Designing an Efficient and Incentive-Compatible Mechanism of Self-Adjusting in the Smart Power Grid

Articles in Press

Document Type : Research Article

Authors

1 Non Government Higher Education Institute of Fazilat, Semnan, Iran

2 Department of Economics, Semnan University, Semnan, Iran

3 School of Engineering, Damghan University, P.O. Box 36716-41167, Damghan, Iran

4 Department of Mathematics, Semnan University, P.O. Box 35195-363, Semnan, Iran

10.22128/ansne.2026.3234.1191

Abstract

Given the increasing challenges in electricity supply and the necessity of optimizing energy consumption in public institutions, this article designs an efficient and incentive-compatible self-regulating mechanism in the smart electricity grid (based on mechanism design theory) to manage electricity consumption in public governmental institutions. Unlike existing mechanisms that rely on direct supervision or fixed quotas, our approach introduces a composite permitted ceiling that dynamically adapts to each institution's historical performance and operational constraints. The aim of this article is to design a mathematical model and create a mechanism through which agents (public governmental institutions) voluntarily and without coercion choose desirable and optimal consumption behavior. The proposed mechanism encourages agents to reduce consumption and adhere to the permitted ceiling without direct supervision. Our model achieves an improvement in energy balance compared to traditional fixed-ceiling approaches while maintaining voluntary participation.  The proposed mechanism encourages agents to reduce consumption and adhere to the permitted ceiling without direct supervision. The proposed mechanism includes a composite permitted ceiling, mission coefficient, and a system of rewards and penalties that aligns with the interests of each institution and leads to the reform of consumption behavior.

Keywords

Main Subjects

Analytical and Numerical Solutions for Nonlinear Equations

Articles in Press, Accepted Manuscript
Available Online from 13 April 2026

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History

  • Receive Date: 29 January 2026
  • Revise Date: 25 March 2026
  • Accept Date: 07 April 2026
  • Publish Date: 13 April 2026

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