Agent-Based system for microgrid power real-time pricing with client preferences

Abstract

Microgrid technology is actually the most practical way for Distributed Energy Resources (DERs) deployment in urban and rural communities. The factors that motivate reliance to the microgrid technology include energy security, economy and environment. The economical sustainability of microgrids depends on the energy market within a community. This can be challenged by issues related to the scalability of the microgrid and the setting up of a pricing system. Various energy management systems and energy pricing methods developed so far offer little or no option to the end user/client to accept or reject the proposed price. Thus, this paper presents a client focused agent that automatically negotiates various available economical options in real-time pricing context within a microgrid. The proposed agent collects and analyses the prices as communicated by the microgrid network operator. Moreover, based on client predefined preferences, it regulates the client load demand in a predefined sequence with the aim of minimizing the power consumption during high price period. Therefore, the proposed system will reduce the client overall energy cost and contributes towards demand side management from the network operator perspective. The agent mathematical model and algorithm are simulated in MATLAB environment. The findings of the study demonstrate the effectiveness of the proposed agent approach in offering the client a real-time control over the energy cost control in a microgrid context.