A combined model for PV system lifetime energy prediction and annual energy assessment

Georgitsioti, Tatiani; Pearsall, Nicola; Forbes, Ian; Pillai, G. N.

doi:10.1016/j.solener.2019.03.055

Cited by 23 publications

(4 citation statements)

References 30 publications

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“…However, in the weight result calculated by the least square method, the weight of the binary logit model is negative, which does not conform to the actual situation. Therefore, the weighting method under the condition that the constraint weight is positive should be considered to weight the model to find the local optimal model [27].…”

Section: The Prediction Results Of the Least Squares Optimal Weight M...mentioning

confidence: 99%

Financial customer classification by combined model

Liu

Zheng

2022

Applied Mathematics and Nonlinear Sciences

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This paper explores the pros and cons of different algorithm models on the same selection problem, and then uses the combined prediction theory to obtain a new combined prediction model to explore its prediction accuracy. The actual problem to be solved is to help financial institutions to scientifically classify customers who choose financial products. We select the bank data set in the UCI database, which is derived from the survey data of a customer conducted by a financial institution in Portugal for a wealth management product. Decision tree C5.0 algorithm, naive Bayes classification algorithm and binary logit model are individually used to carry out a single model of empirical research on financial product customer classification. Through the empirical analysis of the five combination models, it is concluded that in the model that uses the least squares weighting method to determine the weight, the weight appears negative, which does not conform to the actual situation. The model that is based on the least squares weighting method and the model that is based on the simple weighting method are excluded. In contrast, the arithmetic mean weighted model is better than the reciprocal variance weighted model and the reciprocal mean square model. The accuracy reaches 89.91%, which is 0.43% higher than the accuracy of a single model. It can be concluded that the model that is based on the arithmetic average weighting is a better combination forecasting model.

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Section: The Prediction Results Of the Least Squares Optimal Weight M...mentioning

confidence: 99%

Financial customer classification by combined model

Liu

Zheng

2022

Applied Mathematics and Nonlinear Sciences

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“…Therefore, the decoupling component commonly used is an electrolytic capacitor, which reduces the lifetime of the system but is necessary to conserve energy. This point is critical because the application is generally used for power decoupling, a bulky and low reliable electrolytic capacitor, which considerably reduces the lifetime of the application [17].…”

Section: Dc-dc Power Converters 21 Non-resonant Dc-dc Power Convertersmentioning

confidence: 99%

Current Source Topologies for Photovoltaic Applications: An Overview

et al. 2022

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Current source topologies have several advantages compared to conventional voltage systems. Their inherent voltage-boosting function, intrinsic short-circuit protection, no electrolytic capacitor, direct-current control, continuous input current, and high reliability make them exceptional candidates for power generation systems, particularly for photovoltaic applications. This study provides an overview of the current source topologies for multi-stage photovoltaic grid-connected systems by comparing the number of components, performance, power-decoupling techniques, efficiency, and frequency operation. The overview reveals gain, performance, energy quality and lifetime improvements, thereby providing current source systems as an attractive alternative for renewable applications.

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“…Among these resources, the capital invested in the acquisition of photovoltaic modules, the disparity in the value of the kilowatt-hour (kWh) paid to electrical energy concessionaires, and the characteristics of photovoltaic solar energy production stand out. These combined uncertainties limit the accuracy of economic analysis results by traditional methods [24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Photovoltaic Solar Energy in Forest Nurseries: A Strategic Decision Based on Real Options Analysis

et al. 2023

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With the growing demand for investment projects in renewable energy, it is essential for the economic feasibility analysis to consider the inherent uncertainties of these projects and enable more accurate investment decisions. In this way, we analyze whether investment projects in photovoltaic panels to produce electrical energy in a forest nursery are economically viable through the analysis of real options. We consider the energy demand of a forest nursery with an initial investment of USD 90,417 in photovoltaic panels. The managerial flexibilities of deferral, expansion of 30.0% of the energy production capacity, and the project’s abandonment were inserted into the binomial model of the decision tree, built in discrete time. The project’s expanded net present value was 79.2% higher than the traditional net present value, capturing the value of flexibilities for managers. The deferral option was the one that most impacted the expanded net present value. Investment projects in photovoltaic panels to produce electricity in a forest nursery are economically viable when analyzed through real options.

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A combined model for PV system lifetime energy prediction and annual energy assessment

Cited by 23 publications

References 30 publications

Financial customer classification by combined model

Financial customer classification by combined model

Current Source Topologies for Photovoltaic Applications: An Overview

Photovoltaic Solar Energy in Forest Nurseries: A Strategic Decision Based on Real Options Analysis

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