scholarly journals Hydrogen Distribution Network of Medor Refinery Plant by Using Two Different Optimization Techniques

2015 ◽  
Vol 17 (1) ◽  
pp. 66-72
Author(s):  
Fatma Gad ◽  
Jin Kim ◽  
Abeer Shoaib ◽  
Walaa Shehata
Author(s):  
Jitendra Singh Bhadoriya ◽  
Atma Ram Gupta

Abstract In recent times, producing electricity with lower carbon emissions has resulted in strong clean energy incorporation into the distribution network. The technical development of weather-driven renewable distributed generation units, the global approach to reducing pollution emissions, and the potential for independent power producers to engage in distribution network planning (DNP) based on the participation in the increasing share of renewable purchasing obligation (RPO) are some of the essential reasons for including renewable-based distributed generation (RBDG) as an expansion investment. The Grid-Scale Energy Storage System (GSESS) is proposed as a promising solution in the literature to boost the energy storage accompanied by RBDG and also to increase power generation. In this respect, the technological, economic, and environmental evaluation of the expansion of RBDG concerning the RPO is formulated in the objective function. Therefore, a novel approach to modeling the composite DNP problem in the regulated power system is proposed in this paper. The goal is to increase the allocation of PVDG, WTDG, and GSESS in DNP to improve the quicker retirement of the fossil fuel-based power plant to increase total profits for the distribution network operator (DNO), and improve the voltage deviation, reduce carbon emissions over a defined planning period. The increment in RPO and decrement in the power purchase agreement will help DNO to fulfill round-the-clock supply for all classes of consumers. A recently developed new metaheuristic transient search optimization (TSO) based on electrical storage elements’ stimulation behavior is implemented to find the optimal solution for multi-objective function. The balance between the exploration and exploitation capability makes the TSO suitable for the proposed power flow problem with PVDG, WTDG, and GSESS. For this research, the IEEE-33 and IEEE-69 low and medium bus distribution networks are considered under a defined load growth for planning duration with the distinct load demand models’ aggregation. The findings of the results after comparing with well-known optimization techniques DE and PSO confirm the feasibility of the method suggested.


2021 ◽  
Author(s):  
Chinmay Shah ◽  
Richard Wies

The conventional power distribution network is being transformed drastically due to high penetration of renewable energy sources (RES) and energy storage. The optimal scheduling and dispatch is important to better harness the energy from intermittent RES. Traditional centralized optimization techniques limit the size of the problem and hence distributed techniques are adopted. The distributed optimization technique partitions the power distribution network into sub-networks which solves the local sub problem and exchanges information with the neighboring sub-networks for the global update. This paper presents an adaptive spectral graph partitioning algorithm based on vertex migration while maintaining computational load balanced for synchronization, active power balance and sub-network resiliency. The parameters that define the resiliency metrics of power distribution networks are discussed and leveraged for better operation of sub-networks in grid connected mode as well as islanded mode. The adaptive partition of the IEEE 123-bus network into resilient sub-networks is demonstrated in this paper.


Author(s):  
Alex Takeo Yasumura Lima Silva ◽  
Fernando Das Graças Braga da Silva ◽  
André Carlos da Silva ◽  
José Antonio Tosta dos Reis ◽  
Claudio Lindemberg de Freitas ◽  
...  

 Inefficiency of sanitation companies’ operation procedures threatens the population’s future supplies. Thus, it is essential to increase water and energy efficiency in order to meet future demand. Optimization techniques are important tools for the analysis of complex problems, as in distribution networks for supply. Currently, genetic algorithms are recognized by their application in literature. In this regard, an optimization model of water distribution network is proposed, using genetic algorithms. The difference in this research is a methodology based on in-depth analysis of results, using statistics and the design of experimental tools and software. The proposed technique was applied to a theoretical network developed for the study. Preliminary simulations were accomplished using EPANET, representing the main causes of water and energy inefficiency in Brazilian sanitation companies. Some parameters were changed in applying this model, such as reservoir level, pipe diameter, pumping pressures, and valve-closing percentage. These values were established by the design of experimental techniques. As output, we obtained the equation of response surface, optimized, which resulted in values of established hydraulic parameters. From these data, the obtained parameters in computational optimization algorithms were applied, resulting in losses of 26.61%, improvement of 16.19 p.p. with regard to the network without optimization, establishing an operational strategy involving three pumps and a pressure-reducing valve.  We conclude that the association of optimization and the planning of experimental techniques constitutes an encouraging method to deal with the complexity of water-distribution network optimization.


2019 ◽  
Vol 63 (4) ◽  
pp. 320-331
Author(s):  
Kothuri Ramakrishna ◽  
Basavaraja Banakara

Common technique has been discussed in this paper for the reconfiguration of feeder network by optimal location and measuring of Distribution Generator (DG) in electrical power system. The consolidated execution of both Biography Based Optimization (BBO) and Particle Swarm Optimization (PSO) strategies are the curiosity of the proposed strategy. The optimization techniques are utilized for optimizing the optimum location and DG capacity for radial distribution network. The BBO algorithm requires radial distribution network voltage, real and reactive power for deciding the optimum location and capacity of the DG. Here, the input parameters of BBO are classified into sub parameters and permitted as the PSO algorithm optimization process. The PSO develops the sub solution with the assistance of sub parameters by issue synthesis. For identifying the optimum location and capacity of DG the BBO movement and mutation process is applied for the sub solution of PSO. At that point the proposed mutual technique is actualized in the MATLAB/simulink platform and by contrasting it with the BBO and PSO systems the effectiveness is scrutinized. The comparison results demonstrate the predominance of the proposed approach and affirm its capability to comprehend the issue.


2015 ◽  
Vol 75 ◽  
pp. 1147-1152 ◽  
Author(s):  
Ruifeng Dong ◽  
Yunsong Yu ◽  
Zaoxiao Zhang

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