Solar energy adoption: A case study of South Carolina

Burnett, J. Wesley; Hefner, Frank

doi:10.1016/j.tej.2021.106958

Cited by 12 publications

(10 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…On the other hand, some data show that the trend may not be like this. It is reported that electricity produced from solar energy will be cheaper than all other technologies for new generation resources entering service in 2025 [34]. One reason for this is that the fall in oil prices did not affect natural gas and coal prices much during the Covid-19 outbreak.…”

Section: Findings Confirming That the Solar Sector Is In A Positive Trendmentioning

confidence: 99%

Solar energy sector under the influence of Covid-19 pandemic: A critical review

Eroğlu

Cüce

2021

Journal of Energy Systems

View full text Add to dashboard Cite

Different controversies arise when the world is dealing with the Covid-19 outbreak and fast solutions are produced in the field of health. However, the impact of Covid-19 on some critical sectors is perspicuous. One of the most important of those is the status of the solar industry, which is a favorite renewable and sustainable energy sector and the most sensitive part of global energy transformation. In this study, the solar energy sector has been examined in detail under the lens of Covid-19. The effect of the covid-19 outbreak on the sector has been tried to be measured and the steps that could be taken for a quick recovery have been proposed. In addition, the possible positive effects of the pandemic on the sector have been discussed within the perspective of the research.

show abstract

Section: Findings Confirming That the Solar Sector Is In A Positive Trendmentioning

confidence: 99%

Solar energy sector under the influence of Covid-19 pandemic: A critical review

Eroğlu

Cüce

2021

Journal of Energy Systems

View full text Add to dashboard Cite

show abstract

“…However, it is intermittent and significantly dependent on ambient weather conditions, set aside such challenges as large space requirements and the necessity of energy storage systems. Nevertheless, solar energy technologies are generously subsidized in many parts of the world, which, together with technological advancements, help lower their capital costs and foster their widespread installation [23]. For instance, in the United States, prices of solar panels have dropped by half since 2008, while the capacity of installed panels increased by 35 times [24].…”

Section: Introductionmentioning

confidence: 99%

Design and Energy Performance Analysis of a Hotel Building in a Hot and Dry Climate: A Case Study

2021

View full text Add to dashboard Cite

In times of unprecedented climate change and energy scarcity, the design and delivery of energy-efficient and sustainable buildings are of utmost importance. This study aimed to design a hotel building for hot and dry climate conditions and perform its energy performance analysis using energy simulation tools. The model of the hotel building was constructed by a graphical tool OpenStudio and EnergyPlus following the ASHRAE Standard 90.1. To reduce the energy demand of the hotel, parametric analysis was conducted and building envelope parameters such as the thickness of insulation layer in the exterior wall and the roof, thermal conductivity of insulation layer, rate of infiltration, U-factor of windows, and thermal resistance of air gap in the interior walls (R-value), window-to-wall ratio, and orientation of the building were tested and the impact on the energy use of the building was analyzed. It was found that most of the design assumptions based on the ASHRAE standard were already optimal for the considered locality, however, were still optimized further to reach the highest efficiency level. Apart from this, three sustainable technologies—thermochromic windows, phase change materials, and solar panels—were incorporated into the building and their energy consumption reduction potential was estimated by energy simulations. Cumulatively, these sustainable technologies were able to reduce the total energy use from 2417 GJ to 1593 GJ (i.e., by 824 GJ or 34%). Calculation of payback period and return on investments showed that thermochromic windows and solar panels have relatively short payback periods and high return on investments, whereas PCM was found to be economically nonviable. The findings of this study are deemed to be useful for designing a sustainable and energy-efficient hotel building in a sub-tropical climate. However, the overall design and energy performance analysis algorithm could be used for various buildings with varying climate conditions.

show abstract

“…where 𝑓(•)is an activation function; 𝑊 (1) and 𝑏 (1) are two matrices containing the weight and bias values between the input and hidden layers, respectively. During the decoding process, the feature vector of the hidden layer is transformed into an output vector of 𝑥 ̂𝑑 = [𝑥 ̂1 𝑑 , 𝑥 ̂2 𝑑 ,• • •, 𝑥 ̂𝑀 𝑑 ] 𝑀 ∈ 𝑅 𝑀 , i.e., 𝑥 ̂𝑑 = 𝑓(W (2) ℎ 𝑑 + 𝑏 (2) )…”

Section: B Fault Feature Extractionmentioning

confidence: 99%

“…The importance of renewable energy sources has gained more attention in recent years due to rapidly growing concerns on environmental pollution issues [1,2]. Despite the economic slowdown brought by the COVID-19 pandemic, the additional global renewable energy capacity generated in the year 2020 has exceeded the earlier estimation and all historical records.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Deep Learning Model for Fault Detection and Classification of Grid-Connected Photovoltaic System

et al. 2022

View full text Add to dashboard Cite

Effective fault detection and classification play essential roles in reducing the hazards such as electric shocks and fire in photovoltaic (PV) systems. However, the issues of interest in fault detection and classification for PV systems remain an open-ended challenge due to manual and time-consuming processes that require the relevant domain knowledge and experience of fault diagnoses. This paper proposes a hybrid deep-learning (DL) model-based combined architectures as the novel DL approaches to achieve the real-time automatic fault detection and classification of a PV system. This research employed the wavelet packet transform (WPT) as a data preprocessing technique to handle the PV voltage signal collected and feeding them as the inputs for combined DL architectures that consist of the equilibrium optimizer algorithm (EOA) and long short-term memory (LSTM-SAE) approaches. The combined DL architectures are able to extract the fault features automatically from the preprocessed data without requiring any previous knowledge, therefore can override the traditional shortages of manual feature extraction and manual selection of optimal features from the extracted fault features. These desirable features are anticipated to speed up the fault detection and classification capability of the proposed DL model with higher accuracy. In order to determine the performance of the proposed fault model, we carried out a comprehensive evaluation study on a 250-kW grid-connected PV system. In this paper, symmetrical and asymmetrical faults have been studied involving all the phases and ground faults such as single phase to ground, phases to phase, phase to phase to ground, and three-phase to ground. The simulation results validate the efficacy of the proposed model in terms of computation time, accuracy of fault detection, and noise robustness. Comprehensive comparisons between the simulation results and previous studies demonstrate the multidisciplinary applications of the present study.INDEX TERMS Deep distributed energy, equilibrium optimizer algorithm (EOA), fault detection and classification, grid-connected photovoltaic systems, optimal feature selection, wavelet packet transform (WPT).

show abstract

Solar energy adoption: A case study of South Carolina

Cited by 12 publications

References 4 publications

Solar energy sector under the influence of Covid-19 pandemic: A critical review

Solar energy sector under the influence of Covid-19 pandemic: A critical review

Design and Energy Performance Analysis of a Hotel Building in a Hot and Dry Climate: A Case Study

Hybrid Deep Learning Model for Fault Detection and Classification of Grid-Connected Photovoltaic System

Contact Info

Product

Resources

About