A Small Beautiful Example of Sustainability in the Heart of Zimbabwe

Zimbabwe has diligently started pursuing the Sustainable Development Goals (SDGs) defined by the United Nations in 2015. While making progress and being aware of it, will be a shot in the arm, with success breeding more success, the journey may seem daunting at times. However, the journey – sustainable development towards the targets set – is what matters more than the final destination, as philosophers and savants often remind us. This article, while dwelling on sustainable development in this southern-African landlocked country in general, presents a beautiful example of a collaborative venture, undertaken by dedicated and determined international partners, and predicated on SDG#4 (Quality Education) and SDG#5 (Gender Equality), and harnessing the complementarities and synergies with the other SDGs, which set root during the COVID-pandemic, in Mwenezi in southern Zimbabwe. The pandemic while being a scourge, tended to have some silver linings to it, as it gave birth to many collaborations and made human beings realise that one's own happiness is dependent to a very great extent on that of others. This venture emphasizes girls' education and skills-development, which open the doors, synergistically, to sustained growth, development and progress. Education, indisputably, is a key component of the freedom necessary to live a life of value. To quote Nelson Mandela, "It is the most powerful weapon which you can use to change the world.”. © 2023, Scientific Publishing House of the Cardinal Stefan Wyszynski University. All rights reserved.

Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review

The use of machine learning and data-driven methods for predictive analysis of power systems offers the potential to accurately predict and manage the behavior of these systems by utilizing large volumes of data generated from various sources. These methods have gained significant attention in recent years due to their ability to handle large amounts of data and to make accurate predictions. The importance of these methods gained particular momentum with the recent transformation that the traditional power system underwent as they are morphing into the smart power grids of the future. The transition towards the smart grids that embed the high-renewables electricity systems is challenging, as the generation of electricity from renewable sources is intermittent and fluctuates with weather conditions. This transition is facilitated by the Internet of Energy (IoE) that refers to the integration of advanced digital technologies such as the Internet of Things (IoT), blockchain, and artificial intelligence (AI) into the electricity systems. It has been further enhanced by the digitalization caused by the COVID-19 pandemic that also affected the energy and power sector. Our review paper explores the prospects and challenges of using machine learning and data-driven methods in power systems and provides an overview of the ways in which the predictive analysis for constructing these systems can be applied in order to make them more efficient. The paper begins with the description of the power system and the role of the predictive analysis in power system operations. Next, the paper discusses the use of machine learning and data-driven methods for predictive analysis in power systems, including their benefits and limitations. In addition, the paper reviews the existing literature on this topic and highlights the various methods that have been used for predictive analysis of power systems. Furthermore, it identifies the challenges and opportunities associated with using these methods in power systems. The challenges of using these methods, such as data quality and availability, are also discussed. Finally, the review concludes with a discussion of recommendations for further research on the application of machine learning and data-driven methods for the predictive analysis in the future smart grid-driven power systems powered by the IoE.

Going Green Post COVID-19: Employer Perspectives on Skills Needs

Achieving a just transition to a low carbon economy and society, in the wake of the COVID-19 pandemic, is arguably one of the greatest policy challenges facing governments. It is also of deep concern to businesses, employees and the organisations that represent them. Much of the focus, particularly at policy level, has been on the potential of this transition to create new jobs especially through the growth of renewable energy and clean technology. In this paper, we argue that this focus on ‘green jobs', and in particular new green jobs, grossly underestimates the skills needs of a future workforce able to deliver a transition to a more sustainable low-carbon economy. The focus of this study is to gain an understanding of what skills are required to support the transition beyond these sectors. It critically reports on the results of a series of in-depth interviews with senior managers in key organisations within Cambridgeshire and Peterborough, UK. It sheds a light on the significant employment transitions taking place in organisations who are not specifically focused on delivering ‘green' products or services. It finds widespread acknowledgement of the importance of a green recovery, albeit predicated by economic growth. The key skills needs reported, at all levels were likely to be ‘soft' transferrable skills rather than ‘hard' technical skills. COVID-19 was recognised as both a disrupter and as a catalyst for a green transition.

Challenges and Opportunities for the Energy Sector in the Face of Threats Such as Climate Change and the COVID-19 Pandemic—An International Perspective

New threats such as the COVID-19 pandemic have brought forth not only threats to human health but also changes to many other sectors of the global economy. Despite strict lockdowns, the highest annual number of global renewable energy installations were completed in 2020, including onshore wind power stations and PV power stations. The development of these two types of renewables is increasing rapidly. Transformations in terms of renewable energy require both governmental and public support;thus, it is important to note that the pandemic did not weaken the public commitment to fight climate change. This article aims to evaluate the actual level of support for renewable energy sources in different countries of the world and how the pandemic has affected public opinion regarding this issue. Our analysis suggests that, regardless of the pandemic, public support for renewable energy remains strong in different regions of the world. [ FROM AUTHOR] Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Post-COVID-19 energy transition strategies: even reaching 100% renewable in Ecuador by 2055 is not enough to face climate change issue

The pandemic scenario caused by Covid-19 generated negative impacts. Covid-19 has made it clear that our daily lives depend to a high degree on access to energy. Therefore, now more than ever, it is necessary to promote new activities such as local food production, but also local energy capture. This article is an attempt to expose and quantify the benefits of a renewable energy transition in Ecuador post Covid-19 and post-oil. The generation, consumption, and reserves of oil in Ecuador were characterized, and the concept of energy transition was applied to evaluate the possibilities of integration of renewables, the progressive exit of thermal power plants, and future energy strategies. The year 2015 was taken as a basis and it was determined that energy use was 154.0 TWh / year, which corresponds to an end-user of approximately 147 TWh / year. The objective was to reduce this end-use demand to 80.0 TWh/year by 2055 through the integration of renewables and energy efficiency, for which 5 transition phases were planned until a 100% renewable system was obtained. It is concluded that the energy transition in Ecuador is technically possible and economically viable, without giving up the energy well-being that we currently enjoy. However, results show that even 100% renewable is not enough to face climate change.

Harvesting Renewable Energy from Foot Pedal Using Rotational Electromagnetic Induction Flywheel

Philippines is one of the highest electricity prices in the ASEAN where harnessing renewable energy using wasted human effort is necessary. The global pandemic COVID-19 is spreading and because of this, establishments have required sanitation. The study's main objective is to Develop a Rotational Electromagnetic Induction Flywheel using Foot Pedal as Actuation to Harvest Renewable Energy. T-test was used to validate the results using the battery percentage of a power bank as the parameter, where there is a significant difference between single and multiple actuations with an attached mechanical dispenser and without. The system was able to harness an average of 0.30992 Watt-hour and 6.11476 Watt-hour in 5 daily trials for single and multiple controlled set-ups without mechanical dispenser respectively. An average of 0.2441 Watt-hour and 5.0027 Watt-hour for single and multiple controlled set-ups with mechanical dispenser correspondingly. Lastly, an average of 3.2924 Watt-hour in 5 daily trials for uncontrolled set-up. © 2023 IEEE.

A Review on Solar Energy Policy and Current Status: Top 5 Countries and Kazakhstan

The article describes the world's experience in developing the solar industry. It discusses the mechanisms of state support for developing renewable energy sources in the cases of five countries that are the most successful in this area—China, the United States, Japan, India, and Germany. Furthermore, it contains a brief review of state policy in producing electricity by renewable energy facilities in Kazakhstan. This paper uses statistical information from the International Renewable Energy Agency (IRENA), the International Energy Agency (IEA), British Petroleum (BP), and the Renewable Energy Network (REN21), and peer-reviewed sources. The research methodology includes analytical research and evaluation methods to examine the current state of solar energy policy, its motivators and incentives, as well as the prospects for its development in Kazakhstan and in the world. Research shows that solar energy has a huge development potential worldwide and is sure to take its place in gross electricity production. This paper focuses on the selected economic policies of the top five countries and Kazakhstan, in what may be considered a specific research limitation. Future research suggestions for the expansion of Renewable Energy (RE) in Kazakhstan could include analysing the impact of introducing dedicated policies and incentives for solar systems and exploring the benefits and challenges of implementing large RE zones with government–business collaboration.

Alternative Energy Investments as a Part of Global Smart Green Innovations

Concerns about the global environmental situation are leading to a search for new climate solutions, one of which is to stimulate an energy transition at the global level by expanding the use of alternative energy sources and introducing smart energy-saving technologies. Significant financial resources are needed for this purpose. Therefore, it is vital to assess the prospects for alternative energy in the post-COVID economy by analyzing the current state of this segment of the global energy market and the impact of the COVID-19 pandemic on it. The research uses statistical data from the World Bank, the International Energy Agency, and Bloomberg Information and Analysis Agency. The authors apply the methods of retrospective and comparative analysis and the least squares method. The analysis showed the growing importance of alternative energy, especially in developed countries, the serious impact of global energy inflation, and the favorable prospects for renewable energy sources in general. The study has drawn conclusions about the possibility of increasing investment in alternative energy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Ensuring Economic Security by Modifying Renewable Energy Systems

The paper presents the possibility of ensuring economic security by modifying the energy system of renewable energy sources, including solar, wind, hydropower, biofuels, etc. This process is related to the transition of economies to a less carbon-intensive and more sustainable energy system. Recovery in fuel demand and stability in international markets are driving a recovery in production in 2021 and sustained growth through 2025. The paper explores economic and policy incentives focused on clean energy that can directly or indirectly support renewable energy. Experts predict that renewable energy sources should take the leading place in the world's electricity sector. The authors propose using a dynamic information model to refine the forecasts. This research tool will provide data and forecasts in all sectors employing renewable energy technologies. The authors provide up-to-date indicators, analysis, and information on energy security and sustainability on a global scale. Moreover, they quantify the effects of the widespread global recession caused by COVID-19 and consider measures in the clean energy sector to address them. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Impact of Renewable Energy on the Economy of Saudi Arabia

The objective of the study was to identify the impact of renewable energy on Saudi economy during 2000-2021. Analytical techniques were used to conduct this study. An analysis of the study used a set of variables, in which Renewable energy perceives as independent variable and the dependent variables are GDP per capita, net foreign direct investment, unemployment, fixed capital formation, and net foreign trade. The data of the study were analyzed using the E-views program. According to the study, renewable energy has an impact on certain economic variables and does not have an impact on others. A partial validity is found for the study's central hypothesis. According to our findings, renewable energy contributes significantly to net foreign direct investment, unemployment, and fixed capital formation, but not to GDP per capita, net foreign trade, or fixed capital formation.

Lessons Learnt and Policy Implications from Implementing the POWERPOOR Approach to Alleviate Energy Poverty

Energy poverty is a multifaceted phenomenon that affects many Europeans. Alleviating energy poverty is high in the EU, national, and local policy agendas. Despite the attention the phenomenon has been gaining from a policy perspective, especially after the current energy crisis, there are still some gaps due to the complexity of the issue and its vastly different manifestations across Europe. This manuscript presents the policy implications stemming from the implementation of the POWEPROOR approach in alleviating energy poverty in eight European countries, as co-created with relevant stakeholders in each country. The knowledge gained from empowering energy-poor citizens by promoting behavioural changes and small-scale energy efficiency interventions, as well as by encouraging the uptake of renewable energy sources in the form of collective energy initiatives while leveraging innovative financing schemes, resulted in policy recommendations for national and sub-national governments and lessons for civil society and the private sector.

Meeting the Hospital Oxygen Demand with a Decentralized Autonomous PV System: Effect of PV Tracking Systems

When it comes to supplying oxygen, current standard hospitals in Iran have proven inadequate in the face of the COVID-19 pandemic, particularly during infection peaks. Power disruptions drastically reduce the oxygen pressure in hospitals, putting patients' health at risk. The present study is the first to attempt to power an oxygen concentrator with a solar-energy-based system. The HOMER 2.81 package was used for technical–economic–environmental–energy analysis. The most notable aspects of this work include evaluating different available solar trackers, using up-to-date equipment price data and up-to-date inflation rate, considering the temperature effects on solar cell performance, sensitivity analysis for the best scenario, considering pollution penalties, and using a three-time tariff system with price incentives for renewable power. The study has been carried out at Hajar Hospital, Shahrekord, Chaharmahal and Bakhtiari Province, Iran. The study showed that, by supplying 60% of the power demand, the dual-axis solar tracking system offered the highest annual power output (47,478 kWh). Furthermore, generating power at—$0.008/kWh due to selling power to the grid, the vertical-axis tracker was found to be the most economical design. Comparing the configuration with a vertical-axis tracker with the conventional scenario (relying on the power distribution grid), the investment is estimated to be recovered in three years with $234,300 in savings by the end of the 25th year. In the best economic scenario, 6137 kg CO2 is produced, and the analysis revealed the negative impact of a temperature rise on the performance and solar power output.

Probabilistic Forecasting of Electricity Demand Incorporating Mobility Data

Due to extreme weather conditions and anomalous events such as the COVID-19 pandemic, utilities and grid operators worldwide face unprecedented challenges. These unanticipated changes in trends introduce new uncertainties in conventional short-term electricity demand forecasting (EDF) since its result depends on recent usage as an input variable. In order to quantify the uncertainty of EDF effectively, this paper proposes a comprehensive probabilistic EFD method based on Gaussian process regression (GPR) and kernel density estimation (KDE). GPR is a non-parametric method based on Bayesian theory, which can handle the uncertainties in EDF using limited data. Mobility data is incorporated to manage uncertainty and pattern changes and increase forecasting model scalability. This study first performs a correlation study for feature selection that comprises weather, renewable and non-renewable energy, and mobility data. Then, different kernel functions of GPR are compared, and the optimal function is recommended for real applications. Finally, real data are used to validate the effectiveness of the proposed model and are elaborated with three scenarios. Comparison results with other conventional adopted methods show that the proposed method can achieve high forecasting accuracy with a minimum quantity of data while addressing forecasting uncertainty, thus improving decision-making.

Do cryptocurrencies integrate with the indices of equity, sustainability, clean energy, and crude oil? A wavelet coherency approach

The paper examines market co-movement between pairs of financial assets in the time-frequency domain. Recent finance literature confirms the integration of cryptocurrencies and financial assets, which may bring more investments with the possibility of surplus liquidity in the cryptocurrency segment, leading to financial instability. The novelty of this paper is examining the integration of cryptocurrencies and the indices of equity, sustainability, renewable energy, and crude oil for the daily observations from 2015 to 2021 by using the wavelet coherency method. The empirical results signify no integration in the short-term scales and grow stronger in the medium-term scales, especially during the COVID-19 period, and further exhibit weaker heterogeneous associations in the long-term scales. However, the sustainability, clean energy indices follow similar dynamics of the equity market and crypto pairs. In contrast, the global crude oil index showcases the minor integration with cryptocurrencies compared with other traditional asset classes. Hence, the cryptocurrency market fails to confirm the safe haven features, especially during the COVID-19 periods (Medium-term), which facilitate the domestic and international investors expecting to hedge their price risk in equity markets using cryptocurrencies may have to look for short-term. The lead-lag heterogeneous effects of the asset-pairs may pave arbitrage opportunities for investors.

A risk-sharing-based resilient renewable energy supply network model under the COVID-19 pandemic.

Over the past few months, the COVID-19 pandemic has postponed many renewable energy projects because of disruptions in the technology and finance supply. Additionally, the existing power plants are inefficient because of a record drop in demand for goods and services caused by lockdowns in cities. This situation poses huge challenges to the resilience of renewable energy supply networks in the face of deeply hazardous events, such as the COVID-19 pandemic. Therefore, the purpose of this study was to design a resilient renewable energy supply network considering supply, demand, and payment risks caused by COVID-19. The objective of the proposed model was to determine the optimal amount of electric power generated and stored to meet the demands and the risk-sharing effort index to maximize the total resilient profit of the power plant and determine the optimal price adjustment index to minimize the cost to consumers. A government subsidy-based risk-sharing model was developed to enhance the resilience of the concerned renewable energy supply network under the pandemic. To overcome uncertainties in both random and risk events, a robust fuzzy-stochastic programming model was proposed to solve these research problems. Computational experiments were conducted on the test supply network in Vietnam. The results showed that the resilient energy supply network with the risk-sharing model tended to stabilize the total profit with the different impact levels of COVID-19 compared to the network without risk-sharing. The proposed model efficiently tackled both uncertainties in random and hazardous events and had a higher profit and shorter CPU time compared to the robust optimization mode.

Economic development, social media awareness, and technological innovation in biogas sector under climate change in the post-COVID-19 pandemic conditions.

After COVID-19, financing for emerging nation reserves in renewable energy bases was deemed a crucial aspect of sustainable development. Investing in biogas energy plants can be highly beneficial for lowering the use of fossil fuels. Using a survey of shareholders, investors, biogas energy professionals, and active social media participants in Pakistan, this study evaluates the intentions of individual investors to invest in biogas energy plants. The primary purpose of this study is to increase investment intent for biogas energy projects following COVID-19. This study focuses on financing biogas energy plants in the post-COVID-19 era and evaluates the research's assumptions using partial least squares structural equation modeling (PLS-SEM). The study employed the technique of purposive sampling to acquire data for this investigation. The results indicate that attitudes, perceived biogas energy benefits, perceived investment attitudes, and supervisory structure evaluations inspire one's propensity to finance biogas vitality plant efforts. The study found a link between eco-friendly responsiveness, monetary benefits, and investors' actions. The aspiration of investors to mark such reserves was set up to be unpretentious by their risk aversion. Conferring to the facts, evaluating the monitoring structure is the critical factor. The previous studies on investment behavior and other forms of pro-environmental intent and action yielded contradictory results. In addition, the regulatory environment was evaluated to see how the theory of planned behavior (TPB) affects financiers' objectives to participate in biogas power plants. The consequences of the study indicate that feelings of pride and discernment of energy expansively affect people's desire to invest in biogas plants. Biogas energy efficacy has little effect on investors' decisions to invest in biogas energy plants. This study offers policymakers practical ideas on enhancing investments in biogas energy plants.

Scheduling Model for a Trigeneration System With Energy Storage Unit: A Hospital Application

Over the last three COVID-19 effective years, it was evident that healthcare has been the most sensitive sector to electricity failures. Therefore, if well developed and implemented, a microgrid system with an integrated energy storage system (ESS) installed in hospitals has great potential to provide an uninterrupted and low-energy cost solution. In this article, we target to show the importance of the installed ESS against the problems that will arise from power outages and energy quality problems in hospitals. Besides, it aims to construct an energy management system (EMS) based on the scheduling model to meet the lowest cost of a system containing solar panels, microturbine, gas boiler, and energy storage units that are repurposed lithium-ion batteries from electric vehicles and thermal storage tank. EMS is a mixed-integer linear program to meet the hospital's electricity, heating, and cooling demands with the lowest cost for every hour. The established scheduling model is run for a hospital in Antioch, Turkiye, with 197 beds, 4 operating rooms, 2 resuscitation units, and 9 intensive care units for every hour based on the data in 2019. With the EMS, approximately 25% savings were achieved compared to the previous energy cost. Furthermore, as the result of the net present value calculation, the payback period of the proposed system is estimated to be approximately seven years.

Portfolio performance implications of investment in renewable energy equities: Green versus gray

The Sustainable Development Goals of the United Nation and interest by investors in Environmental, Social and Governance (ESG) investment strategies have caused a rapid shift to the green or renewable energy sector, from traditional or gray (oil, gas, and coal) energy companies. In this study, we examine whether and to what extent, financially speaking, there is a price to pay for investing in renewable energy sector equity. Moreover, we seek to determine whether green investments can be considered a hedge during times of financial stress. We find that alphas from investments in a portfolio of gray (overall energy sector) stocks and versus a portfolio of renewable energy equities during an exogenous, non-financial shock-the COVID-19 pandemic-and during non-crisis periods did not differ statistically. However, the renewable energy index showed higher idiosyncratic volatility than the energy index, as expected. The results are robust to alternative model specifications. From a practical perspective, our results are informative in that they provide insights into the tradeoffs associated with renewable energy investments. In particular, risk-adjusted returns to a renewable energy portfolio may be affected by greater idiosyncratic risk.

An application of QVAR dynamic connectedness between geopolitical risk and renewable energy volatility during the COVID-19 pandemic and Russia-Ukraine conflicts.

The article is the first to employ a quantile vector autoregression (QVAR) to identify the connectedness between geopolitical risks and energy volatility from January 1, 2015, to April 03, 2023. This paper is also the first to examine the mediating roles of uncertain events like the COVID-19 pandemic and the Russia-Ukraine conflict on this interlinkage. Dynamic connectedness is 29% in the short term and approximately 6% in the long term. Dynamic net total directional connectedness over a quantile also indicates that connectedness is very intense for both highly positive changes (above the 80% quantile) and negative changes (below the 20% quantile). In the short term, the geopolitical risks remained net receivers of shock, but they turned into net shock transmitters during 2020 in the long term. Clean energy, in the short term, transmits shocks to other markets, and it plays the same role in the long term. Crude oil was a net receiver of shocks during COVID-19 and turned into a net transmitter of shocks in early 2022. Dynamic net pairwise directional connectedness over a quantile suggests that uncertain events like the COVID-19 epidemic or the Russia-Ukraine conflict influence the dynamic interlinkages between geopolitical risks and renewable energy volatility and change their roles in the designed system. These findings are critical since they help authorities develop effective policies to lessen the vulnerabilities of these indicators and minimize how widely the renewable and non-renewable energy market is exposed to risk or uncertainty.

Analysis of COVID-19 recovery and resilience policy in Finland: a transformative policy mix approach

Transformative innovation policy (TIP) implies not only new directionality for innovation policy but also rethinking its means and scope. This requires further investigation into the role of horizontal and cross-sectoral policy programmes that may be relevant for upscaling innovation and destabilising regimes. This paper studies the national implementation, in Finland, of the European Union (EU) programme for COVID-19 recovery, the Recovery and Resilience Facility (RRF), as an example of a cross-sectoral policy programme. It is of interest, because the EU has set certain conditions related to sustainability transitions for the RRF. Using a transformative policy mix approach, the paper finds that the Finnish RRF Programme lists many policy measures that can be regarded as having a transformative intent. These include upscaling innovative sustainability niches and destabilising existing practices. Yet, we also found that there is a risk that cross-sectoral programmes fail to find overall transformative visions and fund multiple potentially competing technological pathways instead.