Optimized Dynamic Operation of Fixed-Speed Wind Farms Using Classical and Advanced Controllers

2020 ◽  
Vol 21 (2) ◽  
Author(s):  
Othman A. Omar ◽  
Niveen M. Badra ◽  
Mahmoud A. Attia ◽  
Ahmed Gad
Keyword(s):  
Renewable Energy ◽  
Output Power ◽  
Pitch Angle ◽  
Wind Farm ◽  
Wind Farms ◽  
Optimization Techniques ◽  
Energy Resources ◽  
Voltage Regulator ◽  
Renewable Energy Resources ◽  
Proportional Integral

AbstractElectric power systems are allowing higher penetration levels of renewable energy resources, mainly due to their environmental benefits. The majority of electrical energy generated by renewable energy resources is contributed by wind farms. However, the stochastic nature of these resources does not allow the installed generation capacities to be entirely utilized. In this context, this paper attempts to improve the performance of fixed-speed wind turbines. Turbines of this type have been already installed in some classical wind farms and it is not feasible to replace them with variable-speed ones before their lifetime ends. A fixed-speed turbine is typically connected to the electric grid with a Static VAR Compensator (SVC) across its terminal. For a better dynamic voltage response, the controller gains of a Proportional-Integral (PI) voltage regulator within the SVC will be tuned using a variety of optimization techniques to minimize the integrated square of error for the wind farm terminal voltage. Similarly, the controller gains of the turbine’s pitch angle may be tuned to enhance its dynamic output power performance. Simulation results, in this paper, show that the pitch angle controller causes a significant minimization in the integrated square of error for the wind farm output power. Finally, an advanced Proportional-Integral-Acceleration (PIA) voltage regulator controller has been proposed for the SVC. When the PIA control gains are optimized, they result in a better performance than the classical PI controller.

scholarly journals Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 627
Author(s):  
Mokhtar Said ◽  
Abdullah M. Shaheen ◽  
Ahmed R. Ginidi ◽  
Ragab A. El-Sehiemy ◽  
Karar Mahmoud ◽  
...  
Keyword(s):  
Experimental Data ◽  
Renewable Energy ◽  
Turbulent Flow ◽  
Optimization Algorithms ◽  
Real Data ◽  
Optimization Techniques ◽  
Environmental Benefits ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Unknown Parameters

Recently, the use of diverse renewable energy resources has been intensively expanding due to their technical and environmental benefits. One of the important issues in the modeling and simulation of renewable energy resources is the extraction of the unknown parameters in photovoltaic models. In this regard, the parameters of three models of photovoltaic (PV) cells are extracted in this paper with a new optimization method called turbulent flow of water-based optimization (TFWO). The applications of the proposed TFWO algorithm for extracting the optimal values of the parameters for various PV models are implemented on the real data of a 55 mm diameter commercial R.T.C. France solar cell and experimental data of a KC200GT module. Further, an assessment study is employed to show the capability of the proposed TFWO algorithm compared with several recent optimization techniques such as the marine predators algorithm (MPA), equilibrium optimization (EO), and manta ray foraging optimization (MRFO). For a fair performance evaluation, the comparative study is carried out with the same dataset and the same computation burden for the different optimization algorithms. Statistical analysis is also used to analyze the performance of the proposed TFWO against the other optimization algorithms. The findings show a high closeness between the estimated power–voltage (P–V) and current–voltage (I–V) curves achieved by the proposed TFWO compared with the experimental data as well as the competitive optimization algorithms, thanks to the effectiveness of the developed TFWO solution mechanism.

scholarly journals Optimal Sizing of Hybrid Wind-Solar Power Systems to Suppress Output Fluctuation

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5377
Author(s):  
Abdullah Al-Shereiqi ◽  
Amer Al-Hinai ◽  
Mohammed Albadi ◽  
Rashid Al-Abri
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Wind Power ◽  
Iterative Algorithm ◽  
Wind Farm ◽  
Energy Resources ◽  
Weather Data ◽  
Optimal Size ◽  
Renewable Energy Resources ◽  
The Impact

Harnessing wind energy is one of the fastest-growing areas in the energy industry. However, wind power still faces challenges, such as output intermittency due to its nature and output reduction as a result of the wake effect. Moreover, the current practice uses the available renewable energy resources as a fuel-saver simply to reduce fossil-fuel consumption. This is related mainly to the inherently variable and non-dispatchable nature of renewable energy resources, which poses a threat to power system reliability and requires utilities to maintain power-balancing reserves to match the supply from renewable energy resources with the real-time demand levels. Thus, further efforts are needed to mitigate the risk that comes with integrating renewable resources into the electricity grid. Hence, an integrated strategy is being created to determine the optimal size of the hybrid wind-solar photovoltaic power systems (HWSPS) using heuristic optimization with a numerical iterative algorithm such that the output fluctuation is minimized. The research focuses on sizing the HWSPS to reduce the impact of renewable energy resource intermittency and generate the maximum output power to the grid at a constant level periodically based on the availability of the renewable energy resources. The process of determining HWSPS capacity is divided into two major steps. A genetic algorithm is used in the initial stage to identify the optimum wind farm. A numerical iterative algorithm is used in the second stage to determine the optimal combination of photovoltaic plant and battery sizes in the search space, based on the reference wind power generated by the moving average, Savitzky–Golay, Gaussian and locally weighted linear regression techniques. The proposed approach has been tested on an existing wind power project site in the southern part of the Sultanate of Oman using a real weather data. The considered land area dimensions are 2 × 2 km. The integrated tool resulted in 39 MW of wind farm, 5.305 MW of PV system, and 0.5219 MWh of BESS. Accordingly, the estimated cost of energy based on the HWSPS is 0.0165 EUR/kWh.

scholarly journals Statistical Analysis of Renewable Energy Resources of Pakistan

2021 ◽  
Vol 9 (4) ◽  
pp. 508-514
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Renewable Resources ◽  
Energy Demand ◽  
Wind Farms ◽  
Electrical Energy ◽  
Energy Resources ◽  
Wind Data ◽  
Atmospheric Conditions ◽  
Renewable Energy Resources

Despite of being one of the richest countries in energy resources Pakistan is facing a huge short fall of electrical energy as energy demand is increasing rapidly but increase in generation capability is much slow. Currently Pakistan is using a huge amount of non-renewable energy resources to produce electricity which is not only expensive but also affecting the environment due to by-products of this process. This is a common trend throughout the world to use renewable resources of energy as it is economical and nature friendly. This paper gives an overview of currently used methods for power generation in Pakistan and a gives a brief detail on how and in which areas of the country power generation can be done using renewable resources of energy. Cost of installing the system is also one of the most important factors but will not be discussed here because purpose of this paper is only to help the reader to know about different renewable resources of energy. Numerous types of wind turbines i.e. Bonus 300/33.4, NEG/Micon 1000/60, Vestas 600/42 and Whisper 0.9/2.13 have been statistically analyzed, for the energy they could ideally produce, under the same atmospheric conditions. The coasts of Karachi are proposed to be among the ideal, most suitable sites, for the erection of wind farms, in Pakistan. Wind-Data for the year 2003 (previously acquired through anemometers) is processed in “MATLAB” to implement the “Curve Fitting techniques” adjusting the “k” and “c”, the shape and scale parameters, respectively, of the “Weibull Distribution” so that the refined Wind-Data curves resemble the ones made by the Raw-Data, minus the anomalies. Furthermore, the refined data is then extracted to be populated in the spreadsheets for mathematical/statistical calculations

Economic Dispatch in Power System Networks Including Renewable Energy Resources using Various Optimization Techniques

2021 ◽  
Author(s):  
Mustefa Jibril ◽  
Mesay Tadesse ◽  
Nurye Hassen
Keyword(s):  
Particle Swarm Optimization ◽  
Renewable Energy ◽  
Power System ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Optimization Techniques ◽  
Energy Resources ◽  
Renewable Energy Resources ◽  
Traditional Methods ◽  
Swarm Optimization

Economic dispatch (ED) is an essential part of any power system network. ED is how to schedule the real power outputs from the available generators to get the minimum cost with satisfying all constraints of the network. Also it can be explained as allocating generation among the committed units with the most effective minimum way in accordance with all constraints of the system. There are many traditional methods for solving ED as the Newton-Raphson Method, Lambda-Iterative technique, Gaussian-Seidel Method, etc. All these traditional methods need the generators’ incremental fuel cost curves to be increasing linearly. But practically the input-output characteristics of a generator are highly non-linear. This causes a challenging non-convex optimization problem. Recent techniques like genetic algorithms, artificial intelligence, dynamic programming and particle swarm optimization solve nonconvex optimization problems in a powerful way and obtain a rapid and near global optimum solution. In addition, renewable energy resources as wind and photovoltaic have been a promising option due to the environmental concerns as the fossil fuels reserves are being consumed and fuel price increases rapidly and emissions are getting higher. Therefore, the world tends to replace the old power stations into renewable ones or hybrid stations. In this paper, we attempt to enhance the operation of electrical power system networks via economic dispatch. An ED problem has been solved using various techniques as particle swarm optimization and a sine-cosine algorithm and the results have been compared. Moreover, case studies have been executed using a photovoltaic-based distributed generator with constant penetration level on the IEEE 14 bus system and results are observed. All the analyses have been made on MATLAB software.

scholarly journals Thermodynamic Optimization of a Geothermal Power Plant with a Genetic Algorithm in Two Stages

Processes ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1277 ◽  
Author(s):  
Mehdi A. Ehyaei ◽  
Abolfazl Ahmadi ◽  
Marc A. Rosen ◽  
Afshin Davarpanah
Keyword(s):  
Genetic Algorithm ◽  
Renewable Energy ◽  
Power Plant ◽  
Output Power ◽  
Flow Rate ◽  
Energy Resources ◽  
Fluid Temperature ◽  
Renewable Energy Resources ◽  
Geothermal Fluid ◽  
Two Stages

Due to the harmful effects and depletion of non-renewable energy resources, the major concerns are focused on using renewable energy resources. Among them, the geothermal energy has a high potential in volcano regions such as the Middle East. The optimization of an organic Rankine cycle with a geothermal heat source is investigated based on a genetic algorithm having two stages. In the first stage, the optimal variables are the depth of the well and the extraction flow rate of the geothermal fluid mass. The optimal value of the depth of the well, extraction mass flow rate, and the geothermal fluid temperature is found to be 2100 m, 15 kg/s, and 150 °C. In the second stage, the efficiency and output power of the power plant are optimized. To achieve maximum output power as well as cycle efficiency, the optimization variable is the maximum organic fluid pressure in the high-temperature heat exchanger. The optimum values of energy efficiency and cycle power production are equal to 0.433 MW and 14.1%, respectively.

scholarly journals Design and Development of Dual Power Generation Solar and Windmill Generator

2020 ◽  
pp. 447-454
Author(s):  
Firas B. Ismail ◽  
◽  
Nizar F.O. Al-Muhsen ◽  
Norul Ilham Noruddin
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Output Power ◽  
Average Energy ◽  
Energy Resources ◽  
Industrial Safety ◽  
Superior Performance ◽  
Secondary Source ◽  
Wind System ◽  
Renewable Energy Resources

The fast depletion of conventional energy resources and the issue of global warming have encouraged researchers worldwide to come up with the best energy solution. Renewable energy resources such as wind and solar energy have been widely adopted as an alternative source of energy. In this work, an integrated solar and wind energy system were implemented aiming to produce the maximum possible output power from the available renewable energy resources such as solar irradiance and wind energy. The proposed system comprised two solar modules and horizontally rotating wind blades. An energy storage system plus a charge controller were also used aiming to improve the overall energy conversion efficiency. The results showed that this system demonstrated superior performance compared with the solar modules and wind system when they had worked individually. The proposed system was generating an average energy of 61.729 Wh daily. Therefore, it was estimated that the system can generate an annual output power of about 207.4 kWh. During the conducted experiments, the solar panels worked as the main source of the generated energy while the wind system acted as a secondary source of energy during the solar absent times. Moreover, the safety factor was calculated to be within the limits of 2 that shows the proposed system can work according to the industrial safety limits of Malaysia.

scholarly journals A Comprehensive Review on Integration Challenges, Optimization Techniques and Control Strategies of Hybrid AC/DC Microgrid

2021 ◽  
Vol 11 (14) ◽  
pp. 6242
Author(s):  
Omar Azeem ◽  
Mujtaba Ali ◽  
Ghulam Abbas ◽  
Muhammad Uzair ◽  
Ayman Qahmash ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Control Strategies ◽  
Optimization Techniques ◽  
Energy Resources ◽  
Effective Control ◽  
Renewable Energy Resources ◽  
Concentrated Load ◽  
Dc Microgrids ◽  
Hybrid Microgrid ◽  
And Control

The depletion of natural resources and the intermittence of renewable energy resources have pressed the need for a hybrid microgrid, combining the benefits of both AC and DC microgrids, minimizing the overall deficiency shortcomings and increasing the reliability of the system. The hybrid microgrid also supports the decentralized grid control structure, aligning with the current scattered and concentrated load scenarios. Hence, there is an increasing need to explore and reveal the integration, optimization, and control strategies regarding the hybrid microgrid. A comprehensive study of hybrid microgrid’s performance parameters, efficiency, reliability, security, design flexibility, and cost-effectiveness is required. This paper discusses major issues regarding the hybrid microgrids, the integration of AC and DC microgrids, their security and reliability, the optimization of power generation and load management in different scenarios, the efficient management regarding uncertainty for renewable energy resources, the optimal placement of feeders, and the cost-effective control methodologies for the hybrid microgrid. The major research areas are briefly explained, aiming to find the research gap that can further improve the performance of the grid. In light of the recent trends in research, novel strategies are proposed that are found most effective and cost-friendly regarding the hybrid microgrid. This paper will serve as a baseline for future research, comparative analysis, and further development of novel techniques regarding hybrid microgrids.

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