Abstract

Smart grid has generated much attention recently due to its potential in bringing a revolutionary change in the production, distribution, and utilization of power. However, before a smart grid can become fully functional, it requires technological advancements in a number of interdisciplinary domains. Even though smart grid facilitates run-time optimal allocation of power via extensive instrumentation and information accessibility, the process of optimal power allocation becomes challenging due to the massively distributed generation facilities, loads, and due to the intermittency of generation. Optimal power flow problem essentially minimizes the overall cost of power generation while meeting the total load or power demand at the consumer end. In this paper, a Market Based technique has been presented to carry out the optimal power flow in a smart grid. The Market Based Resource Allocation is inspired from the concepts in economic market, where resources are allocated to activities through the process of competitive buying and selling. In the proposed technique, consumers act as potential power buyers and generation units act as the power sellers. The proposed method derives its significance due to its ability in optimizing power flow in a grid in a distributed manner, i.e., from local interactions. This feature provides immense scalability and robustness to uncertainties. In addition, this paper presents the evaluation of the proposed Market Based technique via a simulated scenario of power consumers and producers in a Smart Grid. The IEEE 30-bus system (RTS 79) with six generation units is used to test the proposed method in optimizing the total generation cost, and the results are compared with that obtained from widely used Matpower software.

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