Diffusion of Electricity Consumption Practices in Mexico

Castillo, A.; Peña, Landy Sánchez

doi:10.3390/socsci6040144

Cited by 6 publications

(4 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The first regards strategies that engage all political parties, the second aims to educate individuals on climate change (Dadural and Reznikov 2018). At the same time, residential energy consumption can be improved not only through adequate technological solutions but also with a behavior more eco-friendly to citizens (Escoto Castillo and Peña 2017).…”

Section: Introductionmentioning

confidence: 99%

The Profitability of Residential Photovoltaic Systems. A New Scheme of Subsidies Based on the Price of CO2 in a Developed PV Market

D’Adamo

2018

Social Sciences

View full text Add to dashboard Cite

Photovoltaic (PV) resource drives the clean global economy of the future. Its sustainability is widely confirmed in literature, however some countries present a growth very low in the last years. A new policy proposal is examined in this work. It aims to stimulate a new diffusion of PV plants in mature markets (e.g., Italy) regarding residential consumers. The subsidy is given to the amount of energy produced by PV plant for a period of 20 years (equal to its lifetime) and its value is calculated according to the scheme of European Emissions Trading System (EU ETS). Discounted Cash Flow (DCF) is used as economic method and two indexes are proposed: Net Present Value (NPV) and Discounted Payback Time (DPBT). The baseline case studies vary in function of two variables; (i) the share of self-consumption (30%, 40% and 50%) and (ii) the price of emissions avoided (10, 35 and 70 € per ton of CO2eq). Results confirms the environmental advantages of PV sources as alternative to the use of fossil fuels (685 gCO2eq/kWh) and economic opportunities are verified in several scenarios (from 48 €/kW to 1357 €/kW). In particular, the profitability of PV systems is greater with a subsidized rate of fiscal deduction of 50% in comparison to subsidies with a value of carbon dioxide lower than 18.50 €/tCO2eq.

show abstract

Section: Introductionmentioning

confidence: 99%

The Profitability of Residential Photovoltaic Systems. A New Scheme of Subsidies Based on the Price of CO2 in a Developed PV Market

D’Adamo

2018

Social Sciences

View full text Add to dashboard Cite

show abstract

“…As an example, in Qatar, the lack of a penalty for excessive energy use and the free nature of household electricity results in excessive energy use at the household level [39]. Likewise, the increase in household energy use for appliances has been observed to result in an increase in the intensity of household energy consumption which introduces the aspect of a positive feedback loop in terms of overconsuming, which is a result of the lack of governance or policy on the consumption level [39,56]. Energy-saving policies would serve to reduce household energy consumption and draw a path towards sustainable consumption behavior.…”

Section: Contextual Consumptionmentioning

confidence: 99%

Sustainable Consumption and Education for Sustainability in Higher Education

Al-Nuaimi

Al-Ghamdi

2022

Sustainability

View full text Add to dashboard Cite

Sustainable consumption (SC) is the concept surrounding the use of products and services with minimal impact on environmental safeguarding resources for current and future generations. Since its implementation in 2015, SC is an expanding area of research as the increased occurrence of environmental impacts is observed globally. In this article, a literature review of sustainable consumption and education is presented as an in-depth review of relevant literature over the last 25 years. The review provides an understanding of the relationship, effect, and current concepts of sustainability education and consumption behavior. An analysis of the historical, geographical, and thematic characteristics of the relevant literature provided the scholarly context of the literature. An exploration into consumer behaviors on an individual and contextual level is presented, highlighting key factors for achieving sustainable consumption on the consumer level. A further review on the effect of education in general, and higher education on consumer behavior, is provided, noting the key findings for the support of sustainable education, as well as the anticipated barriers. In the conclusion, the effect of education on consumption is found to be positive and significant for pro-environmental consumption behaviors, and it is the main approach for implementing the ideals of sustainable consumption in the future.

show abstract

“…The energy consumption of the whole society is directly or indirectly affected by many factors. Up to now, many scholars have studied the factors affecting the energy consumption [3][4][5][6]. The problem of electricity consumption is a complex non-linear problem, for which so far scholars have proposed various prediction models, such as grey theory [7][8][9], multiple regression [10][11][12], and time series models [13][14][15]; In recent years, various intelligent algorithms have also been applied to power consumption prediction [16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

“…Meng et al [3] proposed a three-dimensional decomposition model and a mixed trend extrapolation model to explore the factors driving the growth of household electricity consumption in China, predicting the future development trend before 2030, and summarizing some of the main influencing factors; Akay et al [4] used the Grey Prediction and Rolling Mechanism (GPRM) method to predict Turkey's overall and industrial electricity consumption, and both social and economic factors were adopted to forecast power consumption. Castillo et al [5] used a unified data set of 13 income and expenditure household surveys to assess changes in electrical and electricity consumption, taking into account income distribution, GDP, population, etc. as indicators of impact assessment; Pablo-Romero [6] analyzed the relationship between electricity consumption and tourism growth in hotels and restaurants in 11 EU countries between 2005 and 2012, and modelled energy use based on three variables: energy price, income and climate.…”

Section: Introductionmentioning

confidence: 99%

Forecasting China’s Renewable Energy Terminal Power Consumption Based on Empirical Mode Decomposition and an Improved Extreme Learning Machine Optimized by a Bacterial Foraging Algorithm

2019

View full text Add to dashboard Cite

The energy consumption pattern dominated by traditional fossil energy has led to global energy resource constraints and the deterioration of the ecological environment. These challenges have become a major issue all over the world. At present, the Chinese government aims to significantly reduce the fossil energy consumption contribution in the terminal energy consumption. The development of renewable energy in the terminal energy and energy conversion links has significantly increased the proportion of clean low-carbon energy. In order to accurately get the proportion of renewable energy terminal power consumption, firstly, this paper selects a primary influencing-factors set including the gross GDP, fixed investment in renewable energy industry, total length of cross-provincial and cross-regional high-voltage transmission lines, etc. as influencing factors of China’s electricity consumption fraction produced by renewable energy based on a multitude of papers. Secondly, from the perspective of signal decomposition, the data inevitably has a lot of interference and noise. This paper uses the empirical mode decomposition (EMD) algorithm to reduce the degree of signal distortion and decomposes the signal into natural modes including several intrinsic mode functions (IMFs) and a residual term (Res); afterwards, a new extreme learning machine (ELM) forecasting model optimized by an Inverse Square Root Linear Units (ISRLU) activation function is proposed, and the ISRLU function is used to replace the implicit layer activation function in the original ELM algorithm. Then, a new bacterial foraging algorithm (BFOA) is applied to optimize the parameters of the optimized ELM forecasting model. After multiple learning and training operations, the optimal parameters are obtained. Finally, we superimpose the output of each IMF and Res training task to get the amount of China’s power consumption produced by renewable energy. Some statistical indicators including root mean squard error (RMSE) are applied to compare the accuracy of several intelligent machine forecasting algorithms. We prove that the proposed forecasting model has higher prediction accuracy and achieves faster training speed by an empirical analysis. Finally, the proposed combined forecasting algorithm is applied to predict China’s renewable energy terminal power consumption from 2018 to 2030. According to the forecasting results, it is found that China’s renewable energy terminal power consumption shows a gradual growth trend, and will exceeded 3300 billion kWh in 2030, which will represent a renewable energy terminal power ratio of about 38% in 2030.

show abstract

Diffusion of Electricity Consumption Practices in Mexico

Cited by 6 publications

References 35 publications

The Profitability of Residential Photovoltaic Systems. A New Scheme of Subsidies Based on the Price of CO2 in a Developed PV Market

The Profitability of Residential Photovoltaic Systems. A New Scheme of Subsidies Based on the Price of CO2 in a Developed PV Market

Sustainable Consumption and Education for Sustainability in Higher Education

Forecasting China’s Renewable Energy Terminal Power Consumption Based on Empirical Mode Decomposition and an Improved Extreme Learning Machine Optimized by a Bacterial Foraging Algorithm

Contact Info

Product

Resources

About