Recent Study on Optimal Economic Dispatch in Microgrids with Renewable Energy Sources| Chapter 3 | New Insights into Physical Science Vol. 8

 The use of microgrids receives more interest in the scientific community due to the opening of the energy market and the agreements for the reduction of pollution emissions, but the management of the delivery of electricity has new challenges. As a main component of designing a microgrid, this paper considers various distributed generation systems and the management of resources is described over a period through the proposed dynamic economic dispatch approach. The inputs are obtained by the model predictive control algorithm, taking into account variations in both the consumption trend and the capability of generation systems, including traditional and renewable energy sources. In addition , the proposed solution considers a consumer benefit programme involving the limitation of demand and the regeneration costs of the pollutants generated by traditional generating systems. Via a mathematical programming approach, the dispatch strategy aims to minimise to the minimum the fuel costs of traditional generators, the energy transactions, the regeneration of polluted emissions and, eventually, includes the advantage of reducing electricity demand by mathematical programming strategy, fulfilling all constraints. LINGO 17.0 programme (Lindo Systems, 1415 North Dayton Street, Chicago, IL , USA) implements the model. The findings show the suggested approach efficacy under various considerations through a study case. Improving the operation of the analysed microgrid is accomplished because various variables and potential scenarios of loads and renewable energy production capability are included in the proposed problem formulation. The results obtained by the proposed algorithm in 24 review periods during the study interval ensure that the performance adjustment level of each microgrid generator can be specified at the best possible value.

Author(s) Details

F. Daniel Santillán-Lemus
Postgraduate Department, Polytechnic University of Tulancingo (UPT), Tulancingo 43629, Mexico.

Hertwin Minor-Popocatl
School Engineering and Business (Postgraduate), Popular Autonomous University of the State of Puebla (UPAEP), Puebla 72410, Mexico.

Omar Aguilar-Mejía
School Engineering and Business (Postgraduate), Popular Autonomous University of the State of Puebla (UPAEP), Puebla 72410, Mexico.

Ruben Tapia-Olvera

Department of Electric Power, National Autonomous University of Mexico (UNAM), CDMX 04510, Mexico.

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