Multipoint Layout Planning Method for Multienergy Sources Based on Complex Adaptive System Theory

This study attempts to study the impact of social and economic constraints, identification of new diseases, wind and solar energy consumption during the 2019 crisis on daily electricity demand by constructing multivariate correlation regression. The aim of the study is to determine the impact of the COVID-19 pandemic on the structure of electricity consumption by building regression models to analyse how various variables (detection of new diseases, wind and solar energy consumption) and social behaviour affect electricity demand. Tasks: to identify the main dates from the chronologies of COVID-19 in Russia, compare the electricity indicators by years, compare the data with the pre-pandemic period, study the share of generated electricity in the balance, conduct a correlation-regression analysis in order to identify the relationship between the detection of new cases of COVID-19 disease in the period from 03/30/2020 to 10/27/2021 and energy consumption, to study the impact of social activity on the level of consumption of renewable energy sources. This study identified links between new cases of coronavirus disease and energy consumption; wind energy consumption and general indicator; consumption of wind energy and solar with an indicator of morbidity.KeywordsEnergy consumptionLocation historyClean fuelsFuel efficiency

Renewable and non-renewable energy consumption-growth nexus: Evidence from a panel error correction model

Economic and social progress is directly and closely related to energy consumption. In the latest decades, there is a higher need to reduce energy consumption from conventional sources, replacing it with energy obtained from unconventional sources. The environmental concern is one of the objectives of the European economic policy, with a particular focus on renewable energy consumption and energy efficiency in order to lower the environmental impact. In this context, we analyzed energy consumption per capita and renewable energy consumption per capita in the EU with the help of parametric methods, using the β-convergence model, and semiparametric methods, using the σ-convergence model. In this research we proposed to study six analysis models of the period 1960–2015, based on the availability of data. We concluded that the EU states went through a convergence process in a slow pace of energy consumption per capita and renewable energy per capita, showing a convergence pattern. The results of the study show that there is a relationship between the convergence of conventional energy consumption and the convergence of renewable (unconventional) energy consumption. The study covers a long period of time in which EU member states had different economic and social systems, implicitly different degrees and rates of development. In addition, the interest in renewable energy is relatively recent in the whole world. There is a possibility that future research will provide more optimistic results, in terms of accelerating the convergence rate, as appropriate measures and technologies are applied to renewable energy production in all EU member states.

The study delves into the intricate question of whether China’s vast renewable resources, specifically wind, geothermal, and solar energy (WGS), can adequately meet the nation’s electricity demands and potentially fulfill its entire energy needs. This study explores China’s transition to renewable energy sources, with the main objective being assess the feasibility of meeting China’s total energy demand through renewables. Based on the historical data from 2010 to 2020, we forecast the development trend of China’s renewable energy and fossil energy demand using gray prediction models. The modeling results indicate that China’s entire electricity demand could be met solely by wind, geothermal, and solar energy (WGS) by approximately 2045. Moreover, if the current development trajectory of WGS is upheld, China’s total energy demand could be satisfied by WGS as early as 2082. Wind and solar power have significantly driven the expansion of WGS, collectively contributing to nearly three-quarters of its growth. However, the development of geothermal energy has progressed more slowly in comparison. Looking ahead, it is projected that China’s total energy demand could potentially be met by a combination of all renewable energy sources – including hydropower, solar, wind, geothermal, and nuclear energy – around 2064. This paper predicts that China’s renewable energy consumption will reach 56% by 2050 and 98% by 2060 respectively. These findings provide valuable insights into the feasibility of achieving “zero-carbon” China and the contribution of renewable energy in this process. The forecast results of this paper are helpful in guiding the development of WGS in China, and are of great significance in promoting sustainable development.

This study employed the novel Dynamic Autoregressive Distributed Lag (DYARDL) model to analyze the impact of renewable energy consumption, green technological innovation and financial development on CO2 emissions in Nigeria. Furthermore, Fully Modified Ordinary Least Square (FMOLS) and Canonical Cointegrating Regression (CCR) approaches are employed for robustness checks. The DYARDL results indicate that green technological innovation, renewable energy consumption and financial development respectively, promote environmental sustainability in the longrun, whereas, in the shortrun, green technological innovation is negatively related to the environmental quality in Nigeria. However, trade openness contributes towards environmental degradation both in the shortrun and the long run. The result of the Dynamic ARDL in this study is in conformity with the findings from both the FMOLS and CCR models. The study therefore, recommends that in order to achieve the target set by Nigeria Renewable Energy Master Plan (REMP) of generating 36% of its electricity from renewable energy sources by 2030, with a primary focus on hydro, Biomass-based, wind and solar energy sources, government should provide fiscal incentives to private investors in form of tax holidays, capital incentives, moratorium on import duties and loan opportunities for renewable energy projects in the country. Also, policymakers should strengthen policies that encourage green technological investments, in order to promote economic growth while also further reducing environmental emissions.

China has witnessed significant growth in trade through vide range trade liberalization strategies and urbanization has also been entered in advanced stage. Based on these dynamics, how much energy consumption of both renewable and none renewable account for energy consumption in whole system is a point of higher attention for the researchers. To understand this salient emerging debatable concern, we investigate the impact of trade openness and urbanization effect on renewable and non-renewable energy consumption in China for the period 1990-2018. We apply the quantile regression technique for the analysis; our results show that trade significantly increases the non-renewable energy consumption in all quintiles while partially increasing renewable energy consumption. This shows that trade activities in production and export commodities heavily rely on non-renewable energy inputs instead of renewable energy inputs. Urbanization affects non-renewable energy consumption only in three quintiles, while its effect is insignificant in most of the quintiles. Similarly, urbanization does not affect renewable energy consumption as in almost all quantiles the coefficients are statistically insignificant. This implies that urbanization is one of the determinants of energy consumption in China. The empirical findings of this study suggest some policy recommendations; first, the government needs to implement certain regulations while expanding trade to minimize the negative effect of non-renewable energy consumption; besides government should provide incentives to industrial units and traders for using renewable energy which may help to attain long term sustainable development goals. The government should also put certain limitations on population moving from rural to urban destinations.

In view of the problems of abandoning wind and solar energy, and carbon emissions, inevitable reduce of thermal power generation caused by the consumption of wind and solar energy, and the changes in the proportion of wind and solar energy consumption to thermal power at different times under the influence of time-of-use price, a time-of-use ladder carbon emission rights exchange mechanism is proposed, and on this basis, a low-carbon virtual power plant optimal dispatching model with ‘wind-solar-gas-storage’ is built. The maximum daily operating income of the virtual power plant is taken as the objective function in the model. The IBM commercial solver CPLEX is employed to optimize the solution, so as to obtain the optimal economic dispatching strategy of the virtual power plant, and compares it with the set scenarios. The simulation results reveal that the proposed mechanism can effectively enhance the enthusiasm and operating benefits of virtual power plants for renewable energy consumption, and reduce carbon emissions, providing new methods for low-carbon dispatching, and wind and solar energy consumption of virtual power plants.

It is known that many countries have made intensive researches and made important technological developments in order to benefit from the wind energy potential, and even in today's conditions, they use some of this potential economically. In the light of these developments, it is important to investigate the relationship between wind energy, especially in the financial markets, and therefore with the economies of the countries. This study aimed to the relationship among wind energy consumption (WIND), economic growth (GDP) and financial development (FIN) for 26 selected OECD countries in period of January-2016 and November-2020. The long-term nexus between the panels has been investigated with fourier panel cointegration and fourier panel causality tests, which detect smooth transition multiple structural breaks using trigonometric functions. According to the panel cointegration test results, the panels move together in the long run, positively for WIND-FIN and negatively for WIND-GDP. Moreover, there is causality relations from both FIN and GDP to WIND. This is a support indicate that wind energy use is costly. Therefore, it would be beneficial to achieve both FIN and GDP to increase the use of renewable energy. When the country-based results are examined, it is understood that there is no causality relationship for 16 countries and that there is unidirectional (neutrality hypothesis) or bidirectional causality for the remaining 6 countries (growth or conservation hypothesis). The findings provide valuable information for policymakers about wind energy investment. In addition, bureaucratic difficulties and deficiencies related to wind energy should be reduced, the private sector should contribute more to renewable energy investments, and individuals should be made aware that renewable energy sources can replace non-renewable energy sources.

The relationship between economic growth (in terms of GDP) and renewable energy (RE) and nonrenewable energy (NRE) consumption was investigated in 20 countries featured on the Renewable Energy Country Attractiveness Index list, also known as the Paris Club. The effect of both RE and NRE consumption on economic growth is discussed in the growth model based on the neoclassical production function. Labor and capital, which are important dynamics of growth, are also considered in the model. Granger causality and panel vector autoregression analysis are performed for the period 1991–2016. The results show that neither RE nor NRE consumption has a positive effect on economic growth. In reality, a 1% increase in RE consumption will reduce the GDP growth by 0.14%. For the effect of GDP growth on energy types, if growth increases by 1%, NRE consumption increases by 5.54%. If economic growth increases by 1%, a reduction of 1.73% occurs in RE consumption. In contrast, a causal link between both types of energy to growth has not been determined. There is no statistically significant coefficient of NRE and capital factors on GDP. A mutually positive and statistically significant relationship was determined between labor and growth. According to the results of variance decomposition, the basic dynamic of growth is itself: over a ten-year period, growth was affected by itself by 98%.

Background/Objectives: This article explores the theoretical and practical implications of the meaning of thinking, living, and acting within the framework of nursing in Complex Adaptive Systems. The Nursing Theory of Complex Adaptive Systems is grounded in the principles of Complex Adaptive Systems (CASs). It seeks to offer a new paradigm for nursing practice that addresses healthcare’s dynamic and evolving nature. Methods: The Nursing Theory of Complex Adaptive Systems represents a new nursing paradigm capable of addressing the challenges of a constantly evolving healthcare environment. This theory promotes personalized care plans adaptable to patients’ changing needs by emphasizing a holistic and interactive approach to care. Results: It also underscores the importance of interprofessional collaboration and effective communication in improving the quality of care. The Nursing Theory of Complex Adaptive Systems has significant implications for nursing practice, education, and research. Conclusions: It provides a robust framework for developing adaptive and resilient nursing practices that can respond to the complexities of modern healthcare. By integrating the principles of CASs into nursing, the Nursing Theory of Complex Adaptive Systems fosters a more flexible, interdependent, and holistic approach to patient care, ultimately enhancing patient outcomes and improving healthcare systems. This theory has practical applications in various healthcare settings, offering a framework for personalized and adaptable care plans that respond to the dynamic needs of patients while improving overall system efficiency. Future research should focus on the empirical validation of the Nursing Theory of Complex Adaptive Systems and its practical implementation in various healthcare settings.

ABSTRACTThis study examines the relationship between economic growth, renewable energy consumption, energy consumption, capital fixed formation, and trade openness for the period 1971–2015 for South Africa. In this regard, the study used auto-regressive distributed lag (ARDL) bound testing approach. The empirical findings show that the variables in the study are cointegrated indicating the existence of long-run relationship among them. Granger causality test shows that there exists bidirectional causality between renewable energy consumption and trade openness to economic growth. This result supports feedback hypothesis. The stability of model was also checked at the end. The empirical findings provide strong evidence that the interdependence between renewable energy consumption and economic growth indicates that renewable energy is important for economic growth, and likewise economic growth encourages the use of more renewable energy source.

This study extends recent work on the relationship between renewable and non-renewable energy consumption and economic growth to the case of developed and developing countries over the period 1990–2007. Heterogeneous panel cointegration procedures show a long-run equilibrium relationship between real GDP, renewable energy consumption, non-renewable energy consumption, real gross fixed capital formation, and the labor force with the respective coefficient estimates positive and statistically significant for developed and developing country panels. The results from the panel error correction models reveal bidirectional causality between renewable and non-renewable energy consumption and economic growth in the short- and long-run for each country panel.

What is better for mitigating carbon emissions – Renewable energy or nuclear energy? A panel data analysis

ABSTRACTThis paper uses the vector error correction model (VECM) and Granger causality tests to investigate short and long-run relationships between per capita carbon dioxide (CO2) emissions, real gross domestic product (GDP), renewable and non-renewable energy consumption, trade openness ratio and agricultural value added (AVA) in Tunisia spanning the period 1980–2011. The Johansen-Juselius test shows that all our considered variables are cointegrated. Short-run Granger causality tests reveal the existence of bidirectional causalities between AVA and CO2 emissions, and between AVA and trade. There are short-run unidirectional causalities running from non-renewable energy and GDP to AVA and to renewable energy, and running from CO2 emissions to renewable energy. Interestingly, there are long-run bidirectional causalities between all considered variables. Our long-run parameters estimates show that non-renewable energy, trade and AVA increase CO2 emissions, whereas renewable energy reduces CO2 emissions. In addition, the inverted U-shaped environmental Kuznets curve (EKC) hypothesis is not supported. Our policy recommendations are to increase international economic exchanges because this gives new opportunities to the agricultural sector to develop and to benefit from renewable energy technology transfer. Subsidizing renewable energy use in the agricultural sector enables it to become more competitive on the international markets while polluting less and contributing to combat global warming.

This paper examines the long-term and short-term relationships between renewable energy consumption, output and export, and CO2 emissions in China over the period 1990–2020 from the perspective of industry and agriculture using econometric methods. The results of the study found that there is a long-run relationship and there is a causality between these variables, indicating that renewable energy consumption, output, and export are related to CO2 emissions. Specifically, from a long-term perspective, the results of co-integration and causality reveal that there is a two-way causal relationship between renewable energy consumption, output, export, and CO2 emissions, supporting the feedback hypothesis; that is, output and export have an adverse impact on the environment, while renewable energy consumption has a favorable impact on the environment. In the short term, there is a direct or indirect one-way causal relationship between export, CO2 emissions, and renewable energy consumption, which supports the growth hypothesis. The impulse response analysis has further verified the causality test results and supported this hypothesis. However, there is a strong negative correlation between industrial and agricultural export and renewable energy consumption, which will cause the use of renewable energy to fail to meet the peak demand for industrial and agricultural export in the short term. Conversely, large amounts of fossil fuels will be consumed to meet output and export demand. Therefore, on the road to social, economic, and environmental sustainability, it is necessary to consider the impact of economic growth and energy consumption (renewable and non-renewable energy) of related industries on CO2 emissions, which also provides a strong basis for the development and reduction of China’s renewable energy and the long-term implementation of the emission control policy.