Corrections to “A Privacy-Preserving Online Learning Approach for Incentive-Based Demand Response in Smart Grid” [Dec 19 4208-4218]

Chen, Wenbo; Zhou, Anni; Gao, Liang; Ji, Shouling; Wu, Dapeng

doi:10.1109/jsyst.2019.2938641

Cited by 2 publications

(1 citation statement)

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“…In this paper, an algorithm to share the benefit of micro-grid operator among demand resource providers is presented considering the IB DR program. A privacy-preserving algorithm for selecting the most promising consumer for IB DR is presented in [27]. A compensation scheme considering the inconvenience parameter, is proposed in [28] for residential consumers.…”

Section: A Related Workmentioning

confidence: 99%

A Game-Theoretic Energy Scheduling Scheme with Price-Based and Incentive-Based Demand Response Programs

Gaba¹,

Chanana²,

Ismail³

2020

IJCDS

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Demand response (DR) is playing a revolutionary role in changing the way demand at the distribution end is managed. In the literature, a number of centralized energy management schemes have been discussed. Due to large computational overload and privacy concerns in the centralized schemes, distributed schemes are being preferred over centralized schemes. In this paper, an energy scheduling problem (ESP) considering the impact of price-based (PB) and incentive-based (IB) DR programs is presented. The combined effect of PB and IB based DR programs with load-limiting strategy is observed on electricity cost, comfort and system load. In PB DR program, the user is charged according to a quadratic cost function whose coefficients depend on time-of-use pricing. In the IB DR program, an incentive/discount rate is applied to the consumers during peak hours. In PB and IB DR program with a peak limit, the ESP is implemented using a Nash equilibrium problem with pricing. Asynchronous Proximal Decomposition algorithm with shared constraint is implemented to obtain the optimal appliance schedule. In the end, analysis of system load profile, system cost and consumer cost in different cases is performed. The comfort of the consumers is also monitored using a discomfort index. The outcomes of the proposed scheduling scheme are compared with a mixed integer linear programming (MILP) based scheduling scheme proposed in literature. It has been observed that the proposed strategy is useful in reducing load during peak hours and minimizing the electricity bills for residential consumers.

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Section: A Related Workmentioning

confidence: 99%