Economic Assessment of Advanced Control Devices and Renewable Energy Sources in Island Power Systems Using a Weekly Unit Commitment Model

2016 ◽  
pp. 231-278
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Economic Assessment ◽  
Energy Sources ◽  
Advanced Control ◽  
Control Devices

Unit Commitment Incorporating Wind Generators Considering Emission Reduction

2011 ◽  
Vol 347-353 ◽  
pp. 3973-3977
Author(s):  
Xiao Hua Zhang ◽  
Jin Quan Zhao ◽  
Xing Ying Chen
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Power Systems ◽  
Emission Reduction ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Primary Energy ◽  
Energy Sources ◽  
Primary Energy Consumption ◽  
Wind Generators

The rise of environmental protection and the progressive exhaustion of traditional fossil energy sources have increased the interest in integrating renewable energy sources into existing power systems. The energy saving and emission reduction is of most importance. Wind energy could be one of the most promising renewable energy sources. However, the intermittency and unpredictability of wind power generation creates difficulty in control of frequency and generation scheduling. Many problems will arise in the renewable energy based hybrid power system. In this paper, a fuzzy unit commitment model including wind generators is presented. Primary energy consumption, gas emission and the risk of wind are synthetically considered. Through defining membership function, the deterministic problem is transformed into the fuzzy problem. Then it is reformulated into the nonlinear problem by means of the maximum-minimum fuzzy satisfaction. Improved Genetic Algorithms (IGA) is used to solve the fuzzy optimization problem. The simulation results of a 10-unit system demonstrate that the proposed method is feasible. It can compromise between the primary energy consumption and the risk according to the decision-maker’s will. It provides valuable information in both operational and planning problems in the future.

scholarly journals Methodology of optimum unit commitment of energy systems with renewable energy sources

Vestnik IGEU ◽  
2020 ◽  
pp. 25-38
Author(s):  
S.G. Obukhov ◽  
G.N. Klimova ◽  
A. Ibrahim
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Electric Power ◽  
Optimization Problem ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Electric Power Systems ◽  
Electric Power System ◽  
Energy Sources ◽  
Particle Swarm Algorithm

One of the promising ways to improve the reliability and efficiency of power supply for customers in the areas remote from central electrical grid is the use of hybrid power systems with renewable energy sources. The primary task of designing such systems is the unit commitment of the generating equipment that provides the optimal technical and economic indexes of the electric power system. The stochastic nature of generation and nonlinearity of the characteristics of power plants cause a high complexity of solving this problem, which, from a mathematical point of view, is formulated as an optimization problem. An accurate and reliable solution of this optimization problem increases the efficiency of design and operation of hybrid electric power systems with renewable energy sources. And it is a vital task of modern power industry. A probabilistic-statistical methods and models for the analysis of experimental data are used to construct climatic time series and graphs of electrical loads. In addition, to study the operating modes of the electric power system the MatLab system is used for the simulation and modeling, and an evolutionary particle swarm algorithm is used to solve the optimization problem. The original model of solar radiation is used as a part of this methodology. This model provides forecasting the key characteristics of solar radiation in any geographical point of Russia including the areas that have no results of routine actinometric observation. Weibull distribution function is used to forecast daily variations of wind speed. It enhances the validity of forecasting of electricity generation of wind-driven power plant at daily time interval. As a result of the research, a method of optimum unit commitment has been developed for the equipment of electric power systems based on renewable energy sources. The use of the particle swarm algorithm as a part of the methodology provides reliable and accurate determination of the extremum of the objective function, which increases the efficiency of design and operation of hybrid electric power systems with renewable energy sources. The method has been tested on practical examples of optimum unit commitment for the equipment of electric power systems of various configurations and has proven its effectiveness. The technique is implemented as a software application, which ensures the convenience of its practical application. The obtained results can be used by companies involved in the design and operation of electric power systems using renewable energy generating units.

scholarly journals An Adaptive Load Frequency Control for Power Systems with Renewable Energy Sources

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 573
Author(s):  
Mohamed Mokhtar ◽  
Mostafa I. Marei ◽  
Mariam A. Sameh ◽  
Mahmoud A. Attia
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
System Performance ◽  
Frequency Control ◽  
Renewable Energy Sources ◽  
Adaptive Controller ◽  
Load Frequency Control ◽  
Energy Sources ◽  
Load Variations

The frequency of power systems is very sensitive to load variations. Additionally, with the increased penetration of renewable energy sources in electrical grids, stabilizing the system frequency becomes more challenging. Therefore, Load Frequency Control (LFC) is used to keep the frequency within its acceptable limits. In this paper, an adaptive controller is proposed to enhance the system performance under load variations. Moreover, the proposed controller overcomes the disturbances resulting from the natural operation of the renewable energy sources such as Wave Energy Conversion System (WECS) and Photovoltaic (PV) system. The superiority of the proposed controller compared to the classical LFC schemes is that it has auto tuned parameters. The validation of the proposed controller is carried out through four case studies. The first case study is dedicated to a two-area LFC system under load variations. The WECS is considered as a disturbance for the second case study. Moreover, to demonstrate the superiority of the proposed controller, the dynamic performance is compared with previous work based on an optimized controller in the third case study. Finally in the fourth case study, a sensitivity analysis is carried out through parameters variations in the nonlinear PV-thermal hybrid system. The novel application of the adaptive controller into the LFC leads to enhance the system performance under disturbance of different sources of renewable energy. Moreover, a robustness test is presented to validate the reliability of the proposed controller.

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