Economic Load Dispatch Monitoring and Optimization for Emission Control Using Flower Pollination Algorithm: A Case Study

2021 ◽  
pp. 249-268
Author(s):  
Deepesh Mali ◽  
D. Saxena ◽  
Rajeev Kumar Chauhan
Keyword(s):  
Emission Control ◽  
Flower Pollination Algorithm ◽  
Economic Load Dispatch ◽  
Flower Pollination

scholarly journals PSS Tuning on Power Generator System using Flower Pollination Algorithm

2018 ◽  
Vol 6 (3) ◽  
pp. 93-99
Author(s):  
Muhammad Ruswandi Djalal ◽  
Sonong Sonong
Keyword(s):  
Bat Algorithm ◽  
Flower Pollination Algorithm ◽  
Generator System ◽  
Steady State Condition ◽  
Tuning Method ◽  
Flower Pollination ◽  
Velocity Deviation ◽  
Rotor Angle ◽  
System Stabilizer

This research proposed a tuning method of power system stabilizer (PSS) using an intelligent method based on flower pollination algorithm (FPA) on Pajalesang generator located in Soppeng district. The observed result is the deviation response of velocity and rotor angle in case of disturbance. The case study used as the disturbance to this generator system is a load addition of 0.05 pu. The results show that velocity deviation response without PSS is 0.01152 pu to -0.0248 pu, using PSS trial is 0.007014 pu to -0.02174 pu, using PSS bat algorithm is 0.003972 pu to -0.01865 pu, and using the proposed method of PSS flower algorithm is 0.002149 pu to -0.01678 pu. The rotor angle response shows better results with reduced oscillation and rapidly leading to the steady-state condition. The performance of Pajalesang diesel power plant increased with the installation of FPA PSS, with parameters respectively Kpss=8.5956, T1= 0.0247, T2=0.2484, T3=0.4776, and T4=0.8827.

An Enhanced Flower Pollination Algorithm for Power System Economic Load Dispatch

2021 ◽  
pp. 77-86
Author(s):  
Hung-Peng Lee ◽  
Trong-The Nguyen ◽  
Thi-Kien Dao ◽  
Van-Dinh Vu ◽  
Truong-Giang Ngo
Keyword(s):  
Power System ◽  
Flower Pollination Algorithm ◽  
Economic Load Dispatch ◽  
Flower Pollination

scholarly journals Flower Pollination Algorithm to Solve Dynamic Economic Loading of Units with Practical Constraints

2019 ◽  
Vol 8 (3) ◽  
pp. 535-542
Keyword(s):  
Flower Pollination Algorithm ◽  
Economic Load Dispatch ◽  
Power Losses ◽  
Complex Issue ◽  
Flower Pollination ◽  
Valve Point Effect ◽  
Non Linear ◽  
Simulation Results ◽  
Practical Constraints

Dynamic h“economic load dispatch (DELD) aims to obtain optimum generation schedule of the committed generating units’ output over ha certain timing horizon”, sustaining practical restrictions and power demands in each period.”Valve-point effect, the ramp up/down limits, prohibited operation zones (POZs), and power losses form the hDELD has ha complex, non-linear liable’ problem. The Flower Pollination Algorithm (FPA) his therefore anticipated in this paper to solve such a complex issue. The practicality of the proposed FPA method is assessed by conducting simulations at different load patterns hon standard 5-unit and 10-unit systems for ha 24-hour schedule. The FPA's simulation results hare related to other previously published biography techniques. These results clearly show that the skill hand robustness hof the proposed FPA method to solve the non h- linear DELD problem has been restricted.

Modeling and Optimal Control Applying the Flower Pollination Algorithm to Doubly Fed Induction Generators on a Wind Farm in a Hot Arid Climate

2021 ◽  
Vol 143 (4) ◽  
Author(s):  
Omar Chogueur ◽  
Saïd Bentouba ◽  
Mahmoud Bourouis
Keyword(s):  
Wind Farm ◽  
Short Circuit ◽  
Pi Controller ◽  
Electrical Network ◽  
Flower Pollination Algorithm ◽  
Dynamic Mode ◽  
Flower Pollination ◽  
First Case ◽  
Doubly Fed

Abstract In the present paper, the flower pollination algorithm (FPA) is employed for tuning the controller parameters of a doubly fed induction generator (DFIG) in a wind energy system. These parameters are then compared with those generated by the genetic algorithm (GA) and the proportional-integral (PI) (initial design) controllers. Performance analysis of the DFIG is carried out in dynamic mode in two case studies. The first case study is carried out with no failure, the second one is subject to a short circuit in the electrical network. In this latter case study, a break occurs in the rotor circuit and disconnects the DFIG from the power grid. This gives rise to an excessive current in the rotor circuit which in turn influences the converters AC/DC/AC and makes the IGBT very sensitive. The GA and the FPA are used to tune the PI controllers with the purpose of improving the quality of a power supply should electrical disturbances occur. The results show that by applying an optimal PI controller design to a DFIG using the FPA the performance of the DFIG system can be improved in the event of disturbances. When the PI controller tuning using the GA and the initial control system design is compared with the DFIG using the optimized design, a significant decrease in the overshoot of the rotor current and the DC-link voltage is observed.

scholarly journals Optimal Power Flow Using Flower Pollination Algorithm: A Case Study of 500 kV Java-Bali Power System

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Fredi Prima Sakti ◽  
Sarjiya Sarjiya ◽  
Sasongko Pramono Hadi
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Problems ◽  
Flower Pollination Algorithm ◽  
Flower Pollination ◽  
Optimal Power ◽  
Metaheuristic Methods ◽  
Owned Company

Flower Pollination Algorithm (FPA) is one of metaheuristic methods that is widely used in optimization problems. This method was inspired by the nature of flower pollination. In this research, FPA is applied to solve Optimal Power Flow (OPF) problems with case study of 500 kV Java-Bali power system in Indonesia. The system consists of 25 bus with 30 lines and 8 generating units. Control variables are generation of active power and voltage magnitude at PV bus and swing bus under several power system constraints. The results show that FPA method is capable of solving OPF problem. This method decreased the generator fuel cost of PT. PLN (Persero), the state-owned company in charge of providing electricity in Indonesia, up to 13.15%.

A Comparative Analysis on Economic Load Dispatch Problem Using Soft Computing Techniques

2020 ◽  
Vol 12 (2) ◽  
pp. 50-73 ◽  
Author(s):  
O.V. Singh ◽  
M. Singh
Keyword(s):  
Search Algorithm ◽  
Optimal Solution ◽  
Inequality Constraints ◽  
Optimization Techniques ◽  
Flower Pollination Algorithm ◽  
Economic Load Dispatch ◽  
Flower Pollination ◽  
Soft Computing Techniques ◽  
Equality And Inequality Constraints ◽  
Optimization Search

This article aims at solving economic load dispatch (ELD) problem using two algorithms. Here in this article, an implementation of Flower Pollination (FP) and the BAT Algorithm (BA) based optimization search algorithm method is applied. More than one objective is hoped to be achieve in this article. The combined economic emission dispatch (CEED) problem which considers environmental impacts as well as the cost is also solved using the two algorithms. Practical problems in economic dispatch (ED) include both nonsmooth cost functions having equality and inequality constraints which make it difficult to find the global optimal solution using any mathematical optimization. In this article, the ELD problem is expressed as a nonlinear constrained optimization problem which includes equality and inequality constraints. The attainability of the discussed methods is shown for four different systems with emission and without emission and the results achieved with FP and BAT algorithms are matched with other optimization techniques. The experimental results show that conferred Flower Pollination Algorithm (FPA) outlasts other techniques in finding better solutions proficiently in ELD problems.

scholarly journals DYNAMIC PROBABILITY SELECTION FOR FLOWER POLLINATION ALGORITHM BASED ON METROPOLISHASTINGS CRITERIA

2020 ◽  
Vol 20 ◽  
Author(s):  
Kamal Zuhairi Zamli ◽  
Fakhrud Din ◽  
Abdullah Nasser ◽  
Nazirah Ramli ◽  
Noraini Mohamed
Keyword(s):  
Heuristic Algorithms ◽  
Flower Pollination Algorithm ◽  
Adaptive Selection ◽  
Dynamic Selection ◽  
Flower Pollination ◽  
Selection For ◽  
Test Suite Generation ◽  
Selection Of

Flower Pollination Algorithm (FPA) is a relatively new meta-heuristic algorithm that adopts its metaphor from the proliferation role of flowers in plants. Having only one parameter control (i.e. the switch probability, pa) to choose from the global search (i.e. exploration) and local search (i.e. exploitation) is the main strength of FPA as compared to other meta-heuristic algorithms. However, FPA still suffers from variability of its performance as there is no one size that fits all values for pa, depending on the characteristics of the optimisation function. This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. Adopting the problem of t-way test suite generation as the case study and with the comparative evaluation with the original FPA, FPA-MH gave promising results owing to its dynamic and adaptive selection of search operators based on the need of the current search.  

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