Intelligent Predictive Analytics for Sustainable Business Investment in Renewable Energy Sources

Anagnostopoulos, Theodoros; Kyriakopoulos, Grigorios L.; Ntanos, Stamatiοs; Gkika, Eleni; Asonitou, Sofia

doi:10.3390/su12072817

Cited by 20 publications

(12 citation statements)

References 45 publications

(55 reference statements)

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“…The authors of (Vahedipour et al 2020) have proposed an optimal bidding mechanism for a VPP that competes in the day-ahead energy markets to lower end-user costs. The Bayesian Network Classifier was found to be the most effective method for predicting willingness to invest in renewable energy by Anagnostopoulos et al (2020), with a classification accuracy of 0.7942. have assessed a VPP energy trading model, made up of conventional and non-conventional sources of energy, energy storage systems, and electrical loads with the aim of maximizing SW while disregarding the uncertainties associated with renewable energy sources. The authors of have analyzed VPP interactive characteristics in the distribution systems providing energy flexibility support services in the distribution system without considering the uncertainty of photovoltaics.…”

Section: Literature Reviewmentioning

confidence: 99%

Operational Planning and Design of Market-Based Virtual Power Plant with High Penetration of Renewable Energy Sources

Ullah

Baseer

2022

Int. J. Renew. Energy Dev.

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Renewable energy sources are becoming more prevalent as a source of clean energy, and their integration into the power industry is speeding up. The fundamental reason for this is the growing global concern about climate change. However, the weather-dependent and uncertain nature of renewable generation raise questions about grid security particularly, when photovoltaics (PVs) and wind turbines (WTs) technologies are used. The incorporation of energy storage systems (ESS) in a virtual power plant (VPP) environment could compensate for the renewable generation's uncertainty. Where a VPP is a new concept that combines dispatchable and non-dispatchable energy sources, electrical loads, and energy storage units, enabling individual energy producers to participate in the electricity market. In this study, a market-based-VPP’s operational planning and design model is presented to assess the optimal active power dispatch of (WT, PV, and ESS) operating in the day-ahead electricity market to maximize social welfare (SW) considering the uncertainties associated with wind speed, solar irritation, and load demand. The Scenario-tree technique is applied to model the uncertainties of renewable energy sources and load demand. The proposed model performance is validated by simulation studies on a 16-bus UK generic distribution system (UKGDS). According to the simulation results, renewable energy sources and energy storage systems dispatched optimally active power to satisfy the load demand in the most efficient way possible.

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Section: Literature Reviewmentioning

confidence: 99%

Operational Planning and Design of Market-Based Virtual Power Plant with High Penetration of Renewable Energy Sources

Ullah

Baseer

2022

Int. J. Renew. Energy Dev.

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“…Much debate surrounds the outcomes of developing and implementing environmental policies to encourage renewable energy consumption and impede wasteful nonrenewable energy sources use. Cross‐national evidence shows that sustainable energy policy, among other things establishing emission limits for the industrial sector, results in the consumption of renewable energy resources in economic development that allegedly leads to environmental improvement in terms of reduction in emissions of atmospheric pollutants and waste products recycling (Adebayo et al, 2021; Anagnostopoulos et al, 2020; Liu et al, 2021; Mahmood et al, 2021; Oh et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Do changes in the business environment and sustainable development really matter for enhancing enterprise development?

Brychko

Bilan

Lyeonov

et al. 2022

Sustainable Development

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The accomplishment of sustainable development goals has become a global initiative to encourage renewable energy, reduce wasteful energy consumption and increase investment in energy efficiency projects. The number of publications devoted to sustainable development, environmental protection and green investments is growing exponentially. Firstly, this study is committed to provide a comprehensive overview of research literature on enterprise development in decades-long, focusing on the sustainable development and business environment field. Secondly, it seeks to elaborate the most comprehensive structural model examining the multilateral and facilitative role of internal and external business environment changes in the relationship between sustainable development and enterprise development. A bibliometric analysis via VOSviewer was applied to detect and visualize the research trends and display the research status of enterprise development under the changes in the business environment and sustainable development. A confirmatory factor analysis and structural equation modeling were performed to develop, implement and verify a conceptual structural model examining the multilateral and facilitative role of internal and external business environment changes in the relationship between sustainable development and enterprise development. Mapping bibliographic data based on cocitation, co-occurrence, bibliographic coupling, and network and content analysis showed that generally, researchers had made significant efforts to investigate different links that arise between enterprises development, sustainable development, and business environment separately in different combinations. Structural equation modeling showed that the argument that sustainable development directly causes enterprise development is disputable since sustainable development focuses on changes in the

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“…. The energy efficiency of demand side infrastructure is used for calculating the energy demand in energy management system [18]. The study describes about the energy consumption of demand data for calculating the data driven for decision making for power transmission analysis [19].…”

Section: Introductionmentioning

confidence: 99%

Performance analysis of demand forecasting in energy consumption based on ensemble model

Dhanalakshmi

Ayyanathan

2022

Bulletin EEI

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Over the previous decade, energy usage has increased exponentially all over the world. The machine learning algorithms are used to classify the demand and requirement of off and evening peak load of southern regional load dispatch centre (SRLDC) data. In this paper, data are classified based on demand and requirement of both evening and off peak of day wise southern regional grid of Andhra Pradesh, Karnataka, Kerala, Tamilnadu, and Pondicherry of different states are proposed. The machine learning algorithms like k-nearest neighbors (KNN), random forest, and logistic regression have been adopted to classify the model. To improve this model efficiency, an ensemble learning method is used to increase the accuracy. The performance measure of state-wise outcome is determined by classifying its demand and requirement needs over its state energy consumption and with different classification algorithms and it is improved by using a combined method of ensemble model with accuracy of 86%.

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Intelligent Predictive Analytics for Sustainable Business Investment in Renewable Energy Sources

Cited by 20 publications

References 45 publications

Operational Planning and Design of Market-Based Virtual Power Plant with High Penetration of Renewable Energy Sources

Operational Planning and Design of Market-Based Virtual Power Plant with High Penetration of Renewable Energy Sources

Do changes in the business environment and sustainable development really matter for enhancing enterprise development?

Performance analysis of demand forecasting in energy consumption based on ensemble model

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