WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 23Citation - Scopus: 29Optimal Control of Microgrids With Multi-Stage Mixed-Integer Nonlinear Programming Guided Q-Learning Algorithm(State Grid Electric Power Research inst, 2020) Yoldas, Yeliz; Goren, Selcuk; Onen, AhmetThis paper proposes an energy management system (EMS) for the real-time operation of a pilot stochastic and dynamic microgrid on a university campus in Malta consisting of a diesel generator, photovoltaic panels, and batteries. The objective is to minimize the total daily operation costs, which include the degradation cost of batteries, the cost of energy bought from the main grid, the fuel cost of the diesel generator, and the emission cost. The optimization problem is modeled as a finite Markov decision process (MDP) by combining network and technical constraints, and Q-learning algorithm is adopted to solve the sequential decision subproblems. The proposed algorithm decomposes a multi-stage mixed-integer nonlinear programming (MINLP) problem into a series of single-stage problems so that each subproblem can be solved by using Bellman's equation. To prove the effectiveness of the proposed algorithm, three case studies are taken into consideration: (1) minimizing the daily energy cost; (2) minimizing the emission cost; (3) minimizing the daily energy cost and emission cost simultaneously. Moreover, each case is operated under different battery operation conditions to investigate the battery lifetime. Finally, performance comparisons are carried out with a conventional Q-learning algorithm.Conference Object Citation - WoS: 13Citation - Scopus: 15Dynamic Rolling Horizon Control Approach for a University Campus(Elsevier, 2022-04) Yoldas, Yeliz; Goren, Selcuk; Onen, Ahmet; Ustun, Taha SelimAn energy management system based on the rolling horizon control approach has been proposed for the grid-connected dynamic and stochastic microgrid of a university campus in Malta. The aims of the study are to minimize the fuel cost of the diesel generator, minimize the cost of power transfer between the main grid and the micro grid, and minimize the cost of deterioration of the battery to be able to provide optimum economic operation. Since uncertainty in renewable energy sources and load is inevitable, rolling horizon control in the stochastic framework is used to manage uncertainties in the energy management system problem. Both the deterministic and stochastic processes were studied to approve the effectiveness of the algorithm. Also, the results are compared with the Myopic and Mixed Integer Linear Programming algorithms. The results show that the life span of the battery and the associated economic savings are correlated with the SOC values. (c) 2021 The Author(s). Published by Elsevier Ltd.