Search

In order to prevent wastage of generated power of renewable resources, the energy storage systems can be utilized in the stand‐alone micro grids to store the excess produced power of the renewable generation units. When the generated power of the renewable resources is less than the required load, the energy storage systems can help to compensate all or part of the power shortage. In the current study, a stand‐alone micro grid including wind and tidal turbines, PV systems, batteries and fuel‐based generation units is considered to supply the required load of the micro grid. The generated power of each dispatch‐able generation units is determined in such a way as to minimize the operating cost. In the operating cost of the micro grid, the operating cost of the fuel‐based generation units and the reliability cost associated to the penalty of the curtailed loads are considered. To calculate the reliability cost of the micro grid, a comprehensive reliability evaluation of the micro grid considering the resource‐dependent failure rates for all composed components is performed. To study the effectiveness of the proposed reliability‐based scheduling approach, the numerical results associated to a stand‐alone micro grid containing wind, tidal, PV and fuel‐based generation units connected to the batteries are given. [ABSTRACT FROM AUTHOR]

Due to the advantages of micro‐grids including power losses and voltage drops reduction, reliability improvement and reduction in transmission network cost, numerous clean micro‐grids including renewable resources such as wind, tidal and solar are developed in different countries of world. The investment cost of the renewable energy‐based generation units especially tidal barrages is high, and to generate the cost‐effective electricity from the renewable resources, the optimization process should be performed. In this paper, optimal planning of a micro‐grid containing energy storage device and new mixture of renewable resources including tidal barrage and photovoltaic system is performed. For this purpose, optimal characteristics of barrage type tidal plant including number of turbines, sluices and hydro‐pumps, turbine tip and hub diameters and sluice width are determined to maximum energy of tidal plant is generated. Then, number of photovoltaic systems and batteries are obtained to supply the required load in minimum cost. To optimize the objective functions, different heuristic approaches including particle swarm, genetic and imperial competitive algorithms (ICAs) are applied, in the paper. To study the effectiveness of the proposed approach, optimal planning of a micro‐grid is performed. It is deduced from the numerical results that the particle swarm method has performed best in determining the optimal solution. [ABSTRACT FROM AUTHOR]

A suitable mixture of renewable resources including wind, tidal and photovoltaic units can be used in the microgrids installed in coastal areas or islands. However, the variation in the renewable resources such as wind speed, tidal current speed and solar radiation is significant that affects the reliability performance of these microgrids. Thus, to accurately evaluate the reliability of the microgrids, the failure rate of composed components affected by the variation in the renewable resources must be considered. To study the impact of variation in the temperature and renewable resources on the failure rate of components, different equations including Arrhenius law, temperature modification factor, fatigue strength, bending and contact stress, limit state function of turbine, thermal loss of semiconductor devices, the temperature rise of transformer and cable, the temperature coefficient of voltage and power of photovoltaic panels are developed. According to the developed equations, the components failure rate, and consequently the failure rate of the microgrid considering the variation in the temperature and renewable resources are determined. Then, by simulation, the impact of different energy sources on the failure rate of the whole system is evaluated and the reliability in a microgrid consisting of offshore renewable energy sources will be studied. [ABSTRACT FROM AUTHOR]

As an independent unit, microgrid operator (MGO) should respond to the energy demand of customers with an optimal provision cost. Apart from the ability to guarantee the security of microgrid (MG) operation, the MGO should consider the greenhouse emission effects as well. This paper investigates a novel energy management system for an islanded MG. In the proposed strategy, two efficient methodologies are used to maximize the profit and security of the MG: (a) the optimal operation of electric vehicles (EVs) in vehicle‐to‐grid (V2G) mode and (b) the use of demand response (DR) program. Besides, a hierarchical control structure is proposed to manage frequency and voltage uncertainties in a permissible range. Improving the reliability of the MG is another goal of the proposed strategy, which is pursued by the studied controlling framework. The proposed approach is evaluated through a set of simulation and GAMS tests. Results indicate that the frequency deviation of the MG is damped through the proposed management strategy and place the spotlight on the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

• Proposing a stochastic framework for the optimal operation of microgrids with DR. • Proposing a motivating scheme for consumers to participate in the DR plan. • Proposing a new formulation for the security margin in the direct control of customers. This article assesses the optimal operation and management of the microgrids considering the dispatchable units, demand response (DR) and uncertainty effects. A new formulation is developed which not only models the DR benefits, but also handles the air pollutions due to the power units operation. Moreover, a new term is added to the objective function which incorporates the customers discomfort due to the DR plans. The overall social welfare objective function consists of DGs operation and storage costs, the cost of utilizing the hydrogen tank and other DG resources, the cost of pollutions and the cost of discomfort function. In order to solve the above nonlinear problem, a new optimization method based on particle swarm optimization and a novel three-phase modification method is introduced. The discomfort behavior is modeled using the Taguchi function to convert the DR time interval usages with real cost. In order to have a practical analysis, the time of use (TOC) electricity tariff is also deployed by the upstream network in the DR programs. The proposed method is then implemented on a sample network and validated in four different scenarios of operation. The simulation results show the high performance, and effectiveness of the proposed formulation for the DR problem in the microgrids. It is seen that the DR program with optimal power scheduling could reduce around 30 % in operating costs and about 12 % in the air pollution. In addition, it is seen that although considering the emission as an objective function can increase the operation costs, but the DR program can play a significant role in mitigating the additional operating cost. Moreover, both cost and emission functions increased by modeling the uncertainty effects through the proposed point estimation approach. [ABSTRACT FROM AUTHOR]