Volume 7, Issue 2, December 2019, Page: 29-36
Minimization of Total Operation Cost and the Risk of Shedding in Microgrids
Ahmed R. Abul'Wafa, Electric Power and Machines, Ain-Shams University, Cairo, Egypt
Received: Oct. 20, 2019;       Accepted: Nov. 13, 2019;       Published: Nov. 20, 2019
DOI: 10.11648/j.net.20190702.13      View  432      Downloads  81
Abstract
The objective of this paper is to determine and minimizes the total operation cost and the risk of load shedding in a microgrid (μG) composed of two areas: a generation center and a load center. The system operation is formulated as an optimization problem, where the objective function minimizes the costs of the system operation and the risk of load shedding. The constraints secure the balance between generation and load. Also generation and transmission may not exceed the available capacity. Monte Carlo simulation (MCS) is used for the solution of the optimization problem giving two main outputs: loss of load occasion (LOLO) and total operation cost (TOC). A variance reduction technique is used to reduce the variance of MCS. One other objective of the paper is to study how much the simulation efficiency can be improved by introducing variance reduction techniques. Simulation results shows that, (i) the formulated optimization problem, objective function, and constraints is capable to achieve the study target, and (ii), with even a quite straightforward and simple model the proposed MCS methods show considerable variance reductions compared to Simple sampling in this model of the μG.
Keywords
Micro Grid, Monte Carlo Simulation, Variance Reduction Techniques, Optimization, Operation Costs, Load Shedding, Distribution System Planning, Dispersed Generation, Power System Management
To cite this article
Ahmed R. Abul'Wafa, Minimization of Total Operation Cost and the Risk of Shedding in Microgrids, Advances in Networks. Vol. 7, No. 2, 2019, pp. 29-36. doi: 10.11648/j.net.20190702.13
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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