Tarek H. M. EL-Fouly

Coordinated Active Power Curtailment of Grid Connected PV Inverters for Overvoltage Prevention

Overvoltages in low voltage (LV) feeders with high penetration of photovoltaics (PV) are usually prevented by limiting the feeders PV capacity to very conservative values, even if the critical periods rarely occur. This paper discusses the use of droop-based active power curtailment techniques for overvoltage prevention in radial LV feeders as a means for increasing the installed PV capacity and energy yield. Two schemes are proposed and tested in a typical 240-V/75-kVA Canadian suburban distribution feeder with 12 houses with roof-top PV systems. In the first scheme, all PV inverters have the same droop coefficients. In the second, the droop coefficients are different so as to share the total active power curtailed among all PV inverters/houses. Simulation results demonstrate the effectiveness of the proposed schemes and that the option of sharing the power curtailment among all customers comes at the cost of an overall higher amount of power curtailed.

Impact of High PV Penetration on Voltage Profiles in Residential Neighborhoods

The objective of this paper is to provide an assessment on voltage profiles in residential neighborhoods in the presence of photovoltaic (PV) systems. The network was modeled in PSCAD using common feeder characteristics that Canadian system planners use in suburban residential regions. A simulation study was performed to investigate potential voltage rise issues in the network up to 11.25% total PV penetration in the feeder and LV transformer capacity penetration up to 75%. Results indicate that the PV penetration level should not adversely impact the voltage on the grid when the distributed PV resources do not exceed 2.5 kW per household on average on a typical distribution grid. Moreover, the role of feeder impedance, feeder length, and the transformer short circuit resistance in the determination of the voltage rise is quantified.

Grey predictor for wind energy conversion systems output power prediction

Wind energy is considered one of the most rapidly growing sources of electricity generation all over the world. This letter presents a novel technique for wind speed forecasting and wind power prediction based on using the Grey predictor model GM(1,1). The effectiveness of the proposed predictor is revealed using simulation results

One Day Ahead Prediction of Wind Speed and Direction

This paper presents a new technique for predicting wind speed and direction. This technique is based on using a linear time-series-based model relating the predicted interval to its corresponding one- and two-year old data. The accuracy of the model for predicting wind speeds and directions up to 24 h ahead have been investigated using two sets of data recorded during winter and summer season at Madison weather station. Generated results are compared with their corresponding values when using the persistent model. The presented results validate the effectiveness and accuracy of the proposed prediction model for wind speed and direction.

Supply-Adequacy-Based Optimal Construction of Microgrids in Smart Distribution Systems

Recently, the concept of microgrids (clusters of distributed generation, energy storage units, and reactive power sources serving a cluster of distributed loads in grid-connected and isolated grid modes) has gained a lot of interest under the smart grid vision. However, there is a strong need to develop systematic procedure for optimal construction of microgrids. This paper presents systematic and optimized approaches for clustering of the distribution system into a set of virtual microgrids with optimized self-adequacy. The probabilistic characteristics of distributed generation (DG) units are also considered by defining two new probabilistic indices representing real and reactive power of the lines. Next, the advantages of installing both distributed energy storage resources (DESRs) and distributed reactive sources (DRSs) are investigated to improve the self-adequacy of the constructed micro-grids. The new strategy facilitates robust infrastructure for smart distribution systems operational control functions, such as self-healing, by using virtual microgrids as building blocks in future distribution systems. The problem formulation and solution algorithms are presented in this paper. The well-known PG&E 69-bus distribution system is selected as a test case and through several sensitivity studies, the effect of the total DESRs or DRSs capacities on the design and the robustness of the algorithm are investigated.

Optimum Microgrid Design for Enhancing Reliability and Supply-Security

Microgrids are known as clusters of distributed energy resources serving a group of distributed loads in grid-connected and isolated grid modes. Nowadays, the concept of microgrids has become a key subject in the smart grid area, demanding a systematic procedure for their optimal construction. According to the IEEE Std 1547.4, large distribution systems can be clustered into a number of microgrids to facilitate powerful control and operation infrastructure in future distribution systems. However, clustering large systems into a set of microgrids with high reliability and security is not reported in current literature. To fill-out this gap, this paper presents a systematic and optimized approach for designing microgrids taking into account system reliability- and supply-security-related aspects. The optimum design considers sustained and temporary faults, for system reliability via a combined probabilistic reliability index, and real and reactive power balance, for supply security. The loads are assumed to be variable and different distributed generation (DG) technologies are considered. Conceptual design, problem formulation and solution algorithms are presented in this paper. The well-known PG&E 69-bus distribution system is selected as the test system. The effect of optimization coefficients on the design and the robustness of the algorithm are investigated using sensitivity studies.

Comprehensive Operational Planning Framework for Self-Healing Control Actions in Smart Distribution Grids

Self-healing is a major driving force in the smart grid vision. This paper proposes a comprehensive design and operational planning framework to generate optimum self-healing control actions in a distribution system. For this purpose, a distribution system with optimally allocated distributed generators (DGs) is divided into a set of microgrids with high self-adequacy through allocation of distributed energy storage resources (DESRs) and distributed reactive sources (DRSs). Afterwards, by using the predicted load and generation of renewable-based distributed generators for the next hour of the day and other important factors (self-adequacy in the unfaulted microgrids, total distribution systems energy losses and the total supplied loads according to their requested reliability), the optimum self-healing strategy is planned for the system for all possible future faults. The IEEE 123-bus distribution system is selected as the test system; optimum microgrids are designed and several case studies are presented to demonstrate the effects of optimization coefficients on the optimum self-healing control actions.

One day ahead prediction of wind speed using annual trends

The growing revolution in wind energy encourages for more accurate models for wind speed forecasting and wind power generation prediction. This paper presents a new technique for wind speed forecasting based on using a time series model relating the predicted interval to its corresponding one and two year old data. A set of data that extends to 72 hours is used in investigating the accuracy of the model for predicting wind speeds up 24 hours ahead. Obtained results, form the proposed model, are compared with their corresponding values generated when using the persistence model. The presented results validate the effectiveness of the new prediction models for wind speed

Droop-based active power curtailment for overvoltage prevention in grid connected PV inverters

Photovoltaics (PV) is considered a non-controllable power source which can create overvoltages in distribution feeders during periods of high generation and low load. This is usually prevented by limiting the penetration level of PV to very conservative values, even if the critical periods rarely occur. This paper discusses the use of droop based active power curtailment (APC) techniques for overvoltage prevention in radial low voltage (LV) feeders as a means for increasing the installed PV capacity and energy yield. Two schemes are considered and tested in a typical 240V/75kVA Canadian suburban distribution feeder with 12 houses equipped with roof-top PV systems. In the first scheme, all PV inverters have the same droop coefficients. In the second, the droop coefficients are proposed to be different so as to share the total active power curtailed, and consequent loss of revenue, among all PV inverters/houses. Simulation results demonstrate the effectiveness of the droop based APC schemes and that the option of sharing the power curtailment among all customers comes at the cost of an overall higher amount of power curtailed.

Optimal ESS Allocation for Load Management Application

The recent deployment of distributed generation has led to a revolution in the use of distribution systems and the emergence of “smart grid” concepts. Smart grids are intended primarily as a means of facilitating the integration of renewable energy sources and of achieving greater system reliability and efficiency. Energy storage systems (ESSs) offer a number of benefits that can help utilities move toward those goals. One of those benefits is the capacity to improve the utilization of network infrastructure by means of proper load management. This paper proposes a methodology for allocating ESSs in distribution systems in order to defer system upgrades, minimize system losses, and take advantage of the arbitrage benefit. The cost and arbitrage benefit of energy storage installation are optimized with respect to system upgrade and energy losses costs. The primary goal of this research is to determine the optimal size and location of storage units to be installed, in addition to their optimal operation, so that total system costs are minimized, while system benefits are maximized. In this paper, a probabilistic load model is adopted instead of utilizing time-series based models, which provide an optimal solution that is valid only for the time-series pattern that is applied.