Optimization of the wind farm structure through the use of PV installations and the use of pumped storage power plants

2022 ◽  
Vol 1 (1) ◽  
pp. 86-89
Author(s):  
Joanna KOZIEŁ
Keyword(s):  
Power Plants ◽  
Wind Farm ◽  
Farm Structure ◽  
Pumped Storage

Optimal Operation Model for Virtual Power Plant in Datong Area

2015 ◽  
Vol 785 ◽  
pp. 627-631 ◽  
Author(s):  
Hei Wei ◽  
Rasyidah Mohamed Idris
Keyword(s):  
Power Plant ◽  
Wind Power ◽  
Power Plants ◽  
Large Scale ◽  
Wind Farm ◽  
Thermal Power ◽  
Optimal Operation ◽  
Virtual Power ◽  
Virtual Power Plant ◽  
Pumped Storage

Datong area has abundant wind energy. Due to problem in large scale of wind power grid connection, this paper introduces virtual power plant concept. As for beginning, power source characteristics of the wind farm, pumped storage power station and the thermal power plant are taken for analysis. Three types of different power plants are chosen to represent the virtual power plant modeling as well as adopting the NSGA2 optimization. As a conclusion, this case study proved that virtual power plant can increase the benefits of each power plant and the wind power plant output power curve become smoother.

scholarly journals Optimizing operation of a large-scale pumped storage hydropower system coordinated with wind farm by means of genetic algorithms

2019 ◽  
Keyword(s):  
Genetic Algorithms ◽  
Renewable Energy ◽  
Wind Energy ◽  
Large Scale ◽  
Wind Farm ◽  
Closed Loop ◽  
Open Loop ◽  
Energy Output ◽  
Reservoir System ◽  
Pumped Storage

<p>Due to the intermittent and fluctuating nature of wind and other renewable energy sources, their integration into electricity systems requires large-scale and flexible storage systems to ensure uninterrupted power supply and to reduce the percentage of produced energy that is discarded or curtailed. Storage of large quantities of electricity in the form of dynamic energy of water masses by means of coupled reservoirs has been globally recognized as a mature, competitive and reliable technology; it is particularly useful in countries with mountainous terrain, such as Greece. Its application may increase the total energy output (and profit) of coupled wind-hydroelectric systems, without affecting the availability of water resources. Optimization of such renewable energy systems is a very complex, multi-dimensional, non-linear, multi modal, nonconvex and dynamic problem, as the reservoirs, besides hydroelectric power generation, serve many other objectives such as water supply, irrigation and flood mitigation. Moreover, their function should observe constraints such as environmental flow. In this paper we developed a combined simulation and optimization model to maximize the total benefits by integrating wind energy production into a pumped-storage multi-reservoir system, operating either in closed-loop or in open-loop mode. In this process, we have used genetic algorithms as the optimization tool. Our results show that when the operation of the reservoir system is coordinated with the wind farm, the hydroelectricity generation decreases drastically, but the total economical revenue of the system increases by 7.02% when operating in closed-loop and by 7.16% when operating in open-loop mode. We conclude that the hydro-wind coordination can achieve high wind energy penetration to the electricity grid, resulting in increase of the total benefits of the system. Moreover, the open-loop pumped-storage multi-reservoir system seems to have better performance, ability and flexibility to absorb the wind energy decreasing to a lesser extent the hydroelectricity generation, than the closed-loop.</p>

scholarly journals Dimensioning Studies for Reversible Hydro Power Plants in Portuguese Islands

2018 ◽  
Vol 4 (1) ◽  
pp. 77-86
Author(s):  
Nuno Fonseca ◽  
André Madureira ◽  
João Peças Lopes ◽  
Manuel Matos
Keyword(s):  
Power Plant ◽  
Power Systems ◽  
Power Plants ◽  
Hydro Power ◽  
Power Resources ◽  
Hydro Power Plants ◽  
Pumped Storage ◽  
Energetic Level ◽  
Energy Surplus ◽  
The Ideal

This work is within the scope of set of consultancy studies made for Portuguese islands. It focuses on the integration of Pumped Storage Power in isolated islands. The paper starts to address several power systems circumstances about two Portuguese islands on the energetic level. For each of these islands, an independent examination of the conditions to install a reversible hydro power plant is accomplished. Therefore, the energy volume to be stored due to excess of renewable generation and the ideal power and number of the pumps and turbines to be installed were identified and evaluated for the sake of using the produced energy surplus as to be pumped and later generated. The paper enhances the importance of storing energy in the operation of isolated and small systems with considerable amount of intermittent power resources as well as the conditions for the viability of installing new exploitations of this kind.

scholarly journals Using Deep Learning to Predict Complex Systems: A Case Study in Wind Farm Generation

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
J. M. Torres ◽  
R. M. Aguilar
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Electricity Market ◽  
Power Plants ◽  
Wind Farm ◽  
Polynomial Regression ◽  
Supply And Demand ◽  
Feedforward Neural Networks ◽  
Activation Function ◽  
Renewable Energies

Making every component of an electrical system work in unison is being made more challenging by the increasing number of renewable energies used, the electrical output of which is difficult to determine beforehand. In Spain, the daily electricity market opens with a 12-hour lead time, where the supply and demand expected for the following 24 hours are presented. When estimating the generation, energy sources like nuclear are highly stable, while peaking power plants can be run as necessary. Renewable energies, however, which should eventually replace peakers insofar as possible, are reliant on meteorological conditions. In this paper we propose using different deep-learning techniques and architectures to solve the problem of predicting wind generation in order to participate in the daily market, by making predictions 12 and 36 hours in advance. We develop and compare various estimators based on feedforward, convolutional, and recurrent neural networks. These estimators were trained and validated with data from a wind farm located on the island of Tenerife. We show that the best candidates for each type are more precise than the reference estimator and the polynomial regression currently used at the wind farm. We also conduct a sensitivity analysis to determine which estimator type is most robust to perturbations. An analysis of our findings shows that the most accurate and robust estimators are those based on feedforward neural networks with a SELU activation function and convolutional neural networks.

Hybrid power plants as an alternative to fit pumped-storage hydro in Brazilian electricity sector regulatory framework

2018 ◽  
Vol 42 (15) ◽  
pp. 4898-4908 ◽  
Author(s):  
Gustavo Henrique Duzzi Libanori ◽  
Vinícius de Carvalho Neiva Pinheiro ◽  
Alberto Luiz Francato
Keyword(s):  
Power Plants ◽  
Regulatory Framework ◽  
Electricity Sector ◽  
Hybrid Power ◽  
Pumped Storage

scholarly journals Dynamic security of islanded power systems with pumped storage power plants for high renewable integration – A study case

2019 ◽  
Vol 2019 (18) ◽  
pp. 4955-4960
Author(s):  
Maria Helena Vasconcelos ◽  
Pedro Beires ◽  
Carlos Leal Moreira ◽  
João Abel Peças Lopes
Keyword(s):  
Power Systems ◽  
Power Plants ◽  
Renewable Integration ◽  
Dynamic Security ◽  
Study Case ◽  
Pumped Storage
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