Please use this identifier to cite or link to this item: doi:10.22028/D291-36455
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Title: Forecast-Driven Power Planning Approach for Microgrids Incorporating Smart Loads Using Stochastic Optimization
Author(s): Hijjo, Mohammed
Frey, Georg
Language: English
Title: 2018 International Conference on Smart Energy Systems and Technologies (SEST) conference proceedings
Publisher/Platform: IEEE
Year of Publication: 2018
Place of publication: Piscataway
Place of the conference: Seville, Spain
Free key words: Load modeling
Optimal scheduling
Mathematical model
Smart buildings
DDC notations: 500 Science
Publikation type: Conference Paper
Abstract: The main focus of this work is on improving the resilience of the standalone microgrids using the available forecast of both energy sources and loads, provided that some smart loads are incorporated in the system. The proposed approach assumes that the smartness of the loads facilitates an accurate prediction of their consumption as well as the possible time span for their operation. The kernel of the proposed approach is to provide a greedy-based scheduling scheme of a group of non-preemptive loads in order to reduce the net deficit between the aggregate load and the low-price power profile, and therefore, the levelized cost of energy (LCoE) can be minimized. Based on the driven forecast, the power routings between the components of the microgrid are investigated considering the scheduling candidates of the incorporated smart loads. Thus, the optimal schedule is selected so as to ensure the maximum utilization of the low-price power. A stochastic optimization method based on the genetic algorithms (GAs) is used to cut-down the massive searching space and provide the optimal schedule within a reasonable time. An illustrative example is used to carry out this work using a group of synthetically created loads representing different facilities inside a hospital in Gaza city. Simulation results show that the proposed algorithm can significantly reduce LCoE and meanwhile maximizing the utilization factor of the installed renewable energy sources.
DOI of the first publication: 10.1109/SEST.2018.8495662
URL of the first publication:
Link to this record: urn:nbn:de:bsz:291--ds-364557
ISBN: 978-1-5386-5326-5
Date of registration: 13-Jun-2022
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Systems Engineering
Professorship: NT - Prof. Dr. Georg Frey
Collections:Die Universitätsbibliographie

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