Journal Article

Optimal probabilistic scenario‐based operation and scheduling of prosumer microgrids considering uncertainties of renewable energy sources

Hashemi‐Dezaki, Hamed, Faraji, Jamal, Ketabi, Abbas

2020

Overview

Uncertainties of renewable energy sources (RESs) such as wind turbine (WT) and photovoltaic (PV) units are one of the considerable challenges of prosumer microgrids (PMGs) for the optimal day‐ahead operation. In this study, a new probabilistic scenario‐based method of optimal scheduling and operation of PMGs is developed. In this regard, different scenarios are generated using Monte Carlo Simulations (MCS). Furthermore, k‐means, k‐medoids, and differential evolution algorithms (DEA) are deployed to cluster the scenarios in the proposed method. A realistic commercial PMG in Iran is selected to apply the introduced method. The validity of the developed probabilistic optimization method for PMG operation is examined by comparing the results under various scenario reduction algorithms and MCS ones. The comparison of the obtained results and those of other existing deterministic methods highlights the advantages of the presented method. Furthermore, the sensitivity analyses are carried out to investigate the robustness of the developed method against the increase in the system uncertainty level. According to the test results, it is concluded that the k‐medoids algorithm has the best performance in comparison with the k‐means and the DEA‐based clustering under various conditions. Proposing a novel scenario‐based O.F to optimize the operation costs of prosumers. Comparison of the proposed method and other available deterministic ones. Comparison of different scenario reduction methods. Validation of the scenario reduction‐based method by using MCS. Investigation of the proposed method robustness against the uncertainty increment.

• Publisher: John Wiley & Sons, Inc,Wiley
• Subject: Accuracy / Algorithms / Alternative energy sources / Case studies / Clustering / differential evolution algorithm (DEA) / Distributed generation / Electric vehicles / Electricity / Energy industry / Energy management / Energy resources / Evolutionary algorithms / Evolutionary computation / k‐means algorithm / k‐medoids algorithm / Methods / Monte Carlo simulation / Monte Carlo simulation (MCS) / optimal scenario‐based operation and scheduling / Optimization / Photovoltaic cells / Photovoltaics / Probability theory / prosumer microgrids (PMGs) / Renewable energy sources / Renewable resources / scenario reduction method / Scheduling / Sensitivity analysis / Stochastic models / Turbines / Uncertainty / Wind power / Wind turbines