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In this article, the robust scheduling of the distribution network is presented considering electric vehicles, distributed generation, and energy storage, in which the energy management of the mentioned elements is considered, and also only one scenario is needed. The proposed deterministic problem is an optimization problem whose objective function is equal to minimizing energy cost. Also, the limitations of the problem are equal to the power flow equations of the network, the limitations of the technical indicators of the network such as the voltage of the buses and the passing power of the lines, the operation equations of electric vehicles, energy storages, and distributed generation. It is worth mentioning that the mentioned problem is non-linear. In the following, to achieve the global optimal point with a high solution speed, the linear model of the mentioned problem is presented with a very low calculation error. In this research, the uncertainty parameters of the problem are equal to active and reactive loads, energy prices, parameters of electric vehicles, and renewable productions. Finally, to simplify the decision-making of the distribution network operator, a robust model of the mentioned problem was presented. Finally, the proposed problem is applied to the IEEE standard 33-bus radial distribution network using GAMS optimization software, and then the capabilities of the proposed design are evaluated. [ABSTRACT FROM AUTHOR]

The increasing pollution caused by conventional cars and the problems caused by the use of fossil fuels have drawn the attention of researchers and manufacturers to the design of cars that use clean fuels. Electric vehicles connected to the network have a significant impact on reducing environmental pollution and transportation costs, especially in big cities. The cost of supplying loads to subscribers in the distribution network also includes generation and transmission costs. These costs are directly related to the intelligence of the distribution network and the total amount of energy of electric vehicles. The contribution of each generation unit and each transmission line must be calculated to determine the generation and transmission costs. In this research, in order to maximize the profit of the parking lot owner, improve voltage drop and load factor, a comprehensive framework for optimal energy management in a parking lot is presented, which can provide a method to control the charging of electric vehicles, in addition to meeting the needs of their owners, only as a series of controllable loads that they need to receive electrical energy to charge their batteries. In the next step, considering the inherent characteristic of electric cars, i.e. having a battery, and looking at them as a series of storage resources that can return the electric energy in their battery to the grid if necessary, a method to simultaneously control their charging and discharging is provided. In the final step of the paper, it is assumed that hydrogen storage systems will also enter the circuit, and thus, a comprehensive method for energy management is proposed. Finally, the linearized model of demand response and the proposed scheme along with the modeling of hydrogen storage and electric vehicles are considered to be part of contribution to improve the operation and economic situation of the network. • In practice, the high cost that battery depreciation imposes on car owners when using the V2G feature makes the use of this feature not economically justified. • A comprehensive framework for optimal energy management in a parking lot with the aim of maximizing the profit of the parking lot owner, improving the voltage drop and network power factor is provided. • The proposed method for energy management in the presence of hydrogenous storage systems was applied in a sample parking lot and how it works. • Considering the hydrogenous storage systems, while significantly increasing the profit of the parking lot owner, it also significantly reduces the power received from the network during the peak hours of the network. [ABSTRACT FROM AUTHOR]

With the creation of competitive environments, such as electricity market, it is expected that energy networks and active consumers such as energy hubs participate in the market to promote their economic situation. So, the article proposes the optimal involvement of energy networks and hubs in energy markets in two wholesale and retail designs based on the energy management system at the same time. The proposed scheme is expressed as two-objective optimization. The first objective is to minimize the cost of different types of energy in electricity-gas-thermal networks. In another objective function, the cost of energy (which is the difference between the energy purchase cost and energy sale income) of energy hubs in the retail market is minimized. The scheme is bound to optimal power flow equations of the mentioned networks and operating model of power sources and active loads. Then, the Pareto optimization mixed with the sum of weighted functions helps extract an optimal compromise solution on the basis of fuzzy decision-making. Finally, the scheme is applied to a test system, and the obtained numerical results confirm that energy hubs are improved financially, and economic and operation conditions of the electricity-gas-thermal networks are enhanced simultaneously. So, significant profit can be achieved for EHs in the retail energy market. The economic situation of the networks enhances up to roughly 10% compared with that of power flow studies. Also, operating situation of the networks enhances by about 12% to 53% compared with a case without EHs. [ABSTRACT FROM AUTHOR]

• ESS scheduling has been performed in both weekly and daily modes. • Different operating strategies has been assessed. • Stochastic models of parameters in the MO scheduling are taken into account. • Impact of parameters of EES on reliability determined. Energy storage systems (ESSs) are useful devices to ensure the reliable operation of microgrids especially those with high penetration of renewable energies. The microgrid operation is highly associated with scheduling of ESS units. Therefore, in this paper, a new algorithm for ESS scheduling has been suggested in order to manage MG in a reliable manner. Because reliability considering and cost minimization are conflicting objectives in ESS scheduling, the multi-objective optimization problem should be solved for optimal scheduling of ESS. Different operating strategy have been considered and their impact on ESS scheduling in the microgrid has been investigated. In order to properly consider the uncertainties associated with the multi-objective scheduling problem, probabilistic models have been presented for the parameters in the network and they are expressed as mixed integer linear programming (MILP) problems. Non-dominated sorting teaching learning-based optimization (NSTLBO) algorithm is employed to solve the MO problem. Scheduling plan is performed on both weekly and daily horizons in connected/islanding microgrid modes. By implementing this method on a modified 33-bus IEEE test system, the results endorse the effectiveness of the proposed scheme for enhancing the reliability of MGs. [ABSTRACT FROM AUTHOR]