Conversation and assurance issues play a crucial function when talking regarding to the wise grid. This paper presents opportunities of testing power framework assurance transfers and correspondence standards for smart supply. In this paper, a depiction in the Smart Grid lab hardware and the key protection devices has been presented. Further employ cases and the possibilities by dynamically setting up devices and program interaction are demonstrated. Ideas for the mix of checked and controllable decentralized vitality sources are demonstrated, and the network capacity and Quality of Services (QoS) are tested and evaluated. By implementing adaptive modulation scheme, the served users were increased by 10% at heavy Traffic Load (TL).

Compared to individual DC or AC Microgrids, Hybrid Microgrids (HMGs) are more efficient and inexpensive due to the elimination of multiple DC-AC-DC conversions. In HMGs, where AC loads are supplied by a DC link, load demand disturbance has direct negative effects on the DC link voltage. In this study, primary and secondary controllers are applied to realize suitable operation conditions and control the Microgrid converters. Each converter has a primary controller to compensate for the demand power fluctuations. A secondary controller is also designed for extra demand varieties to send the proper control signals to the primary controllers. The expressed capability of the primary controllers can be obtained by designing a simple and robust secondary controller. Hence, the effects of demand fluctuations are eliminated and the system is stabilized. The overall state space model of the system is conducted for stability analysis. To demonstrate the proposed controller efficiency, a prototype HMG is modeled and simulated. The stability analysis reveals that the system is stable when the secondary controller tracks the error signal of the DC link. Simulation results show that the proposed method could efficiently manage the AC side voltage under load fluctuations.

A common method for controlling a group of parallel converters in decentralized control strategy structure in an island Microgrid, the use is the droop-down characteristics of frequency ω-P and voltage E-Q. However, the problem with using this method is that the reactive power is not properly distributed (in proportion to the capacity of the micronutrients) between the micronutrients, which may lead to overload in the converters. Microgrids may also suffer from dynamic stability problems such as power fluctuations, which can be increased by switching between active and reactive power control. To avoid this problem, the X / R ratio of transmission lines is an important parameter that should be carefully considered in the design of micronutrient controllers. By linearizing and simplifying conditions, the control system conversion function model becomes a single input-single output system, which is efficient enough to show the relationship between control parameters such as slope of droop characteristics and derivative sentences, virtual impedance, and voltage controllers. Using this model, stability conditions for different parameters are analyzed. Also, to improve power distribution stability, common droop strategies are modified by adjusting the slope as well as adding nonlinear sentence sections. This approach reduces the coupling between active and reactive power control and reduces the dependence of power distribution on grid parameters such as the X / R ratio. To evaluate the reliability of the proposed model, the simulation results in a sample island Microgrid in MATLAB software are presented.

Variation of frequency and voltage by load changes in a Microgrid is a challenge in droop control method. Centralized restoration frequency or voltage in a Microgrid requires communication link and therefore affects the advantage of decentralized droop control such as reliability, simplicity and inexpensiveness. This paper proposes a decentralized method that restores the frequency of a Microgrid without any communication link and maintains these advantages. The method detects signal changing by wavelet transform (WT) to synchronize distributed energy resource (DER) that interfaced by converter to Microgrid. Its operation principle and control method are explained and analyzed. The simulation results are presented to validate the effectiveness of the proposed method.

This paper deals with the optimal scheduling of a Microgrid (MG) equipped with dispatchable distributed generators (DGs), renewable generators and electrical storages (batteries). A chance-constrained model is developed to handle normal operation and emergency conditions of MG including DG outage and unwanted islanding. Purchasing reserve from the upstream grid is also considered. Moreover, the uncertainties of loads and renewable resources are incorporated into the model. Furthermore, a novel probabilistic formulation is presented to determine the amount of required reserve in different conditions of MG by introducing separate probability distribution functions (PDFs) for each condition. Accordingly, an index named as the probability of reserve sufficiency (PRS) is introduced. The presented model keeps a given value of PRS in normal and emergency conditions of MG operation. In addition, some controllable variables are added to the chance constraints as an innovative technique to reduce the complexity of the model. Finally, a test Microgrid is studied in different case studies and the results are evaluated.

Microgrid control in the isolated mode is a highly important subject area. In the present paper, a new method is used for controlling isolated Microgrids. This method was used based on the classification of the Microgrids into two groups, namely fast-dynamic (battery and flywheel) and slow-dynamic (diesel generator, electrolyzer, and fuel cell). For the Microgrid components with fast dynamics, a separate controller has been used. Also, another separate controller has been deployed for those components of the Microgrid that are characterized by slow dynamics. This method was simulated in MATLAB software. A fractional-order proportional-integral-differential (FOPID) controller optimized by the grey wolf optimizer (GWO) algorithm was used as the proposed controller in the new control strategy. The proposed method was compared with the FOPID controller that has been optimized by particle swarm optimization (PSO) algorithm and genetic algorithm (GA). Besides, it was compared with the common Proportional-Integral-Differential (PID) controller, the coefficients of which have been obtained using the Ziegler-Nichols method, and proportionalintegral (PI) controller, the coefficients of which have been obtained using the neural network (NN) method. The obtained results indicated the improved response speed, improved transient-state performance, and an improved steady-state performance of the proposed method compared with those mentioned.

The future Microgrids (MGs) hosting a great deal of uncertain and intermittent local renewable generations are envisioned to need for fast and flexible units in the generation side. Demand response, however, as a load shaping tool can alleviate the needs. This paper proposes a model to consider demand response potentials activated by time-varying prices in MG design studies. The model aims at maximizing MG owner’ s profit while technical limits and constraints are adhered. The model also ensures that the designed MG is resilient against islanding events. To handle complexity of the model, Benders decomposition is used to decompose the model into a master problem and two types of sub-problems. The master problem optimizes binary variables indicating installing status of generating units and batteries. The first type of sub-problems optimizes continuous variables, and the second ensures the resilient operation of the MG against islanding events. In the model, the uncertainties associated with load and intermittent generation resources are captured via a scenario-based stochastic approach. The demand behavior in response to time-varying prices is modeled via price elasticity coefficients. The effectiveness of the proposed model is demonstrated through extensive numerical studies and sensitivity analyses.

Load-frequency control is among the important concerns in controlling Microgrids, which are operated independently of the main grid. In this paper, load-frequency control in Microgrids on ships is studied. Resources such as batteries and flywheels are considered controllable resources in load-frequency control. Besides, the model predictive control is used as the controller to design a load-frequency control system. The model predictive control weight parameters, which play a substantial role in determining the performance of this controller, are optimized using the craziness-based particle swarm optimization algorithm. The proposed algorithm accelerates convergence. The results of the proposed controller are compared under several different scenarios considering the uncertainty of parameters using Multi-Objective Fuzzy Type 1 PI and Multi-Objective interval Fuzzy Type 2 PI controllers, which are optimized by the black hole algorithm, the fuzzy proportional integral controllers, and Ziegler– Nichols proportional integral controllers. The effectiveness of the proposed method with regard to the response speed, the decrease in overshoot and undershoot, and robustness against the parameter uncertainties is indicated. The proposed controller responds faster than the other conventional control methods and accelerates the process of responding to oscillations by 7%. In addition, the proposed controller performs better in reducing overshoot and reducing undershoot and it shows a 5% improvement with regard to the decrease in overshoot and undershoot in the oscillations. Simulations are also carried out in MATLAB (Simulink).

In this paper, the operation of a future distribution network is discussed under the assumption of a multicarrier Microgrid (MCMG) concept. The new model considers a modern energy management technique in electricity and natural gas networks based on a novel demand side management (DSM) which the energy tariff for responsive loads are correlated to the energy input of the network and changes instantly. The economic operation of MCMG is formulated as an optimization problem. In conventional studies, energy consumption is optimized from the perspective of each infrastructure user without considering the interactions. Here, the interaction of energy system infrastructures is considered in the presence of energy storage systems (ESSs), small-scale energy resources (SSERs) and responsive loads. Simulations are performed using MCMG which consists of micro combined heat and power (CHP), photovoltaic (PV) arrays, energy storage systems (ESSs), and electrical and heat loads in grid-connected mode. Results show that the simultaneous operation of various energy carriers leads to a better MCMG performance. Moreover, it has been indicated that energy sales by multi sources to main grids can undoubtedly reduce the total operation cost of future networks.