Yusuf Al-Turki

Hierarchical Coordination of a Community Microgrid With AC and DC Microgrids

In this paper, a community microgrid with multiple ac and dc microgrids is introduced and analyzed. Individual microgrids with different frequency and voltage requirements would operate as self-controlled entities, which could also cooperate with neighboring microgrids for providing back-up operations in the community microgrid. A hierarchical coordination strategy with primary, secondary, and tertiary coordination is proposed for the economic operation of an islanded community microgrid. The hierarchical strategy is also applied to a grid-connected community microgrid and the results are discussed. The simulation results verify that the proposed hierarchical coordination strategy is an effective and efficient way for coordinating microgrid flows in an islanded community microgrid, while maintaining the rated frequency and voltage with each microgrid. The simulation results also demonstrate the economic operation of a grid-connected community microgrid in which individual microgrids operate as autonomous agents, while satisfying the community objectives.

A comparative study of medium-weather-dependent load forecasting using enhanced artificial/fuzzy neural network and statistical techniques

Abstract Monthly peak load demand of Jeddah area for the past nine years is used for investigation throughout this work. The first seven years data is used for training while the prediction is carried out for the following two years. First, Minitab statistical software package is used for peak load prediction using autoregressive integrated moving average (ARIMA) technique, and an average error value of 11.7% is achieved. Next, an artificial neural network (ANN) is utilised and several suggestions are implemented to build an adaptive form of ANN. Direct ANN implementation shows poor performance. Also, fuzzy neural network (FNN) is also examined but showed comparatively poor performance. The modelling of the trend of peak load demand is incorporated by introducing “time index feature” and that clearly enhanced the performance of both ANN (6.8% error) and FNN (4.7% error). A comparative study is provided below to show the accuracy of distinction among these techniques.

Control Strategy to Maximize the Power Capability of PV Three-Phase Inverters During Voltage Sags

Under voltage sags, grid-tied photovoltaic inverters should remain connected to the grid according to low-voltage ride-through requirements. During such perturbations, it is interesting to exploit completely the distributed power provisions to contribute to the stability and reliability of the grid. In this sense, this paper proposes a low-voltage ride-through control strategy that maximizes the inverter power capability by injecting the maximum-rated current during the sag. To achieve this objective, two possible active power situations have been considered, i.e., high- and low-power production scenarios. In the first case, if the source is unable to deliver the whole generated power to the grid, the controller applies active power curtailment to guarantee that the maximum rated current is not surpassed. In the second case, the maximum allowed current is not reached, thus, the control strategy determined the amount of reactive power that can be injected up to reach it. The control objective can be fulfilled by means of a flexible current injection strategy that combines a proper balance between positive- and negative-current sequences, which limits the inverter output current to the maximum rated value and avoid active power oscillations. Selected experimental and simulation results are reported in order to validate the effectiveness of the proposed control strategy.

Optimal Power Flow Using Adapted Genetic Algorithm with Adjusting Population Size

Abstract In this article, a new approach for the genetic algorithm is applied to solve the optimal power flow problem based on different objective functions. The main distinction of this technique is in using the adapted genetic algorithm with adjusting population size. The objective functions are minimized using various controlled system variables (generator voltages, transformer taps, and shunt capacitors). The feasibility of the proposed method is presented on the IEEE 30-bus system and compared to other well-established techniques. A comparison with other methods shows the effectiveness of the proposed technique.

Hybrid Synchronous/Stationary Reference-Frame-Filtering-Based PLL

Designing an effective phase-locked loop (PLL) for three-phase applications is the objective of this paper. The designed PLL structure is able to provide an accurate estimation of the grid voltage frequency and the phase, even in the presence of all harmonic components of both positive and negative sequences and the dc offset in its input. In addition to offering a high disturbance rejection capability, the suggested PLL structure has a fast transient response and provides a settling time of around two cycles of the fundamental frequency. The effectiveness of the suggested PLL structure is confirmed using numerical results.

Networked Microgrids for Enhancing the Power System Resilience

This paper focuses on the role of networked microgrids as distributed systems for enhancing the power system resilience against extreme events. Resilience is an intrinsically complex property which requires deep understanding of microgrid operation in order to respond effectively in emergency conditions. The paper first introduces the definition and offers a generic framework for analyzing the power system resilience. The notion that large power systems can achieve a higher level of resilience through the deployment of networked microgrids is discussed in detail. In particular, the management of networked microgrids for riding through extreme events is analyzed. In addition, the merits of advanced information and communication technologies (ICTs) in microgrid-based distributed systems that can support the power system resilience are presented. The paper also points out the challenges for expanding the role of distributed systems and concludes that networked microgrids in particular provide a universal solution for improving the resilience against extreme events in Smart Cities.

Optimal Planning of Loop-Based Microgrid Topology

In microgrid planning, topological design is a critical concern for ensuring certain features such as high reliability in islanded operation. This paper proposes a graph partitioning and integer programming integrated methodology for the optimal loop-based microgrid topology planning while considering the distributed energy resources in the microgrid. The proposed methodology is applied to a microgrid test system and the planning results are discussed. The results demonstrate that the proposed planning methodology is able to accurately and efficiently determine an optimal loop structure for microgrids, and exhibit the potentials for applying the proposed planning methodology in practical microgrid applications.

Performance of Dual-Axis Solar Tracker versus Static Solar System by Segmented Clearness Index in Malaysia

The performance of Dual-Axis Solar Tracker (DAST) and Static Solar System (SSS) with respect to clearness index in Malaysia is presented. An attempt to investigate the correlation between clearness index with energy gain and efficiency of DAST over SSS is being done experimentally. A good correlation could not be found out from the daily clearness index. It is due to the more profound advantage of DAST in the morning and evening compared to midday as it is able to follow the sun’s position. Hence, the daily clearness index is divided into three segments which are morning, midday, and evening to interpret the energy gain and efficiency better. A clearer correlation with low standard deviation can be observed on the segmented clearness index analysis. The energy gain and efficiency of seven cities in Malaysia is being estimated with the segmented clearness index and compared to the result generated from anisotropic radiation model. A similar trend is obtained and it has shown that the segmented clearness index could be utilized as a graphical method for estimation of energy gain and efficiency of DAST over SSS.

Nano silver-anchored reduced graphene oxide sheets for enhanced dielectric performance of polymer nanocomposites

Nano silver-anchored reduced graphene oxide (Ag–RGO) was prepared and used as the filler material for a polar polyvinylidene fluoride (PVDF) polymer. The percolation threshold of the Ag–RGO–PVDF composites was determined to be 1.52 vol%. The results showed that the dielectric performance of the composite system was greatly improved by incorporating Ag–RGO sheets. The dielectric permittivity of the composite system reached a value of about 97 at 1 kHz, while maintaining a relatively low loss tangent. The enhanced dielectric performance of the composites was attributed to the presence of silver nanoparticles. These particles separated the RGO sheets from aggregation, thus increasing the interfacial areas within the composites greatly. When the composites were exposed to an external electric field, intense Maxwell–Wagner–Sillars polarization occurred at the interfacial areas. This led to enhanced dielectric permittivity of the composites. Coupled with low loss tangent and electrical conductivity, the Ag–RGO–PVDF composite system shows great promise for use as dielectric material for electronic capacitors.

Nonlinear dynamics and bifurcation analysis of a boost converter for battery charging in photovoltaic applications

Photovoltaic (PV) systems with a battery back-up form an integral part of distributed generation systems and therefore have recently attracted a lot of interest. In this paper, we consider a system of charging a battery from a PV panel through a current mode controlled boost dc-dc converter. We analyze its complete nonlinear/nonsmooth dynamics, using a piecewise model of the converter and realistic nonlinear v–i characteristics of the PV panel. Through this study, it is revealed that system design without taking into account the nonsmooth dynamics of the converter combined with the nonlinear v–i characteristics of the PV panel can lead to unpredictable responses of the overall system with high current ripple and other undesirable phenomena. This analysis can lead to better designed converters that can operate under a wide variation of the solar irradiation and the batterys state of charge. We show that the v–i characteristics of the PV panel combined with the batterys output voltage variation can increase or decrease the converters robustness, both under peak current mode control and average current mode control. We justify the observation in terms of the change in the discrete-time map caused by the nonlinear v–i characteristics of the PV panel. The theoretical results are validated experimentally.