Achieving Optimality and Fairness in Autonomous Demand Response: Benchmarks and Billing Mechanisms

Baharlouei, Zahra; Hashemi, Massoud Reza; Narimani, Hamed; Mohsenian‐Rad, Hamed

doi:10.1109/tsg.2012.2228241

Cited by 156 publications

(126 citation statements)

References 14 publications

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“…The proposed method can not only cut down the total cost of all users, as well as each users electricity payment, but also reduce the value of the peak-to-average ratio (PAR). Moreover, the authors in [2] introduced the concept of fairness into the users' utility functions, then designed new autonomous demand response systems that can achieve both optimality and fairness with a smart electricity billing mechanism.…”

Section: Related Workmentioning

confidence: 99%

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Autonomous Household Energy Management Based on a Double Cooperative Game Approach in the Smart Grid

et al. 2015

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Taking advantage of two-way communication infrastructure and bidirectional energy trading between utility companies and customers in the future smart grid (SG), autonomous energy management programs become crucial to the demand-side management (DSM). Most of the existing autonomous energy management schemes are for the scenario with a single utility company or the scenario with one-way energy trading. In this paper, an autonomous household energy management system with multiple utility companies and multiple residential customers is studied by considering the bidirectional energy trading. To minimize the overall costs of both the utility companies and the residential customers, the energy management system is formulated as a double cooperative game. That is, the interaction among the residential users is formulated as a cooperative game, where the players are the customers and the strategies are the daily schedules of their household appliances; and the interaction among the utility companies is also formulated as a cooperative game, where the players are the suppliers and the strategies are the proportions of the daily total energy they provide for the customers. Without loss of generality, the bidirectional energy trading in the double cooperative game is formulated by allowing plug-in electric vehicles (PEVs) to discharge and sell energy back. Two distributed algorithms will be provided to realize the global optimal performance in terms of minimizing the energy costs, which can be guaranteed at the Nash equilibriums of the formulated cooperative games. Finally, simulation results illustrated that the proposed double cooperative game can benefit both the utility companies and residential users significantly.

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Section: Related Workmentioning

confidence: 99%

“…Demand-side management (DSM) generally refers to such activities implemented to improve energy efficiency, to reduce cost at the customer side and to control the energy consumption [1,2]. DSM was actually put forward 30 years ago [3][4][5], but it did not attract enough attention until the smart grid (SG) concept came.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Household Energy Management Based on a Double Cooperative Game Approach in the Smart Grid

et al. 2015

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“…The authors in [33] proposed a fairness demand response (FDR) scheme to consider the satisfaction of individual users and the energy provider. Later, an autonomous demand response (DR) model is proposed in [34] to design a fair billing mechanism for different users. The users are rewarded fairly based on their contributions in achieving the system objectives.…”

Section: Related Workmentioning

confidence: 99%

Achieving Cost Minimization and Fairness in Multi-Supplier Smart Grid Environment

et al. 2018

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Abstract:In this paper, we study the energy management techniques in the smart grid with multiple energy providers. We seek to minimize the electricity cost. In this paper, the desired objectives are achieved through scheduling of different consumers to different utilities at different time slots. We consider a practical system where multiple users can be allocated to a single utility, but, a user cannot be assigned to more than one utility. As a first goal, we formulate a sum cost minimization problem subject to independent generation capacity of each utility. A dual decomposition approach is exploited to find an efficient solution where the sub-gradient approach is adopted to update the dual variables. Later, a min-max based optimization framework is adopted to achieve the fairness among different customers. Moreover, suboptimal schemes are also designed to reduce the computational complexity. Simulation results are presented to validate the performance of the proposed solutions.

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“…In order to improve the functions of smart grids on the demand side, the concept of demand-side management (DSM) is proposed to reduce the energy cost of consumers, shift energy consumption from peak hours to reduce peakto-average ratio (PAR) and balance power supply and demand [7][8][9]. DSM programs can be conducted effectively primarily due to their dynamic pricing schemes such as time-of-use (ToU) pricing [10], real-time pricing (RTP) [11] and critical-peak pricing.…”

Section: Introductionmentioning

confidence: 99%

Game-theoretic energy management with storage capacity optimization in the smart grids

Gao

Liu

Wei

et al. 2018

J. Mod. Power Syst. Clean Energy

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With the development of smart grids, a renewable energy generation system has been introduced into a smart house. The generation system usually supplies a storage system with the capability to store the produced energy for satisfying a user's future demand. In this paper, the main objective is to determine the best strategies of energy consumption and optimal storage capacities for residential users, which are both closely related to the energy cost of the users. Energy management with storage capacity optimization is studied by considering the cost of renewable energy generation, depreciation cost of storage and bidirectional energy trading. To minimize the cost to residential users, the non-cooperative game-theoretic method is employed to formulate the model that combines energy consumption and storage capacity optimization. The distributed algorithm is presented to understand the Nash equilibrium which can guarantee Pareto optimality in terms of minimizing the energy cost. Simulation results show that the proposed game approach can significantly benefit residential users. Furthermore, it also contributes to reducing the peak-to-average ratio (PAR) of overall energy demand.

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Achieving Optimality and Fairness in Autonomous Demand Response: Benchmarks and Billing Mechanisms

Cited by 156 publications

References 14 publications

Autonomous Household Energy Management Based on a Double Cooperative Game Approach in the Smart Grid

Autonomous Household Energy Management Based on a Double Cooperative Game Approach in the Smart Grid

Achieving Cost Minimization and Fairness in Multi-Supplier Smart Grid Environment

Game-theoretic energy management with storage capacity optimization in the smart grids

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