Scenario-based stochastic operation management of MicroGrid including Wind, Photovoltaic, Micro-Turbine, Fuel Cell and Energy Storage Devices

• Investigation of renewable MicroGrid in a scenario-based stochastic framework for the first time.
• Introduction of a novel adaptive modification procedure to amend the Firefly Algorithm (FA).
• Investigating the role of storage devices to reduce the total cost of energy under three strategies for 24 h.
• Utilization of Adaptive Modified FA for the first time to solve the renewable MG.
• Considering the uncertainty of load forecast error, Wind Turbine (WT) and Photovoltaic (PV) generation and market price.

In this paper, an efficient stochastic framework is proposed to investigate the effect of uncertainty on the optimal operation management of MicroGrids (MGs). The proposed stochastic framework would concurrently consider the uncertainties of load forecast error, Wind Turbine (WT) generation, Photovoltaic (PV) generation and market price. The proposed stochastic method consists of two main phases. In the first phase, by the use of Probability Distribution Function (PDF) of each uncertain variable and roulette wheel mechanism, several scenarios are generated. Now by the use of scenario reduction process, the most probable and dissimilar scenarios are selected. By means of this strategy, the stochastic problem is converted to a number of deterministic problems with different probabilities. In this regard, the Weibull and normal PDFs are utilized to model the stochastic random variables. In the second phase, a new optimization strategy based on Adaptive Modified Firefly Algorithm (AMFA) is employed to solve each of the deterministic problems generated in the first phase. The stochastic optimization problem is investigated while meeting different equality and equality constraints. In order to see the efficiency and satisfying performance of the proposed method, a typical grid-connected MG including WT/PV/Micro-Turbine/Fuel Cell and Energy Storage Devices is studied as the test system.