Prediction Model for the Electrical Industry in Spain—The Trend Toward Renewable Energy

Verdejo, M.A.; Fernández, Juan Ignacio Pulido

doi:10.1080/10485236.2015.11665758

Cited by 5 publications

(4 citation statements)

References 14 publications

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“…For the first mock exam of single model, there are two kinds of parallel and serial type. The combination of grey system prediction and neural network prediction is shown in figure 2 and 3 [5,6]. The former adopts the combination method of linear weighting of each method, that is, each prediction method assigns a certain weight and finally calculates the total prediction value; The latter uses the combination method to further predict the results by using the existing prediction results.…”

Section: Limitation Analysis Of Single Prediction Algorithmmentioning

confidence: 99%

A Grey Forecasting Model for Energy Demand Based on Optimized BP Neural Networks

Cheng,

2024

Advances in Transdisciplinary Engineering

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In order to accurately evaluate regional energy consumption and demand, the prediction model based on optimized Grey Neural Network was discussed in this paper. Considering the advantages of grey prediction model and artificial neural network model, BP neural network model was introduced to analyze the model, and genetic algorithm was used to optimize the network weight design of series model. Based on the consumption data of urban residents in a province from 2009 to 2019, the case analysis adopted the improved prediction model to test the actual demand trend of energy in the future. The results showed that the combined prediction model can reflect the development trend of energy consumption and demand in a period of time, and it had better prediction accuracy than the single prediction model. Therefore, it was feasible to apply it to complex nonlinear systems.

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Section: Limitation Analysis Of Single Prediction Algorithmmentioning

confidence: 99%

A Grey Forecasting Model for Energy Demand Based on Optimized BP Neural Networks

Cheng,

2024

Advances in Transdisciplinary Engineering

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“…In the field of hydrogen energy, the special focus is on the production and storage of hydrogen fuel, and the industrialization of special fuel cells. In particular, solar photovoltaic, as one of the clean energy sources, has attracted wide attention from all countries [2,3]. But because the traditional solar photovoltaic power generation system using battery performance is poorer, and solar energy have certain volatility, make solar photovoltaic power generation system performance dropped substantially, therefore the promotion solar photovoltaic power generation system performance, research and development of the solar energy photovoltaic power generation system of fuel cell, in order to improve system comprehensive performance, promote the further development of photovoltaic power generation field.…”

Section: Introductionmentioning

confidence: 99%

Optimization Scheduling Method of Solar Photovoltaic and Fuel Cell Combined Power Generation System

Xue

Zheng

Duan³

2022

SPEE

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The performance of the battery used in the traditional solar photovoltaic power generation system is poor, and the solar energy has a certain volatility, which makes the performance of the solar photovoltaic power generation system decline significantly. In order to improve the performance of the solar photovoltaic power generation system, a solar photovoltaic fuel cell combined power generation system has been developed. However, there are some problems in the process of traditional combined generation system optimal scheduling, such as high investment cost and total cost, and short generation time of optimal scheduling scheme. This paper takes solving the problems of traditional system optimal scheduling as the research goal, a new optimization scheduling method of solar photovoltaic and fuel cell combined power generation system was designed. The composition and topological structure of the solar photovoltaic fuel cell combined power generation system are analyzed. The system is composed of photovoltaic array, fuel cell, electrolytic cell, short-term energy storage unit and energy control unit. It can mainly convert sunlight radiation into electric energy, and convert it into DC or AC used by people through multiple links, so as to ensure the stability and security of power supply in our country. A scheduling model is established according to the photovoltaic cell power generation model, the fuel cell power generation model, the electrolytic hydrogen production model, the battery model, the power conversion model and the combined power generation system model. And the multi-objective cuckoo algorithm is used to solve the model, the optimization scheduling results of solar photovoltaic fuel cell combined power generation system are obtained. The experimental results show that the total investment cost of this method is reduced by 123678.4 yuan and 175858.7 yuan compared with the experimental comparison method, and the total cost is reduced by 301195.5 yuan and 414991.8 yuan compared with the experimental comparison method. It shows that compared with the experimental comparison method, the total investment cost and total cost of this method are lower, and the generation time of the optimal scheduling scheme is between 0.19s and 0.25s, and the practical application effect is good. It fully solves the problems existing in the traditional methods and has certain application significance.

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“…Energy services are key to preventing disease and fighting pandemics-from powering healthcare facilities and supplying clean water for essential hygiene, to enabling communications and IT services that connect people while maintaining social distancing. IoT Application Solutions [159][160][161][162][163][164][165][166][167]:…”

mentioning

confidence: 99%

“…The current crisis is an opportunity for a profound, systemic shift to a more sustainable economy that works for both people and the planet. IoT Application Solutions [86,166,[204][205][206][207][208][209]:…”

mentioning

confidence: 99%

Application of IoT in Healthcare: Keys to Implementation of the Sustainable Development Goals

Verdejo-Espinosa

Ruiz

Mata

et al. 2021

Sensors

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We live in complex times in the health, social, political, and energy spheres, and we must be aware of and implement new trends in intelligent social health systems powered by the Internet of Things (IoT). Sustainable development, energy efficiency, and public health are interrelated parameters that can transform a system or an environment for the benefit of people and the planet. The integration of sensors and smart devices should promote energy efficiency and ensure that sustainable development goals are met. This work is carried out according to a mixed approach, with a literature review and an analysis of the impact of the Sustainable Development Goals on the applications of the Internet of Things and smart systems. In the analysis of results, the following questions are answered about these systems and applications: a) Are IoT applications key to the improvement of people’s health and the environment? b) Are there research and case studies implemented in cities or territories that demonstrate the effectiveness of IoT applications and their benefits to public health? c) What sustainable development indicators and objectives can be assessed in the applications and projects analyzed?

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Prediction Model for the Electrical Industry in Spain—The Trend Toward Renewable Energy

Cited by 5 publications

References 14 publications

A Grey Forecasting Model for Energy Demand Based on Optimized BP Neural Networks

A Grey Forecasting Model for Energy Demand Based on Optimized BP Neural Networks

Optimization Scheduling Method of Solar Photovoltaic and Fuel Cell Combined Power Generation System

Application of IoT in Healthcare: Keys to Implementation of the Sustainable Development Goals

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