Open AccessDecentralised voltage control with built‐in incentives for participants in distribution networks
Author(s) -
Wang Xiaoxue,
Wang Chengshan,
Xu Tao,
Guo Lingxu,
Fan Shixiong,
Wei Zechen
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0487
Subject(s) - incentive , computer science , nash equilibrium , voltage droop , profit (economics) , decentralised system , game theory , microgrid , voltage , control (management) , environmental economics , computer security , operations research , microeconomics , economics , voltage regulator , engineering , artificial intelligence , electrical engineering
In the face of unprecedented challenges in environmental sustainability and grid resiliency, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs).This study explores a decentralised voltage control method based on a multi‐agent system (MAS) with built‐in incentives for various participants in distribution networks (DNs). Without an arbitration agent in MAS, peer agents calculate voltage sensitivities via agents’ local and neighbourhood measurements in a fully decentralised approach. An incentive mechanism is designed to motivate the MGs in DNs to participate in voltage control with guaranteed subsidies to ensure individual rationality. On the basis of the voltage sensitivities, each MG decides its strategy by managing energy suppliers and consumers to maximise its own profit while providing the ancillary service of voltage control. The strategy converges through an iterative process to a Nash equilibrium which maximises each MG's profit. In addition, an incomplete information game is applied to ensure the privacy of MGs. Furthermore, the feasibility and effectiveness of the proposed voltage control method is demonstrated on a modified IEEE 33‐bus system, and finally the existence of a Nash equilibrium in the game model is proved in the Appendix.