Smart pricing scheme: A multi-layered scoring rule application |
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| Affiliation: | 1. Nagoya Institute of Technology, Department of Computer Science, Gokisho, Showa, Nagoya, Aichi, 466-8555, Japan;2. University of the Ryukyus, Department of Electrical Engineering, Nakagami, Nishihara, Okinawa, 903-0213, Japan;1. School of Economics and Management, Free University of Bozen-Bolzano, Bolzano, Italy;2. Institute of Mathematics, University of Warsaw, Warszawa, Poland;3. Department “Methods and Models for Economics, Territory and Finance”, Sapienza University of Rome, Rome, Italy;1. School of Control Science and Engineering, Dalian University of Technology, Dalian City, PR China;2. Department of Electrical Computer Engineering, University of Alberta, Edmonton, AB T6R 2V4, Canada;3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland;1. Faculty of Phil. and Arts, University of Kragujevac, Jovana Cvijica bb, 34000 Kragujevac, Serbia;2. Faculty of Economics, University of Nis, Trg kralja Aleksandra Ujedinitelja 11, 18000 Nis, Serbia;3. Faculty of Economics, University of Kragujevac, Djure Pucara Starog 3, 34000 Kragujevac, Serbia;4. Faculty of Engineering, University of Kragujevac, Sestre Janjic 6, 34000 Kragujevac, Serbia;5. College of Applied Mechanical Engineering, Trstenik, Serbia |
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| Abstract: | Defining appropriate pricing strategy for smart environment is important and complex task at the same time. It holds the primal fraction in Demand Response (DR) program. In our work, we devise an incentive based smart dynamic pricing scheme for consumers facilitating a multi-layered scoring rule. The proposed strategy characterizes both incentive based DR and price based DR programs facilities. This mechanism is applied between consumer agents (CA) to electricity provider agent (EP) and EP to Generation Company (GENCO). Based on the Continuous Ranked Probability Score (CRPS), a hierarchical scoring system is formed among these entities, CA–EP–GENCO. As CA receives the dynamic day-ahead pricing signal from EP, it will schedule the household appliances to lower price period and report the prediction in a form of a probability distribution function to EP. EP, in similar way reports the aggregated demand prediction to GENCO. Finally, GENCO computes the base discount after running a cost-optimization problem. GENCO will reward EP with a fraction of discount based on their prediction accuracy. EP will do the same to CA based on how truthful they were reporting their intentions on device scheduling. The method is tested on real data provided by Ontario Power Company and we show that this scheme is capable to reduce energy consumption and consumers’ payment. |
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| Keywords: | Smart grid Demand response Incentive design Scoring rule Energy management |
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