Energy scheduling of renewable integrated system with hydrogen storage in distribution grid including charging and...

In this article, the energy management of the intelligent distribution system with charging stations for battery-based electric vehicles (EVs) and plug-in hybrid EVs, hydrogen station for fuel cell-based EVs, and renewable integrated energy systems (IESs) with hydrogen storage devices in accordance with the estimation of economic, operational, security and environmental goals of distribution system operator is presented. Hydrogen storage is used to store electric energy and feed hydrogen consumers. The methodology adopted here is expressed as a multi-objective formulation to be solved. Objective functions are minimizing the cost of buying energy by distribution system from the upstream network, minimizing distribution system energy losses, minimizing environmental emissions, and maximizing voltage security in the distribution system. In this issue, AC power flow model, operation and voltage security boundaries in the network, performance model of charging station for EVs, hydrogen station model for fuel cell vehicles, and renewable IES operation model with hydrogen storage is the boundaries specific to the problem. The problem in the single-objective model uses the Pareto optimization that relies on the sum of weighted functions method. Next, the fuzzy decision-making technique extracts an optimal compromised solution between the operational, economic, security and environmental objectives of the network operator. In the present scheme, load, energy prices, renewable phenomena, electric vehicles have uncertainty. In this article, stochastic optimization based on Unscented Transform is incorporated to provide a suitable modeling of the uncertain parameters appearing in the problem. Modelling of the performance of EVs charging station and hydrogen fulling station, using hydrogen storage as electricity energy storage and feeding hydrogen loads, energy management of renewable bio-waste and tidal units in IES, considering the different objectives of network operator, and using Unscented Transform approach to model of uncertainty parameters are the innovations of this article. Findings show that the method improves the technical, environmental and economic conditions of the grid, and the integrated system with its optimal performance is able to enhance the economic, environmental, security and operation status of the distribution system up to roughly 45.8%, 38%, 32-45% and 10.6%, respectively.