Ragab A. El-Sehiemy

Bio: Ragab A. El-Sehiemy is an academic researcher from Kafrelsheikh University. The author has contributed to research in topics: Electric power system & Computer science. The author has an hindex of 25, co-authored 139 publications receiving 2144 citations. Previous affiliations of Ragab A. El-Sehiemy include University College of Engineering.

Optimal Placement and Sizing of Distributed Generation and Capacitor Banks in Distribution Systems Using Water Cycle Algorithm

Abstract: Integration of distributed generation units (DGs) and capacitor banks (CBs) in distribution systems aim to enhance the system performance. This paper proposes water cycle algorithm (WCA) for optimal placement and sizing of DGs and CBs. The proposed method aims to achieve technical, economic, and environmental benefits. Different objective functions: minimizing power losses, voltage deviation, total electrical energy cost, total emissions produced by generation sources and improving the voltage stability index are considered. WCA emulates the water flow cycle from streams to rivers and from rivers to sea. Five different operational cases are considered to assess the performance of the proposed methodology. Simulations are carried out on three distribution systems, namely IEEE 33-bus, 69-bus test systems, and East Delta network, as a real part of Egyptian system. The simulated results demonstrate the effectiveness of the proposed method compared with other optimization algorithms. Also, the results demonstrate that the proposed WCA gives superior performance for the system and give distinguished improvements in both economic and environmental benefits. Moreover, the results give the flexible operation with controllable power factor DGs that is better than those using DGs at fixed power factor.

Optimal power flow using an Improved Colliding Bodies Optimization algorithm

Abstract: Flowchart of the proposed OPF solution using ICBO, CBO and ECBO. We developed an Improved Colliding Bodies Optimization (ICBO) algorithm.We solved the optimal power flow for several cases using different constraints, formulations and complexities.The performances of the ICBO algorithm have been evaluated using a comparative study.The ICBO algorithm outperforms many other algorithms for solving optimal power flow problems. This paper proposes Improved Colliding Bodies Optimization (ICBO) algorithm to solve efficiently the optimal power flow (OPF) problem. Several objectives, constraints and formulations at normal and preventive operating conditions are used to model the OPF problem. Applications are carried out on three IEEE standard test systems through 16 case studies to assess the efficiency and the robustness of the developed ICBO algorithm. A proposed performance evaluation procedure is proposed to measure the strength and robustness of the proposed ICBO against numerous optimization algorithms. Moreover, a new comparison approach is developed to compare the ICBO with the standard CBO and other well-known algorithms. The obtained results demonstrate the potential of the developed algorithm to solve efficiently different OPF problems compared to the reported optimization algorithms in the literature.

Optimal capacitor placement in distribution systems for power loss reduction and voltage profile improvement

Abstract: This study presents a two-stage procedure to identify the optimal locations and sizes of capacitors in radial distribution systems. In first stage, the loss sensitivity analysis using two loss sensitivity indices (LSIs) is employed to select the most candidate capacitors locations. In second stage, the ant colony optimisation algorithm is investigated to find the optimal locations and sizes of capacitors considering the minimisation of energy loss and capacitor costs as objective functions while system constraints are fully achieved. The fixed, practical switched and the combination of fixed and switched capacitors are considered to find the optimal solution. The backward/forward sweep algorithm is developed for the load flow calculations. The proposed procedure is applied to different standard test systems as 34-bus and 85-bus radial distribution systems. In addition, the application of the proposed procedure on a real distribution system of the East Delta Network as a part of the Unified Egyptian Network is used as a test system. Numerical results show the capability of the proposed procedure to find the optimal solution for significant saving in the total cost with more accurate and efficient, competitive compared with other methods in the literature especially with increasing the distribution system sizing.

Solving multi-objective optimal power flow problem via forced initialised differential evolution algorithm

Abstract: This study proposes a multi-objective differential evolution algorithm (MO-DEA) based on forced initialisation to solve the optimal power flow (OPF) problem. The OPF problem is formulated as a non-linear MO optimisation problem. The considered objective functions are fuel cost minimisation, power losses minimisation, voltage profile improvement, and voltage stability enhancement. For solving the MO-OPF, the proposed approach combines a new variant of DE (DE/best/1) with the ɛ-constraint approach. This combination guarantees high convergence speed and good diversity of Pareto solutions without computational burden of Pareto ranking and updating or additional efforts to preserve the diversity of the non-dominated solutions. The proposed approach has the ability to generate Pareto-optimal solutions in a single simulation run through adaptive variation of the ɛ-value. In addition, the best compromise solution is extracted based on fuzzy set theory. The effectiveness of the proposed MO-DEA is tested on the IEEE 30-bus and IEEE 57-bus standard systems. The numerical results obtained by the proposed MO-DEA are compared with other evolutionary methods reported in this literature to prove the potential and capability of the proposed MO-DEA for solving the MO-OPF at acceptable economical and technical levels.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Fuzzy Multi-Criteria Decision Making: Theory and Applications with Recent Developments

Abstract: In trying to make a satisfactory decision when imprecise and multicriteria situations are involved, a decision maker has to use a fuzzy multicriteria decision making method. "Fuzzy Multi-Criteria Decision Making" (MCDM) presents fuzzy multiattribute and multiobjective decision-making methodologies by distinguished MCDM researchers. In summarizing the concepts and results of the most popular fuzzy multicriteria methods, using numerical examples, this work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results. This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.