Development of Pareto strategy multi-objective function method for the optimum design of ship structures

This paper presents a practical methodology developed for shape optimization studies of hydraulic structures using environmental numerical modelling codes. The methodology starts by defining the optimization problem and identifying relevant problem constraints. Design variables in shape optimization studies are configuration of structures (such as length or spacing of groins, orientation and layout of breakwaters, etc.) whose optimal orientation is not known a priori. The optimization problem is solved numerically by coupling an optimization algorithm to a numerical model. The coupled system is able to define, test and evaluate a multitude of new shapes, which are internally generated and then simulated using a numerical model. The developed methodology is tested using an example of an optimum design of a fish passage, where the design variables are the length and the position of slots. In this paper an objective function is defined where a target is specified and the numerical optimizer is asked to retrieve the target solution. Such a definition of the objective function is used to validate the developed tool chain. This work uses the numerical model TELEMAC- 2Dfrom the TELEMAC-MASCARET suite of numerical solvers for the solution of shallow water equations, coupled with various numerical optimization algorithms available in the literature.

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Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

Journal of Engineering ◽

10.31026/j.eng.2018.03.07 ◽

2018 ◽

Vol 24 (3) ◽

pp. 84

Author(s):

Hassan Abdullah Kubba ◽

Mounir Thamer Esmieel

Keyword(s):

Genetic Algorithm ◽

Objective Function ◽

Power Flow ◽

Optimal Power Flow ◽

Reactive Power ◽

Test System ◽

Multi Objective ◽

Optimal Power ◽

Blending Method ◽

Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.

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Voltage Stability Enhancement with Optimal Placement of IPFC

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.d9748.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 9465-9471

Keyword(s):

Transmission Line ◽

Objective Function ◽

Search Algorithm ◽

Cuckoo Search ◽

Test System ◽

Optimal Location ◽

Optimal Placement ◽

Utilization Factor ◽

Location Selection ◽

Multi Objective

This paper presents a novel technique based on Cuckoo Search Algorithm (CSA) for enhancing the performance of multiline transmission network to reduce congestion in transmission line to huge level. Optimal location selection of IPFC is done using subtracting line utilization factor (SLUF) and CSA-based optimal tuning. The multi objective function consists of real power loss, security margin, bus voltage limit violation and capacity of installed IPFC. The multi objective function is tuned by CSA and the optimal location for minimizing transmission line congestion is obtained. The simulation is performed using MATLAB for IEEE 30-bus test system. The performance of CSA has been considered for various loading conditions. Results shows that the proposed CSA technique performs better by optimal location of IPFC while maintaining power system performance

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Multi-Objective Energy Management of a Micro-Grid Considering Stochastic Nature of Load and Renewable Energy Resources

Electronics ◽

10.3390/electronics10040403 ◽

2021 ◽

Vol 10 (4) ◽

pp. 403

Author(s):

Deyaa Ahmed ◽

Mohamed Ebeed ◽

Abdelfatah Ali ◽

Ali S. Alghamdi ◽

Salah Kamel

Keyword(s):

Renewable Energy ◽

Objective Function ◽

Energy Management ◽

Energy Resources ◽

Management Problem ◽

Renewable Energy Resources ◽

Multi Objective ◽

Stochastic Nature ◽

Whale Optimization ◽

Micro Grid

Optimal inclusion of a photovoltaic system and wind energy resources in electrical grids is a strenuous task due to the continuous variation of their output powers and stochastic nature. Thus, it is mandatory to consider the variations of the Renewable energy resources (RERs) for efficient energy management in the electric system. The aim of the paper is to solve the energy management of a micro-grid (MG) connected to the main power system considering the variations of load demand, photovoltaic (PV), and wind turbine (WT) under deterministic and probabilistic conditions. The energy management problem is solved using an efficient algorithm, namely equilibrium optimizer (EO), for a multi-objective function which includes cost minimization, voltage profile improvement, and voltage stability improvement. The simulation results reveal that the optimal installation of a grid-connected PV unit and WT can considerably reduce the total cost and enhance system performance. In addition to that, EO is superior to both whale optimization algorithm (WOA) and sine cosine algorithm (SCA) in terms of the reported objective function.

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