Smart City Gnosys
Smart city article details
| Title | Optimal Real-Time Pricing And Sustainable Load Scheduling Model For Smart Homes Using Stackelberg Game Theory |
|---|---|
| ID_Doc | 40495 |
| Authors | Dheeraja K.; Padma Priya R.; Ritika T. |
| Year | 2022 |
| Published | Lecture Notes on Data Engineering and Communications Technologies, 99 |
| DOI | http://dx.doi.org/10.1007/978-981-16-7182-1_22 |
| Abstract | Governments today are striving at their best to keepup with the “Energy for all” motto among their citizens. Today, majority of the electricity is generated through non-renewable resources, but these resources are getting depleted day by day. With more and more connected things around us, the drive and thrive for efficient electricity load scheduling has been an important focus, in order to ensure availability of electricity till the last mile. It is also observed that few usage hours experience over-consumptions, amid the possible presence of under-consumption usage hours. We, in this paper, propose an efficient load scheduling model for achieving a sustainable power system framework using reverse Stackelberg game technique. Since this game is played between the Electricity Department and domestic consumers, it is a single leader multi-follower problem. This reverse Stackelberg model handles a bi-level programming problem, with a single objective at the upper level (leader) and two objectives at the lower level (followers). At the upper level, we have the Electricity Department, whose aim is to propose a real-time tariff plan such that the electricity demand of his customers is load-balanced throughout the day. Contrastingly at the lower level, we have domestic users, who seek to schedule usage of their appliances in such a way that their two objectives, namely minimization of electricity bills and maximization of satisfaction, are attained. The leader’s and followers’ problems have been solved using genetic algorithm and greedy approach, respectively, which yielded a reduction of up to 68% domestic load consumption during peak hours. An average of 33% and markdowns of up to 72% were observed in the bimonthly bills of high power-consuming users during the experimental runs. Thus, this model has been proposed aiming for effective and sustainable benefits, as the Indian government is moving towards installation of smart meters in smart homes under smart cities development project plans. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. |
| Author Keywords | Electricity load scheduling; Genetic algorithm; Satisfaction modeling; Stackelberg game; Sustainable energy |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
22295  | 0.88 | Manzoor A.; Akram W.; Judge M.A.; Khan N.; Khattak H.A. | Efficient Economic Energy Scheduling In Smart Cities Using Distributed Energy Resources | Science and Technology for Energy Transition (STET), 79 (2024) |
| 53662 | 0.869 | Zhang Z.; Chen Z. | Supply-Demand Collaborative Energy Internet For Smart City: A Three-Stage Stackelberg Game Approach | Proceedings - 2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, CyberC 2019 (2019) |
| 58385 | 0.869 | Ghanavati F.; Matias J.C.O.; Osório G.J. | Towards Sustainable Smart Cities: Integration Of Home Energy Management System For Efficient Energy Utilization | Sustainable Cities and Society, 111 (2024) |
| 3316 | 0.868 | Saroha P.; Singh G. | A Novel Dprede Model For Optimizing Demand-Side Power Management In Smart Home | Progress in Artificial Intelligence, 14, 2 (2025) |
| 40751 | 0.86 | Hou L.; Tong X.; Chen H.; Fan L.; Liu T.; Liu W.; Liu T. | Optimized Scheduling Of Smart Community Energy Systems Considering Demand Response And Shared Energy Storage | Energy, 295 (2024) |
| 40488 | 0.859 | Liu L.; Li X.; Ji H.; Zhang H. | Optimal Pricing And Energy Scheduling With Adaptive Grouping Based On Trading Contribution Evaluation In Smart Grid | IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC (2023) |
| 16300 | 0.856 | Wanjala J.; Langa H.M.; Walingo T. | Cost Minimization In A Smart Grid Using A Genetic Algorithm | International Conference on Science, Engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024 (2024) |
| 3547 | 0.856 | Tostado-Véliz M.; Rezaee Jordehi A.; Hasanien H.M.; Turky R.A.; Jurado F. | A Novel Stochastic Home Energy Management System Considering Negawatt Trading | Sustainable Cities and Society, 97 (2023) |
| 40420 | 0.854 | Raza A.; Jingzhao L.; Adnan M.; Ahmad I. | Optimal Load Forecasting And Scheduling Strategies For Smart Homes Peer-To-Peer Energy Networks: A Comprehensive Survey With Critical Simulation Analysis | Results in Engineering, 22 (2024) |