935v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"a-stackelberg-game-approach-to-control-the","repo_url":"https://github.com/erhancanozcan/energy-qcqp-grad","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}