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This study presents two proposed adaptive and intelligent control schemes for accurately adjusting the MG voltage and frequency in islanded mode and ensuring the seamless transition between islanded and grid‐connected modes. The two proposed controllers are based on improving the performance of the droop control method depending on H‐infinity and model predictive control methods. However, when the MG connected to the utility grid, the MG is related to the grid voltage and frequency and the active and reactive power transfer is adjusted using the P/Q control method. Firstly, this study presents a comprehensive review of the commonly used control schemes in MGs. Then, the structure of the two proposed controllers is described and the Simulink model is presented. The controller is applied to an MG test system to validate its capability to meet requirements. In addition, a comparison between the two proposed controllers is made based on the integral of square error (ISE), integral of absolute error (IAE), and integral time‐weighted absolute error (ITAE). The results prove that the two proposed control schemes have the ability to adjust the MG in its two operating modes and also provide a seamless transfer between the islanded and grid‐connected modes of MGs. [ABSTRACT FROM AUTHOR]

The integration of the various types of distributed generators in low‐voltage (LV) distribution networks becomes a great concern, especially the rooftop photovoltaic (PV) systems. The negative impacts of the rooftop PVs on the distribution feeder buses' voltage include voltage rise and voltage unbalance (VU). Such a voltage‐violation condition depends mainly on the PVs ratings and the network unbalance percentage. This study presents a review for different techniques used to mitigate the voltage violation resulting from PVs integration in a typical three‐phase four‐wire LV distribution network case study. The voltage‐violation mitigation techniques studied in this study are enhancement of the feeder, on‐load tap changer, demand‐side management, active power curtailment, a reactive power control, static transfer switch, energy storage systems and hybrid strategies. The LV distribution network case study was modelled based on constant power model method using MATLAB software environment. The simulation results demonstrate both voltage regulation and alleviating VU capabilities of each technique. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a novel methodology for controlling voltage and frequency of islanded microgrids and meanwhile improving the system power quality. The proposed methodology is based on applying a multi‐stage H‐Infinity (H∞) controller with different control loops to restore the nominal values of voltage and frequency after any load variation. These control loops include power control, current control, and voltage control loops. The H∞ is also applied with an LCL filter to enhance the system power quality. The proposed controller is applied to a test system under three different loading conditions and the obtained results are compared with that obtained by applying the model predictive control (MPC) method. The results are compared with that obtained by applying a proposed traditional control method in the same test system. A comparison between the droop controller and the proposed controller, MPC is performed based on fitness value, controller response time, and maximum frequency deviation. In addition, the system stability is analysed using root locus, system step response, singular value decomposition, and bode diagram. The results prove the effectiveness and the efficiency of the proposed method in restoring voltage and frequency and improving the system power quality. [ABSTRACT FROM AUTHOR]

Summary: Economic load dispatch (ELD) became recently a mandatory tool for reliable and economic power system operation. ELD improves the security of the power supply while minimizing the generation costs. Daily load curve imposes conflicting requirements on ELD scheme, such as fulfilling demand during peak periods while limiting the cost. Demand response (DR) is an intelligent approach that ensures load demand fulfillment without introducing additional costs. DR allows shifting the electricity consumption to the non‐peak periods. Therefore, DR could be considered as a virtual power plant. ELD is usually solved as nonlinear constraint optimization problem. Three simple, fertile, and robust meta‐heuristic optimizations are competing in this article for solving ELD incorporating DR as virtual power plant. These are ant lion optimizer (ALO), particle swarm optimization (PSO), and artificial immune system (AIS). The objectives are minimizing the overall cost, system losses, and emission levels. Variety of distinctive study systems are considered to test the functionality and feasibility of the proposed algorithms; they are 6‐bus, 30‐bus, and 118‐bus IEEE systems. MATLAB environment is used for coding ALO, PSO, AIS, and the systems under concern. The comprehensive results show that incorporating DR in ELD reduces the costs/losses/emissions without affecting the power system security and reliability. The comparative results verify the robustness and reliability of ALO in minimizing the overall operating cost and emission levels of the power systems under concern while confining with the constraints. Moreover, they show that ALO has the highest accuracy and convergence efficiency while enjoying the reduced computation storage and execution time. [ABSTRACT FROM AUTHOR]