Smart grid

About: Smart grid is a research topic. Over the lifetime, 37536 publications have been published within this topic receiving 627844 citations. The topic is also known as: intelligent grid.

Power system and communication network co-simulation for smart grid applications

Abstract: The vision of a smart grid is predicated upon pervasive use of modern digital communication techniques to today's power system. As wide area measurements and control techniques are being developed and deployed for a more resilient power system, the role of communication network is becoming prominent. Power system dynamics gets influenced by the communication delays in the network. Therefore, extensive integration of power system and its communication infrastructure mandates that the two systems are studied as a single distributed cyber-physical system. This paper proposes a power/network co-simulation framework which integrates power system dynamic simulator and network simulator together using an accurate synchronization mechanism. The accuracy is tunable based on the time-scale requirements of the phenomena being studied. This co-simulation can improve the practical investigation of smart grid and evaluate wide area measurement and control schemes. As a case study an agent-based remote backup relay system is simulated and validated on this co-simulation framework.

GTES: An Optimized Game-Theoretic Demand-Side Management Scheme for Smart Grid

Abstract: Demand-side management in smart grids has emerged as a hot topic for optimizing energy consumption. In conventional research works, energy consumption is optimized from the perspective of either the users or the power company. In this paper, we investigate how energy consumption may be optimized by taking into consideration the interaction between both parties. We propose a new energy price model as a function of total energy consumption. Also, we propose a new objective function, which optimizes the difference between the value and cost of energy. The power supplier pulls consumers in a round-robin fashion and provides them with energy price parameter and current consumption summary vector. Each user then optimizes his own schedule and reports it to the supplier, which, in turn, updates its energy price parameter before pulling the next consumers. This interaction between the power company and its consumers is modeled through a two-step centralized game, based on which we propose our game-theoretic energy schedule (GTES) method. The objective of our GTES method is to reduce the peak-to-average power ratio by optimizing the users' energy schedules. The performance of the GTES approach is evaluated through computer-based simulations.