Game-theoretical energy management design for smart cyber-physical power systems

Abstract

In this paper, we consider the energy management problem for smart cyber-physical power systems with conventional utility companies, microgrids (MGs) and customers. We have adopted a game-theoretical approach to model the problem as a hierarchical game, which takes the interactions and interconnections among utility companies, MGs and customers into consideration. We have considered two completely different situations depending on whether utility companies can enforce their strategies upon MGs and customers, and have modelled the problem as a two-stage Stackelberg game and three-stage Stackelberg game, respectively. The backward induction method is used to analyse the proposed games and closed-form expressions are derived for optimum strategies. We prove that there exists a unique Nash equilibrium for each non-cooperative price competition game, and these Nash equilibria constitute the Stackelberg equilibrium. Simulation results show the effectiveness of the proposed algorithm and the relationships among system parameters.

Game Theoretical Energy Management with Storage Capacity Optimization and Photo-Voltaic Cell Generated Power Forecasting in Micro Grid

“…Similarly in case of wind turbine, speed of wind goes up any time and become stronger, which will cause grid frequency goes up [14]. Therefore, dynamics of energy generation behavior of renewable resources can not be ignored [17][18][19]. Literature work is restricted to limited application of MG, where real world data is not considered while managing energy distribution.…”

Autonomous monitoring framework for resource-constrained environments

“…In comparison, an event or time-driven scheme that involves periodic data communications will result in relatively higher energy consumption. Proposed methods have ranged from the use of complex sensors [7], through efficient relay node selection [8], to cooperative data gathering [9] and game-theoretical energy management designs [10]. However, each approach addresses a specific application and none introduce a general framework to guide balancing the energy cost of onboard image processing with that of communication.…”

SAI: A Suspicion Assessment-Based Inspection Algorithm to Detect Malicious Users in Smart Grid

“…information and communication technologies), smart grid significantly improves power systems' performance in reliability, economics, and efficiency [1], [2]. However, advanced hardware and software techniques also bring smart grid many vulnerabilities, among which security concerns garner the most attentions [3].…”

“…The SAI algorithm can deal with static cases where new malicious users appear during the inspection process as well as dynamic cases in which new malicious users do not appear. The major contributions of this paper are highlighted as follows: (1) We assess suspicions that users steal electricity through analyzing prior records as well as consumption deviations; (2) We propose the SAI algorithm, by which users with the highest suspicions will be first probed individually. Then, the remaining users will be probed by a binary tree based inspection strategy; (3) Experiment results show that the SAI algorithm outperforms existing methods.…”

“…Electricity theft is defined as using electricity from utility companies through totally or partially bypassing metering system or interfering this system to adulterate its measurement 2. The users stealing electricity are referred to as "malicious users".1556-6013 © 2019 IEEE.…”