Multi-Objective Optimal Performance of a Hybrid CPSD-SE/HWT System for Microgrid Power Generation

2022 ◽  
pp. 166-210
Author(s):  
Bashar Shboul ◽  
Ismail Al-Arfi ◽  
Stavros Michailos ◽  
Derek Ingham ◽  
Godfrey T. Udeh ◽  
...  
Keyword(s):  
Economic Performance ◽  
Dynamic Performance ◽  
Electrical Power ◽  
Operating Conditions ◽  
Multi Objective ◽  
Cost Of Energy ◽  
One Year ◽  
Net Power Output ◽  
Dynamic Performance Analysis

A new integrated hybrid solar thermal and wind-based microgrid power system is proposed. It consists of a concentrated parabolic solar dish Stirling engine, a wind turbine, and a battery bank. The electrical power curtailment is diminished, and the levelised cost of energy is significantly reduced. To achieve these goals, the present study conducts a dynamic performance analysis over one year of operation. Further, a multi-objective optimisation model based on a genetic algorithm is implemented to optimise the techno-economic performance. The MATLAB/Simulink® software was used to model the system, study the performance under various operating conditions, and optimise the proposed hybrid system. Finally, the model has been implemented for a specific case study in Mafraq, Jordan. The system satisfies a net power output of 1500 kWe. The developed model has been validated using published results. In conclusion, the obtained results reveal that the optimised model of the microgrid can substantially improve the overall efficiency and reduce the levelised cost of electricity.

Optimal Design of Modified Power System Stabilizer Using Multi Objective Based Bio Inspired Algorithms

2018 ◽  
Vol 7 (4) ◽  
pp. 17-55 ◽  
Author(s):  
Dasu Butti ◽  
Siva Kumar Mangipudi ◽  
Srinivasarao Rayapudi
Keyword(s):  
Power System ◽  
Dynamic Performance ◽  
Operating Conditions ◽  
Power System Stabilizer ◽  
Value Analysis ◽  
Multi Objective ◽  
De Algorithm ◽  
System Data ◽  
Bus Voltage ◽  
System Stabilizer

In this article, a multi objective and a novel objective based Power System Stabilizer (PSS) design is proposed for a modified Heffron - Philiphs model (MHP) using bio inspired algorithms. A conventional Heffron – Philphs (CHP) model is developed by taking infinite bus voltage as reference, whereas MHP model is developed by taking transformer high voltage bus voltage as reference, which makes independent of external system data for the PSS design. PSS parameters are optimized using differential evolution (DE) algorithm and Firefly (FF) algorithm to obtain better dynamic response. The proposed method is tested on various operating conditions under different typical disturbances to test efficacy and robustness. Simulation results prove that better dynamic performance is obtained with the proposed stabilizers over the fixed gain stabilizers. This method of tuning would become a better alternative to conventional stabilizers as conventional stabilizers require retuning of parameters mostly when operating condition changes, which is a time-consuming process and laborious. Eigen value analysis is also done to prove the efficacy of the proposed method over the conventional methods.

scholarly journals Multi-Objective Predictive Control Optimization with Varying Term Objectives: A Wind Farm Case Study

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 778 ◽  
Author(s):  
Clara M. Ionescu ◽  
Constantin F. Caruntu ◽  
Ricardo Cajo ◽  
Mihaela Ghita ◽  
Guillaume Crevecoeur ◽  
...  
Keyword(s):  
Predictive Control ◽  
Wind Farm ◽  
Cost Effective ◽  
Optimality Criteria ◽  
Operating Conditions ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Efficiency Cost

This paper introduces the incentive of an optimization strategy taking into account short-term and long-term cost objectives. The rationale underlying the methodology presented in this work is that the choice of the cost objectives and their time based interval affect the overall efficiency/cost balance of wide area control systems in general. The problem of cost effective optimization of system output is taken into account in a multi-objective predictive control formulation and applied on a windmill park case study. A strategy is proposed to enable selection of optimality criteria as a function of context conditions of system operating conditions. Long-term economic objectives are included and realistic simulations of a windmill park are performed. The results indicate the global optimal criterium is no longer feasible when long-term economic objectives are introduced. Instead, local sub-optimal solutions are likely to enable long-term energy efficiency in terms of balanced production of energy and costs for distribution and maintenance of a windmill park.

scholarly journals Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7084
Author(s):  
Fadi Kahwash ◽  
Basel Barakat ◽  
Ahmad Taha ◽  
Qammer H. Abbasi ◽  
Muhammad Ali Imran
Keyword(s):  
Renewable Energy ◽  
Electrical Power ◽  
Energy System ◽  
Optimal Solutions ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Cost Of Energy ◽  
The Uk ◽  
Hybrid Renewable Energy

This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simulations were carried out using the actual and forecasted parameters to improve decision making. The results show that incorporating forecasted parameters into the optimisation allows to identify the subset of optimal solutions that will become sub-optimal in the future and, therefore, should be avoided. Finally, a framework for choosing the most suitable subset of optimal solutions was presented.

Differential Evolution Algorithm Optimized Dual Mode Load Frequency Controller for Isolated Wind-Diesel Power System with SMES & Fuel Cell

2019 ◽  
Vol 12 (1) ◽  
pp. 50-60
Author(s):  
Deepak Kumar Lal ◽  
Ajit K. Barisal ◽  
Manish Tripathy
Keyword(s):  
Fuel Cell ◽  
Power System ◽  
Differential Evolution ◽  
Dynamic Performance ◽  
Differential Evolution Algorithm ◽  
Operating Conditions ◽  
Dual Mode ◽  
Load Frequency ◽  
Frequency Controller ◽  
Dynamic Performance Analysis

Background: This paper presents dynamic performance analysis of isolated wind-diesel power system. A dual mode controller is proposed for pitch control of wind turbine generator. Methods: The parameters of the controller are optimized by Differential Evolution (DE) algorithm. The hybrid model was simulated with the proposed load frequency controller (LFC) by considering step load perturbation. The minimization of time multiplied integral of absolute error is considered as the objective function. The performance of the proposed controller is compared with the published result of the optimal controller. Further, the performance of the system is investigated by incorporating Super Conducting Magnetic Energy Storage (SMES) and Fuel Cell (FC). Also, the dynamic performance is investigated for changing step load perturbations. Furthermore, the response of the system is analyzed towards random loading. Results: Finally, sensitivity analysis is done by varying the system parameters and operating conditions from their nominal values. Conclusion: The simulation results show that the proposed dual mode DE optimized controller gives better transient and steady state response.

Power Test System Development and Dynamic Performance State Estimation Based on Hub Motor Vehicle

2020 ◽  
Vol 13 (2) ◽  
pp. 126-140
Author(s):  
Jing Gan ◽  
Xiaobin Fan ◽  
Zeng Song ◽  
Mingyue Zhang ◽  
Bin Zhao
Keyword(s):  
Real Time ◽  
Dynamic Performance ◽  
Test System ◽  
Operating Conditions ◽  
Motor Vehicles ◽  
Maximum Speed ◽  
Performance Parameters ◽  
Power Performance ◽  
Power Test ◽  
The Real

Background: The power performance of an electric vehicle is the basic parameter. Traditional test equipment, such as the expensive chassis dynamometer, not only increases the cost of testing but also makes it impossible to measure all the performance parameters of an electric vehicle. Objective: A set of convenient, efficient and sensitive power measurement system for electric vehicles is developed to obtain the real-time power changes of hub-motor vehicles under various operating conditions, and the dynamic performance parameters of hub-motor vehicles are obtained through the system. Methods: Firstly, a set of on-board power test system is developed by using virtual instrument (Lab- VIEW). This test system can obtain the power changes of hub-motor vehicles under various operating conditions in real-time and save data in real-time. Then, the driving resistance of hub-motor vehicles is analyzed, and the power performance of hub-motor vehicles is studied in depth. The power testing system is proposed to test the input power of both ends of the driving motor, and the chassis dynamometer is combined to test so that the output efficiency of the driving motor can be easily obtained without disassembly. Finally, this method is used to carry out the road test and obtain the vehicle dynamic performance parameters. Results: The real-time current, voltage and power, maximum power, acceleration time and maximum speed of the vehicle can be obtained accurately by using the power test system in the real road experiment. Conclusion: The maximum power required by the two motors reaches about 9KW, and it takes about 20 seconds to reach the maximum speed. The total power required to maintain the maximum speed is about 7.8kw, and the maximum speed is 62km/h. In this article, various patents have been discussed.

Pareto Set as a Model for Dispatching Resources in Emergency Centres (Preprint)

2018 ◽  
Author(s):  
Ricardo Guedes ◽  
Vasco Furtado ◽  
Tarcísio Pequeno ◽  
Joel Rodrigues
Keyword(s):  
Operational Research ◽  
Real Data ◽  
Pareto Set ◽  
Multi Objective Optimization ◽  
Pareto Dominance ◽  
Four Dimensions ◽  
Multi Objective ◽  
The Best Approximation ◽  
One Year ◽  
The Cost

UNSTRUCTURED The article investigates policies for helping emergency-centre authorities for dispatching resources aimed at reducing goals such as response time, the number of unattended calls, the attending of priority calls, and the cost of displacement of vehicles. Pareto Set is shown to be the appropriated way to support the representation of policies of dispatch since it naturally fits the challenges of multi-objective optimization. By means of the concept of Pareto dominance a set with objectives may be ordered in a way that guides the dispatch of resources. Instead of manually trying to identify the best dispatching strategy, a multi-objective evolutionary algorithm coupled with an Emergency Call Simulator uncovers automatically the best approximation of the optimal Pareto Set that would be the responsible for indicating the importance of each objective and consequently the order of attendance of the calls. The scenario of validation is a big metropolis in Brazil using one-year of real data from 911 calls. Comparisons with traditional policies proposed in the literature are done as well as other innovative policies inspired from different domains as computer science and operational research. The results show that strategy of ranking the calls from a Pareto Set discovered by the evolutionary method is a good option because it has the second best (lowest) waiting time, serves almost 100% of priority calls, is the second most economical, and is the second in attendance of calls. That is to say, it is a strategy in which the four dimensions are considered without major impairment to any of them.

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