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Dynamic Multi-Carrier Microgrid Deployment Under Uncertainty

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  • Amir, Vahid
  • Azimian, Mahdi

Abstract

An accurate assessment of microgrid economic benefits is a challenging task due to various uncertain data involved in the assessment. This paper scrutinizes the economic viability of multi-carrier microgrid deployments under various uncertainties, incorporating smart grid technologies, namely dispatchable and nondispatchable resources, energy storage devices, and demand response programs. The optimal type, size, and commissioning year of the available distributed energy resources along with economic utilization of selected resources are assessed to be implemented in the proposed multi-carrier microgrid. In this study, the stochastic multi-objective function comprises the net present value costs associated with the multi-carrier microgrid investment and installation, operation, maintenance, emission, incentive and penalty payments, and contracted power between multi-carrier microgrid owner and local utility company. Furthermore, an economic model for time-based demand response programs along with voluntary and mandatory demand response programs is developed innovatively. It correlates the local energy price of elastic loads for electrical and thermal carriers with day-ahead hourly pricing, energy import amounts, and on-site generations. The proposed dynamic planning problem under uncertainties of electrical and thermal loads, electricity price, and solar irradiation is solved by using a two-stage stochastic programming method that combines the genetic algorithm of MATLAB and the mixed-integer nonlinear programming model of GAMS software. Numerical simulation analyses demonstrate the effectiveness of the proposed multi-carrier microgrid expansion planning problem from the economic, environmental, and technical points of view.

Suggested Citation

  • Amir, Vahid & Azimian, Mahdi, 2020. "Dynamic Multi-Carrier Microgrid Deployment Under Uncertainty," Applied Energy, Elsevier, vol. 260(C).
  • Handle: RePEc:eee:appene:v:260:y:2020:i:c:s0306261919319804
    DOI: 10.1016/j.apenergy.2019.114293
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