Ghada M. Amer

Virtual Power Plants (VPP) represents a transformative approach in the integration of distributed energy resources (DERs) into the modern electricity grid. Due to the stochastic nature of DERs and the growing energy demand, the increasing penetration of DERs introduces significant challenges for the stability and reliability of the power system. In order to effectively manage DERs and facilitate their market participation, new concepts have emerged. The VPP is one of these concepts that is now attracting a lot of attention. The operation of a VPP seeks to maximize economic benefits while ensuring the technical performance and reliability of the system are not compromised. This paper presents a method for defining the VPP’s border by determining the optimal number and location of buses, as well as for allocating and sizing DERs to achieve grid profit maximization. Several scenarios are considered, as the price of power exchanged by the grid is varied, it can be smaller, equal, or more than the price of power generated from distributed generations(DGs), also the generator at one is outed from the service. This paper used a robust methodology of Artificial Hummingbird Algorithm (AHA) for finding the best solution while evaluating this method on the IEEE 57-bus system and IEEE−39 bus system. The output results of AHA illustrate the number and location of buses of VPP, the location and size of DGs, which shows that the profit can be increased between 78 and 85% from the base case for IEEE−57 bus system.

Integrating numerous renewable resources has been extensively researched and studied to create a dependable energy system. This study investigated the best techno-economical hybrid energy system configuration while using hydrogen energy to keep the system's energy balanced. Additionally, this study aims to determine the best hybrid system configuration for the location under investigation. A novel technique of DBM (Deterministic Balanced Method) was introduced to determine the total annual energy output for the project's lifetime. This approach is used to contrast the outcomes of other HOMER software tools. Then, using HOMER, it is possible to confirm the sizing optimization results for the suggested method by comparing the power ratings and yearly energy output. A detailed comparison between our proposed method and HOMER Pro has been conducted for validation and verification. Our method has been rigorously tested in various hybrid off-grid energy systems, ensuring its applicability and reliability across different scenarios and configurations. The results of our study indicate a high degree of similarity between the proposed approach and HOMER pro for computing annual energy power for the studied energy systems. Specifically, our analysis revealed that the difference between the approaches was within a range of 5%, indicating a high level of consistency and reliability in our method. These findings suggest that our approach can be confidently applied to determine the appropriate size of hybrid energy systems accurately. Overall, our study provides valuable insights into the development of effective sizing methodologies for hybrid energy systems. After considering the amount of solar radiation and wind speed gathered by global weather data platforms like NASA and METEONORM, this paper has also included a real case study of the Cairo International Airport's hybrid renewable energy production systems. To guarantee the viability of this study, the system design was founded on an actual load that was researched and simulated. A cluster of distributed networks was finally proposed to use the excess energy and enable energy conversion processes to be used in industry and transportation applications.

Recent technologies such as artificial intelligence, machine learning, and big data are essential for supporting healthcare monitoring systems, particularly for monitoring Monkeypox confirmed cases. Infected and uninfected cases around the world have contributed to a growing dataset, which is publicly available and can be used by artificial intelligence and machine learning to predict the confirmed cases of Monkeypox at an early stage. Motivated by this, we propose in this paper a new approach for accurate prediction of the Monkeypox confirmed cases based on an optimized Long Short-Term Memory (LSTM) deep network. To fine-tune the hyper-parameters of the LSTM-based deep network, we employed the Al-Biruni Earth Radius (BER) optimization algorithm; thus, the proposed approach is denoted by BER-LSTM. Experimental results show the effectiveness of the proposed approach when assessed using various evaluation criteria, such as Mean Bias Error, which is recorded as (0.06) using BER-LSTM. To prove the superiority of the proposed approach, six different machine learning models are included in the conducted experiments. In addition, four different optimization algorithms are considered for comparison purposes. The results of this comparison confirmed the superiority of the proposed approach. On the other hand, several statistical tests are applied to analyze the stability and significance of the proposed approach. These tests include one-way Analysis of Variance (ANOVA), Wilcoxon, and regression tests. The results of these tests emphasize the robustness, significance, and efficiency of the proposed approach.

A technical analysis based on modeling, simulation, optimization and verification was conducted for the design of an off-grid hybrid solar PV/hydrogen system. The main objective is to make sizing optimization of the off-grid system to meet the desired electric load of a residential community in a studied region. Additionally, the goal of this study is to have a 100% renewable fraction penetration in the energy mix resulting in a zero percentage of the greenhouse gas emissions and lowering the cost of energy from power systems and verifying the design concept using SAM (System Advisor Model). The effect of meteorological data inputs for the hybrid off-grid system was investigated in Cairo international Airport zone. The distributed power generation in this paper was using solar PV and Fuel Cell energy systems integrated with electrolyzer and hydrogen tank where the main resource for production is the PV modules so that it satisfies the load demand during the peak sun hours and supplying an excess energy to be stored for the later use of fuel cell to supply community load demand of average 4980 kWhr/day.Keywords : Solar PV, Fuel Cell, Hydrogen production, Optimization, off-grid

This study proposes a complementary fault identification scheme for triple fed high‐voltage transmission lines (TFHVTLs). The current signals are captured from a single end measuring system of the TFHVTL. Then, the captured current signals are decomposed using wavelet multi‐resolution analysis technique. The proposed scheme is based on two criteria. The first criterion is dependent on the level of detail coefficients while the second one is dependent on the deviation of detail coefficients. The decision is obtained using an OR‐logic of the two criteria. Also, this study introduces the stability and sensitivity concepts for the fault identification process. In addition, a suggested fault identification sensitivity index is proposed to measure the efficacy of the proposed scheme. Also, different types of mother wavelets are assessed to show that the best mother wavelet, Haar, has high fault detection and classification performance. An ATP/EMTP package is used to simulate the tested part of the 500 kV Egyptian grid. The proposed scheme performance is corroborated under different operating conditions for load changes, fault locations, sampling frequencies of the monitored current, fault resistances, fault types, and inception angles. The proposed scheme is tested for series compensated TFHVTL at different compensation levels.

This paper proposes a novel fault identification algorithm for an electrical multi-terminals network. The Discrete Wavelet Transform (DWT) is used to decompose current signals. The purposed algorithm designs to be algorithm able to detect and classify various fault types at any point on the multi-terminals system. Using the current signals only that are captured from single ended of multi-terminals configuration, which consists of three terminal circuits. The ATP/EMTP simulator is developed to evaluate the capability of the proposed algorithm. In addition, the proposed algorithm is applied to simulated parameters that are taken from Egyptian electrical grid, which comprises of three terminal circuits connected as ring configuration. Also, it considered the future installation of El Dabaa nuclear power station. The proposed algorithm achieves accurate results under numerous conditions such as different fault resistances, locations and inception angles.

Many factors affect the loading of the underground power cables, such as ambient temperature, depth of laying of cable, number of parallel circuits of cable, and thermal resistivity of the surrounding soil. One important factor, usually ignored, is the formation of dry zones around the underground power cables. Dry zones are usually formed around underground power cables under loading conditions due to the migration of moisture within the soil. In this paper, the effect of the formation of the dry zone on the ampacity of underground power cables is investigated. The derating factor for the formation of dry zones around underground power cables is suggested and calculated for different types of natural backfill soil. IEC 60287-1-3 is taken as a reference. Experimental work was conducted to study the phenomena of the dry zone as related to different types of soils.

The backfill materials around under-ground power cables affect the maximum current carrying capacity of these cables. Usually backfill soils around under-ground power cables lose their moisture content, forming dry bands around the cables and leading to an increase in the thermal resistance and decreasing in maximum current carrying capacity. But according to the results of the experimental works which are carried out in this paper, it is noticed that some types of soil lost their moisture content faster than the other. This means that the dry band around the cable in some soils form faster than the others. The aim of this paper is to determine the best type of artificial soil that can be used as backfill material to minimize the effect of dry bands that cause thermal failure to the cable insulation.