Assessment of energy credits for the enhancement of the Egyptian Green Pyramid Rating System

Energy is one of the most important categories in the Green Building Rating Systems all over the world. Green Building is a building that meets the energy requirements of the present with low energy consumption and investment costs without infringing on the rights of forthcoming generations to find their own needs. Despite having more than a qualified rating system, it is clear that each system has different priorities and needs on the other. Accordingly, this paper proposes a methodology using the Analytic Hierarchy Process (AHP) for assessment of the energy credits through studying and comparing four of the common global rating systems, the British Building Research Establishment Environmental Assessment Method (BREEAM), the American Leadership in Energy and Environmental Design (LEED), the Australian Green Stars (GS), and the PEARL assessment system of the United Arab Emirates, in order to contribute to the enhancement of the Egyptian Green Pyramid Rating System (GPRS). The results show the mandatory and optional energy credits that should be considered with their proposed weights according to the present and future needs of green Egypt. The results are compared to data gathered through desk studies and results extracted from recent questionnaires

Ocean Wind Energy Technologies in Modern Electric Networks: Opportunity and Challenges

Wind energy is one of the most important sources of energy in the world. In recent decades, wind as one of the massive marine energy resources in the ocean to produce electricity has been used. This chapter introduces a comprehensive overview of the efficient ocean wind energy technologies, and the global wind energies in both offshore and onshore sides are discussed. Also, the classification of global ocean wind energy resources is presented. Moreover, different components of a wind farm offshore as well as the technologies used in them are investigated. Possible layouts regarding the foundation of an offshore wind turbine, floating offshore, as well as the operation of wind farms in the shallow and deep location of the ocean are studied. Finally, the offshore wind power plant challenges are described

Bi-Level damped double-tuned harmonic passive filters design: Multi-criteria decision-making analysis

Harmonic distortion levels in current power systems have increased due to technical advancements in industrial and renewable energy applications. So far, passive power filters have been widely employed to minimize harmonics and lessen their adverse effects. In this regard, this paper presents a novel bi-level design of damped double-tuned passive filters operating in a non-sinusoidal power system with nonlinearities at both the source and the load. A modern metaheuristic optimization technique known as wild horse optimization is applied to acquire the parameters of the used filters. Several objective functions, such as voltage total harmonic distortion, current total demand distortion, active power losses, and resonance-based metric minimization, were researched to improve the analyzed system's overall power quality performance. The mathematical derivations of the filter design expressions are given in detail. In the literature, there are several schemes for damped double-tuned filters. This paper investigates and analyses four schemes of this filter. The results are compared to those obtained from other metaheuristic optimization algorithms to ensure that the proposed algorithm produces the most effective outcomes. Statistical analysis is performed using many criteria to ensure the superiority of the proposed algorithm. Furthermore, depending on several assessment criteria, the analytical hierarchy process is employed to find the most effective candidate scheme. One of the schemes tested (scheme B) outperformed the others

Considerations on optimal design of hybrid power generation systems using whale and sine cosine optimization algorithms

Nowadays, the continuous increase of power demand leads to various challenges for distribution system operators (DSOs) such as power quality, system stability and reliability. Microgrids (MGs) and hybrid power generation systems (HPGSs) can play a significant role in solving these issues while improving the performance of electrical power systems. In this paper, an optimal multi-criteria design of a grid-connected HPGS is introduced, taking into consideration involvement of a natural gas distribution network (NGDN) in the proposed configuration, where the NGDN supplies natural gas to a gas turbine. The HPGS system consists of wind turbines (WT), photovoltaic (PV) arrays, battery banks (BBs), gas turbines (GTs), in addition to a utility grid (UG). Two different meta-heuristic optimization algorithms, namely whale, and sine cosine, are employed to find the optimal design of the system for minimizing the total annual cost and system emissions. A detailed comparative study of the results with results of the cuckoo search and firefly optimization algorithms is presented to show the robustness of the used techniques. Keywords: Distributed generation, Power generation systems, Natural gas, Optimization algorithm

A new fuzzy framework for the optimal placement of phasor measurement units under normal and abnormal conditions

This paper presents a new procedure for finding the optimal placement of the phasor measurement units (PMUs) in modern power grids to achieve full network observability under normal operating conditions, and also abnormal operating conditions such as a single line or PMU outage, while considering the availability of PMU measuring channels. The proposed modeling framework is implemented using the fuzzy binary linear programming (FBLP) technique. Linear fuzzy models are proposed for the objective function and constraints alike. The proposed procedure is applied to five benchmark systems such as the IEEE 14-bus, 30-bus, 39-bus, 57-bus, and 118-bus. The numerical results demonstrate that the proposed framework is capable of finding a fine-tuned optimal solution with a simple model and acceptable solution characteristics compared with early works in the literature. Besides, four evaluation indices are introduced to assure the various criteria under study such as the observability depth, measurement redundancy, and robustness of the method under contingencies. The results show that full network observability can be met under normal conditions using 20% PMUs penetration; however, under contingencies, approximately 50% PMUs penetration is required. The novelty of the proposed procedure has proven the capability of the proposed linear fuzzy models to find better optimal number of PMUs with lower number of channels compared to other algorithms under various operating conditions. Hence, the proposed work represents a potential tool to monitor power systems, and it will help the operators in a smart grid environment. Keywords: Binary linear programming, Fuzzy models, Observability, Optimization, Phasor measurement unit, Smart grid

Review of batteries reliability in electric vehicle and E-mobility applications

Electric mobility (E-Mobility) has expedited transportation decarbonization worldwide. Lithium-ion batteries (LIBs) could help transition gasoline-powered cars to electric vehicles (EVs). However, several factors affect Li-ion battery technology in EVs’ short-term and long-term reliability. Li-ion batteries’ sensitivity and non-linearity may make traditional dependability models unreliable. This state-of-the-art article investigated power fade (PF) and capacity fade (CF) as leading reliability indicators that help analyze battery reliability under various ambient temperatures and discharge C-rates. Trends in LIBs applications for EVs and E-mobility are discussed. Furthermore, qualitative analysis and risk management were conducted to identify the reliable and unreliable zones of battery operation based on these indicators and the degradation circumstances implemented in recent publications. Besides, the influence of degrading circumstances on reliability indicators over the battery’s lifespan, such as a high C-rate at a low temperature throughout the battery's lifetime, has been presented in a comprehensive investigated case study in this work

Dual Enhancement of Power System Monitoring: Improved Probabilistic Multi-Stage PMU Placement with an Increased Search Space & Mathematical Linear Expansion to Consider Zero-Injection Bus

This paper presents a mathematical linear expansion model for the probabilistic Multistage Phasor Measurement Unit (PMU) Placement (MPP) in which zero-injection buses (ZIBs), as well as communication channel limitations, are taken into consideration. From the linearization perspective, presenting a model formulizing the probabilistic concept of observability while modelling the ZIB is of great significance, and has been done in this paper for the first time. More importantly, the proposed probabilistic MPP utilizes a technique disregarding the prevalent subsidiary optimizations for each planning stage. Although this technique, in turn, increases the problem complexity with manifold variables, it guarantees the global optimal solution in a wider and thorough search space; while in the prevalent methods, some parts of the search space might be missed. Furthermore, the proposed model indicates more realistic aspects of the MPP where system operators are allowed to follow their intention about the importance of buses such as strategic ones based on monitoring the priority principles. In addition, the model is capable of considering the network topology changes due to long-term expansions over the planning horizon. Finally, in order to demonstrate the effectiveness of the proposed formulation, the model is conducted on the IEEE 57-bus standard test system and the large scale 2383-bus Polish power system

Power conditioning using dynamic voltage restorers under different voltage sag types

Voltage sags can be symmetrical or unsymmetrical depending on the causes of the sag. At the present time, one of the most common procedures for mitigating voltage sags is by the use of dynamic voltage restorers (DVRs). By definition, a DVR is a controlled voltage source inserted between the network and a sensitive load through a booster transformer injecting voltage into the network in order to correct any disturbance affecting a sensitive load voltage. In this paper, modelling of DVR for voltage correction using MatLab software is presented. The performance of the device under different voltage sag types is described, where the voltage sag types are introduced using the different types of short-circuit faults included in the environment of the MatLab/Simulink package. The robustness of the proposed device is evaluated using the common voltage sag indices, while taking into account voltage and current unbalance percentages, where maintaining the total harmonic distortion percentage of the load voltage within a specified range is desired. Finally, several simulation results are shown in order to highlight that the DVR is capable of effective correction of the voltage sag while minimizing the grid voltage unbalance and distortion, regardless of the fault type

Dynamic performance enhancement of nonlinear AWS wave energy systems based on optimal super-twisting control strategy

This paper presents a Super-Twisting Algorithm (STA) sliding mode control technique as an alternative to the conventional Proportional-Integral (PI) control system. This application is specifically in the context of a nonlinear Archimedes Wave Swing (AWS) device, which functions as a wave energy converter system (WECS) connected to the power grid. The main goal is dynamic performance enhancement of such wave energy systems under network disturbances. Two STA controllers are essential for the rectifier control system in the grid-connected system to capture the most power from waves while limiting losses in the AWS linear generator. In addition, four STA controllers are incorporated into the inverter control loop to preserve the DC link and common coupling voltages at the preset values. The Honey-Badger Algorithm (HBA) is applied for the optimization of gain parameters of the STA controllers, which are compared to the PI gains adjusted using the coot, the hybrid augmented grey wolf optimizer and cuckoo, and PSO search techniques to assess the worthiness of adopting this new control approach. The grid-connected AWS experiences a variety of faults, including symmetrical and unsymmetrical faults with successful and unsuccessful breaker reclosures. Finally, the system is experimentally validated using the OP4510 real-time simulator. The experimental results reveal that the HBA-STA controllers outperform PI controllers in omitting fluctuations in the regulated variables, making the STA a strong contender as a control method