Renewable Capacity Research Articles

Hybrid Renewable Energy Microgrids: A Genetic Algorithm Approach to System Design

The paper examines the use of genetic algorithm (GA) methods to optimize hybrid renewable energy microgrids by merging various renewable sources and energy storage technologies. An examination of meteorological data over many days reveals fluctuations in solar irradiance ranging from 4.8 kW/m² to 5.5 kW/m² and wind speed oscillating between 3.9 m/s and 4.5 m/s, indicating the presence of dynamic weather conditions. An analysis of energy generating capabilities reveals a wide range of potentials, with solar capacities varying from 80 kW to 150 kW and wind capacities ranging from 60 kW to 120 kW across different sources. An analysis of Energy Storage System (ESS) specifications shows a range of values for maximum capacities, charge/discharge efficiencies (ranging from 85% to 96%), and maximum charge/discharge rates (from 60 kW to 100 kW), highlighting the need for flexible energy storage systems. The examination of microgrid load profiles reveals the presence of diverse energy needs, with residential loads oscillating between 48 kW and 55 kW, commercial loads ranging from 40 kW to 47 kW, and industrial loads spanning from 30 kW to 36 kW. A percentage change study reveals the ability to adapt, with solar irradiance and wind speed showing mild fluctuations of roughly 14% and nearly 15% respectively. In contrast, renewable source capacity demonstrate significant percentage changes ranging from around 40% to 50%. These results highlight the ever-changing characteristics of renewable energy sources, underlining the need for strong optimization tactics in microgrid systems. The study emphasizes the potential of GA-based approaches in developing efficient microgrids, promoting sustainable and dependable energy solutions in the face of changing environmental circumstances and varied energy requirements.

Evaluation method of renewable energy absorptive capacity based on Monte Carlo

Evaluation method of renewable energy absorptive capacity based on Monte Carlo

Pathway to the Zero Emission Utopia: a review

Attaining zero emissions stands as a key aspect of sustainable development. The conventional pathway, known as the “Zero Emissions Society (ZES)”, involves the use of renewable energy generation as an alternative to traditional fossil fuels and promotes the total de-carbonisation of the grid, ultimately leading to net-zero emissions. This requires the establishment of large-scale renewable energy power stations, increased transmission efficiency and energy storage facilities. In addition to this conventional pathway, this review introduces an innovative concept, termed “Zero Emission Utopia (ZEU)”, which originates from an individual-centric perspective. This novel approach enables the achievement of zero carbon emissions in human daily life activities and subsequent propagation of this practice extensively, actualising a zero-emissions scenario. An analysis of the available utopian sources of energy and distributed energy storage methods for this proposed pathway is conducted and presented. In addition, an evaluation case study, quantifying the renewable energy production capacity available to an individual, shows with the help of distributed energy storage methods, the ZEU pathway is feasible for normal families. Moreover, the constructive collaboration between these two pathways is explored, highlighting their potential for mutual enrichment and complementary advantages.

Effect of Combining Carbon Policies and Price Controls in Cross-Border Trade of Energy on Renewable Generation Investments

In this paper, we investigate the combined effect of carbon policies and price controls in cross-border trade of electricity on power generation investments. It has been shown that price controls in cross-border trade of electricity may negatively affect renewable energy investments. However, the assessment of the impact of the simultaneous adoption of carbon policies and energy price controls has still not been addressed. Assessing this interaction is important to find out whether carbon policies can offset the negative impact of price controls on renewable energy investments or not. Results show that carbon policies can partially offset the negative impact of price controls, and that cap-and-trade programs are more effective to prevent this negative impact than carbon taxes. On the other hand, high levels of carbon taxes combined with price control regulation may increase renewable capacity investments, but without completely offsetting the negative effect of the price controls.

Periodontal ligament stem cell colony-forming units of fluorosed and nonfluorosed teeth: An in vitro study

Abstract Introduction: The continued quest for extracting possible differences in the colony forming units (CFUs) of periodontal ligament stem cells (PDLSCs) between fluorosed and nonfluorosed, led to the current original project to evaluate if any such difference exists. Materials and Methods: For this study, the soft tissues adhering to eight healthy fluorosed and seven nonfluorosed extracted teeth were scraped using a curette. Results: The results of this study demonstrate similar CFUs by both fluorosed and nonfluorosed PDLSCs (P = 0.97), but nonfluorosed PDLSCs showed higher CFUs. Moreover, this is the first study where CFUs on PDSLCs were compared between fluorosed and nonfluorosed groups. Conclusion: This would influence the regeneration or renewal capacity of PDLSCs following treatment or on the physiologic basis, respectively. This is the first study of its kind; therefore, further studies are in progress on age-related changes in PDLSCs to evaluate the potential markers and various tissue-forming abilities.

Do mineral imports increase in response to decarbonization indicators other than renewable energy?

While previous studies examine the impact of renewable energy generation capacity on mineral imports where minerals are broadly defined, this study examines the role of three decarbonization indicators (energy efficiency, energy's carbon footprint, and renewable generation) in driving import demand for four specific minerals used in multiple decarbonization technologies: copper, aluminum, nickel, and manganese. Our results, based on the cross-sectional autoregressive distributed lag modeling approach applied to panel data from 33 countries, suggest that imports for some minerals increase in response to (1) investments in energy efficiency (aluminum and manganese), (2) reducing energy's carbon footprint (copper), and (3) investments in renewable energy generation (copper and manganese). Nickel imports were found to increase with higher levels of energy use per GDP suggesting their role in cleaner vehicles, which heavily rely on electrification, higher electricity use, and urbanization. When imports are broadly defined to include all types of mineral groups, import values were found to be responsive to higher renewable generation but not the other decarbonization indicators. Our findings provide insights into developing mineral-specific strategies and policy frameworks to ensure supply chain resilience.

Optimal siting of shared energy storage projects from a sustainable development perspective: A two-stage framework

The rapidly increasing installed renewable energy capacity has drawn greater attention to energy storage technology in China. However, the commercial implementation of energy storage is constrained by several obstacles. One potential solution to overcome these constraints is the shared energy storage model. The optimal location layout plays a crucial role in addressing the strategic decision problem of sustainable development. Therefore, a two-stage multi-criteria decision-making model is proposed to identify the optimal locations of shared energy storage projects in this work. In the first stage, the power attraction model is established to determine the macroscopic layout of shared energy storage. In the second stage, a large-scale group decision making (LSGDM) framework is developed to select the optimal micro location. The empirical study conducted in China reveals that Shandong, Henan, and Hebei provinces exhibit greater power flow attraction, from which eight alternatives are selected as site preferences and evaluated by twenty experts. Based on the improved EDAS method, the evaluation score function values of the eight alternatives are 0.497, 0.5, 0.476, 0.499, 0.507, 0.477, 0.506, and 0.498, respectively. Specifically, A5 in Rao Yang County, Hengshui City and A7 in Qing Long Manchu Autonomous County, Qinhuangdao City are preferred locations. Furthermore, the dependability and stability of the model are illustrated through the sensitivity analysis and comparative analysis. This model not only assists in determining the layout of shared energy storage but also contributes to the theoretical study of geographic information system and LSGDM.

Optimal Operation of Hydrogen Energy Coupling Integrated Energy System considering Green Certificate, Ladder-Type Carbon Joint Trading, and Dual-Incentive Demand Response

Under the “carbon peak and carbon neutrality” goal, the construction of an efficient, low-carbon, and economical energy supply system is of great significance for advancing a dual carbon strategy. In allusion to the integrated energy systems (IES) with hydrogen energy coupling, a hydrogen energy coupling IES low-carbon optimization operation strategy that took account of green certificate and ladder-type carbon joint trading and dual-incentive demand response was proposed in this paper. First, a hydrogen energy multiuse system composed of an electrolyzer, a hydrogen fuel cell, a methane reactor, and hydrogen energy storage was constructed to make full use of the low-carbon cleaning characteristics of hydrogen energy. Besides, a combined model of hydrogen mixed with natural gas was established to improve the utilization efficiency of hydrogen energy. Second, a dual-incentive demand response model including price incentives and subsidy incentives was constructed to fully use the ability to adjust demand-side resources. Next, in view of the carbon emission reduction mechanism of the green certificate, a green certificate and ladder-type carbon joint trading mechanism was constructed. In addition, a green certificate trading mechanism and a reward and punishment tiered carbon trading mechanism had been introduced separately in the IES optimization operation model to reduce carbon emissions of the system. The calculation simulation sets up different scenarios for comparative analysis. As shown by the results, the proposed model could effectively improve renewable energy consumption capacity and energy utilization efficiency. The effectiveness of hydrogen energy utilization, demand respond, and green certification carbon trading mechanism in improving system economy and low-carbon efficiency is verified.

Bibliometric analysis of research progress in microwave-assisted pyrolysis of biomass during 1979–2023

Increasing the footprint of installed renewable energy capacity helps to mitigate CO2 emissions. Numerous countries have been devising strategies for harnessing various renewable sources to meet the rising demands. Solar, wind, hydro, geothermal, and biomass are a few of the renewable sources that are being used to generate electricity across the globe. Based on the nature of the source's availability, biomass is considered one of the plausible resources to generate electricity consistently. In light of this, extensive research works is being conducted to explore different approaches to convert biomass to energy. Microwave pyrolysis is one of the new approaches to convert biomass into energy. This study aims to understand the global trends in adopting micro-wave-assisted pyrolysis with the help of bibliometric analysis performed based on keyword occurrences. A total of 510 scientific contributions have been made between 1979 and 2023, addressing various aspects of microwave-assisted pyrolysis to convert biomass into energy. To gain insights into the adaptability of microwave-assisted pyrolysis, temporal growth in the total number of publications and citations has been studied. Prominent publications, top journal sources, highly contributing countries, and researchers are also identified to facilitate future research in this area. Findings suggest that attention to microwave pyrolysis is increasing by 7.59%, and China is designated as the top nation and the most frequent partner in microwave-assisted pyrolysis of biomass, followed by the United States and Malaysia. Bioresource Technology, Journal of Analytical and Applied Pyrolysis, Fuel, and Energy are popular journals focusing on microwave-assisted pyrolysis. Based on the bibliometric study of prior existing work, this study presents a road map for collaborations to conduct research on microwave-assisted pyrolysis of biomass to generate energy.

Party affiliation, economic interests and U.S. governors’ renewable energy policies

This paper explores the impact of U.S. state governors’ party affiliation and economic interests on renewable energy outcomes. Using data on installed renewable capacity, we find that, on average, Democratic governors had a positive impact on the state-level adoption of renewable energy. However, the effect is highly heterogeneous. There are no differences in renewable energy outcomes between Democratic and Republican governors in states where the energy-intensive manufacturing industries are economically important or in states where the natural renewable endowment is scarce. Consistent with a political economy approach, we argue that in the area of renewable and climate policy, governors’ policy preferences are overridden by holding office motivations and economic interests.

Day-Ahead PV Generation Scheduling in Incentive Program for Accurate Renewable Forecasting

Photovoltaic (PV) power can be a reasonable alternative as a carbon-free power source in a global warming environment. However, when many PV generators are interconnected in power systems, inaccurate forecasting of PV generation leads to unstable power system operation. In order to help system operators maintain a reliable power balance, even when renewable capacity increases excessively, an incentive program has been introduced in Korea. The program is expected to improve the self-forecasting accuracy of distributed generators and enhance the reliability of power system operation by using the predicted output for day-ahead power system planning. In order to maximize the economic benefit of the incentive program, the PV site should offer a strategic schedule. This paper proposes a PV generation scheduling method that considers incentives for accurate renewable energy forecasting. The proposed method adjusts the predicted PV generation to the optimal generation schedule by considering the characteristics of PV energy deviation, energy storage system (ESS) operation, and PV curtailment. It then maximizes incentives by mitigating energy deviations using ESS and PV curtailment in real-time conditions. The PV scheduling problem is formulated as a stochastic mixed-integer linear programming (MILP) problem, considering energy deviation and daily revenue under expected PV operation scenarios. The numerical simulation results are presented to demonstrate the economic impact of the proposed method. The proposed method contributes to mitigating daily energy deviations and enhancing daily revenue.

Comparative life cycle assessment of renewable energy storage systems for net-zero buildings with varying self-sufficient ratios

The transition towards zero and net-zero buildings necessitates identifying sustainable and effective renewable energy systems to reduce the impacts of operational energy. This study analyses the environmental impacts of multiple microgrids that consist of a photovoltaic plant and a hybrid hydrogen/battery energy storage system in a grid-connected building. To this end, a three-step simulation process was proposed. The first step involved modelling the energy consumption of the building during operation. Following that, the size of components was optimised. Lastly, a comparative life cycle assessment was conducted to evaluate different self-sufficient ratios (SSR). The results show that as SSR increase, the optimised capacities of all components generally increase, although this relationship is complex, particularly as the system approaches full renewable capacity. The climate change impact initially decreases to its lowest values but then increase again towards achieving full self-sufficiency. Furthermore, the results highlight the importance of considering multiple environmental impact categories when designing renewable energy systems. A sensitivity analysis reveals that countries with carbon-intensive electricity grids can reduce climate change impacts by increasing their renewable energy penetration. However, for countries with a high proportion of renewable energy, a higher SSR may not lead to a lower climate change impact but rather exacerbate it.

Reliance on fossil fuels increases during extreme temperature events in the continental United States

Increasing extreme climate events driven by climate change raise the question of their impacts on the power production system, and implications for renewable versus fossil power supply. Here, using climate reanalysis data and daily electricity generation (2018–2023), we systematically quantify the impact of extreme climate events, specifically extreme cold events and extreme hot events on United States state-level carbon emissions and on the carbon intensity of electricity. We find that extreme climate events increase the carbon intensity of the energy production, increasing the reliance on fossil-based sources of energy and reducing the capacity of renewables. The states with more renewable electricity generation were also more affected by extreme temperatures. Our results reveal the extent to which the reliability and resilience of the current United States electricity system depends on fossil energy during extreme climate events, and suggest a need for adaptation measures as the country will transition to higher shares of renewable energy while extreme events will become more frequent.

Abstract A013: Leukemic stem cell differentiation visible at single-cell resolution in AML patients treated with BRG1/BRM inhibitor FHD-286

Abstract BAF chromatin remodeling complexes are critical to the regulation of cellular differentiation and are implicated in cancer as well as other diseases. FHD-286 is a first-in-class dual inhibitor of the BAF catalytic subunits BRM and BRG1 (SMARCA2/4) that is being developed for the treatment of advanced hematologic malignancies. We previously reported that exposure of acute myeloid leukemia (AML) cells to pharmacologically relevant concentrations of FHD-286 led to downregulation of leukemic stem cell (LSC) marker CD34, and upregulation of the myeloid maturation marker CD11b. Morphologic features of differentiation were also observed, suggesting that BAF functions to maintain AML cells in an undifferentiated state, and that FHD-286 may inhibit AML cell growth by reducing their capacity for stem cell renewal. Using single-cell transcriptomic data, we further assessed the impact of FHD-286 on differentiation markers of tumor cells from clinical AML patients. scRNA-seq data was obtained for 26 bone marrow aspirate samples from 11 AML and 2 myelodysplastic syndrome (MDS) patients from the Phase 1 clinical study evaluating FHD-286. Non-tumor cell types (T-cells, erythroid, B cells, megakaryocytes) were identified using published gene markers and removed from the dataset, leaving only tumor cells enriched for either LSC markers (CD34, CD123) or CD11b. We next identified differentially expressed genes between patient LSCs and CD11b+ cells. The top 50 genes associated with each cell group were taken as signature markers of stemness or differentiation, and their mean expression used as phenotypic scores for all patient tumor cells. Clustering analysis of the patient single-cell data showed that cells grouped according to cell type, treatment timepoint, and patient identity. Tumor cells expressing LSC markers CD34 and CD123 clustered separately from those expressing differentiation marker CD11b, and the relative percentage of CD11b+ tumor cells increased on treatment for 8 out of 12 patients dosed at >=5mg, consistent with preclinical AML models. Differential expression analysis revealed additional genes upregulated in either LSCs or CD11b+ cells, which were identified in literature as markers of stemness or myeloid differentiation, respectively. Single-cell LSC and differentiation signature scores showed a strongly statistically significant shift away from LSC identity and toward differentiation for 10 out of 12 patients. Single-cell RNA data from AML patients validates the preclinical observation that FHD-286 treatment induces changes in LSCs resembling differentiation towards a terminal myeloid cell state. This dataset further indicates that nearly all patients undergo some degree of tumor cell differentiation after treatment, suggesting broad on-target activity of FHD-286. Citation Format: GiNell Elliott, Jessica Wan, Kim Horrigan, Mike Collins, Astrid Thomsen, Ashley K Gartin, Ammar Adam, David L Lahr, Gabriel Sandoval, Sameul Agresta, Jessica Piel, Martin Hentemann. Leukemic stem cell differentiation visible at single-cell resolution in AML patients treated with BRG1/BRM inhibitor FHD-286 [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A013.

Enhancing the Green Energy Revolution: Analyzing the Impact of Financial and Investment Processes on Renewable Energy Projects in Kazakhstan

Abstract As a fossil fuel-dependent nation, Kazakhstan is caught between issues and possibilities in its search for a sustainable energy transition. Despite its tremendous resources, Kazakhstan’s renewable energy capacity is 1%, much behind its non-renewable peers. According to this research, green fiscal policies in renewable energy firms are needed to reduce the country’s political and economic dependence on the global oil sector. This report emphasizes regional collaboration and Kazakh-stan’s potential leadership in Central Asian Green Economy projects. Kazakhstan can promote renewable energy adoption and economic sustainability by forming regional alliances. Challenges lie ahead on the green future path, so this paper addresses legislative, infrastructure, financial, and data barriers to green fiscal initiatives in Kazakhstan. It stresses the significance of holistically tackling these concerns, including banking and stock market reforms and sustainable planning. Policymakers and stakeholders in Kazakh-stan can use the research findings to boost the economy, fight corruption, and increase political engagement. Upskilling the workforce to support green technology and local renewable energy production is recommended. The report recommends proactive global crisis prediction and management to help Kazakhstan handle economic and environmental challenges. Hence, the above actions are crucial to Kazakhstan’s goal of industrialization by 2050. Kazakhstan can lead a world rapidly moving to green energy by committing to green fiscal methods, regional collaboration, and addressing the many obstacles to development. By doing so, it can safeguard its future and advance the global green energy revolution.

Unlocking inter-regional flexibility for the HVDC-connected two-area system with a multistage model

In recent years, the deployment of high-voltage direct current (HVDC) tie-lines in power grids has become a prevalent solution in some countries to transmit renewable energy from remote locations to load centers. However, the variability and uncertainty associated with renewable energy generation pose challenges to effectively utilizing this technology. This work proposes a novel multistage planning-operation model, aiming to unlock the potential flexibility in the HVDC transmission system and increase the renewable penetration. By incorporating flexibility, which is essential for accommodating the uncertainty in renewable generation, our model optimally shares the inter-regional flexibility between the sending- and receiving-end grids. One of the key features of our proposed model is its robustness and non-anticipativity, meaning it can account for different levels of uncertainty and make decisions that are suitable for multiple scenarios. This work develops two solution approaches to solve this challenging multistage model with variable uncertainty sets. We validate the proposed approach through a case study conducted on a real-world inter-regional grid. The numerical results demonstrate that our approach effectively unlocks more inter-regional flexibility and assists in increasing the renewable hosting capacity.

Implications of a smart grid-integrated renewable distributed generation capacity expansion strategy: The case of Iraq

The rapid growth of electricity demand in Iraq has consistently outstripped the country's electricity infrastructure, leading to frequent blackouts, especially during peak summer demand. With a heavy reliance on oil 93 % and gas 7 % for electricity generation, the nation is exposed to economic fluctuations associated with global oil prices and environmental impacts from burning fossil fuels. This study explores the implications of integrating smart grids and expanding renewable distributed generation capacity in the country's energy system. Drawing upon the projection of the energy demand by 2035 across four scenarios (Business as Usual, Sustainable Development, High Growth, and Low Carbon), the study underscores solar energy, backed by abundant solar and wind energy, as a key player in the country's renewable transition. However, challenges persist, including the need for technical expertise in renewable energy technologies, financing hurdles, and concerns about policy stability. With the country's policies targeting 25 % renewable electricity by 2030 and the establishment of significant renewable projects, there tangible momentum. The results have drawn out a roadmap for an estimated addition of up to 10 GW of renewable energy capacity by 2030 and 14 GW by 2035. In addition, strategies for distributed generation capacity expansion were highlighted, underscoring the crucial role of solar and wind energy and other renewables in the country's sustainable energy future.

HR’S ROLE IN ORGANIZATIONAL CHANGE WITHIN NIGERIA’S RENEWABLE ENERGY SECTOR: A REVIEW

In the rapidly evolving landscape of Nigeria's renewable energy sector, the role of Human Resources (HR) in driving and managing organizational change is paramount. This systematic review aims to elucidate the specific functions and strategies employed by HR professionals in facilitating such transitions within the sector. Drawing from a comprehensive analysis of empirical studies, industry reports, and case studies, several key insights emerge. Firstly, HR's proactive involvement in strategic planning and decision-making is crucial in anticipating and addressing potential challenges. Secondly, continuous training and development programs are instrumental in equipping employees with the necessary skills and knowledge to adapt to technological and regulatory shifts. Moreover, HR's role in fostering a culture of innovation and resilience cannot be understated, as it directly influences employee morale and retention during periods of change. In conclusion, HR plays a pivotal role in ensuring the seamless integration of change initiatives within Nigeria's renewable energy sector. Their strategic involvement, capacity-building efforts, and emphasis on organizational culture are vital components in navigating the complexities of the industry's transformation.
 Keywords: Human Resources (HR), Organizational Change, Renewable Energy Sector, Nigeria, Strategic Positioning, Change Management, Workforce Alignment, Capacity Building, Training and Development, Communication, Stakeholder Engagement, Resistance Mitigation, Impact Evaluation, Continuous Improvement, Socio-economic Impact, Sustainability Goals, Innovation, Agile Organizations, Strategic Importance, Sectoral Growth.

A mean field model for the development of renewable capacities

We propose a model based on a large number of small competitive producers of renewable energies, to study the effect of subsidies on the aggregate level of capacity, taking into account a cannibalization effect. We first derive a model to explain how long-time equilibrium can be reached on the market of production of renewable electricity and compare this equilibrium to the case of monopoly. Then we consider the case in which other capacities of production adjust to the production of renewable energies. The analysis is based on a master equation and we get explicit formulae for the long-time equilibria. We also provide new numerical methods to simulate the master equation and the evolution of the capacities. Thus we find the optimal subsidies to be given by a central planner to the installation and the production in order to reach a desired equilibrium capacity.

An opinion on minimizing the need for agricultural and public areas while renewable energy production capacity is increasing rapidly

An opinion on minimizing the need for agricultural and public areas while renewable energy production capacity is increasing rapidly