Global Electricity Generation Research Articles

Model predictive control of multilevel inverter used in a wind energy conversion system application

The rapid growth of renewable energy, particularly wind energy, has significantly contributed to global electricity generation, with global renewable energy capacity reaching an all-time high of 3870 gigawatts (GW) in 2023. However, ensuring high power quality for grid integration remains crucial for wind energy's role as a leading source in the energy transition. This necessitates the development of advanced Wind Energy Conversion Systems (WECS) capable of regulating current, voltage, and frequency to ensure power quality. This work proposes a novel predictive control strategy for multilevel inverters in WECS to achieve a total harmonic distortion (THD) below 5% in the generated electrical power. The proposed predictive control algorithm is presented and implemented in a WECS simulation with a multilevel inverter. The performance of the proposed system is evaluated through simulations using MATLAB/SIMULINK. Our results demonstrate that the predictive control approach outperforms traditional controllers for multilevel inverters in terms of output voltage, harmonic reduction, execution time, and overall WECS control.

A blockchain‐based resilient and secure framework for events monitoring and control in distributed renewable energy systems

AbstractThe rapid and green energy transition is essential to deal with the fast‐growing energy needs in both public and industrial sectors. This has paved the way to integrate distributed renewable energy resources () such as solar, hydro, wind, and geothermal into the power grid (). Wind and solar are free, zero‐carbon emission, and everlasting power sources that contribute 5% and 7% of global electricity generation, respectively. Therefore, the fast, secure, and reliable integration of these green is critical to achieve the instant energy demands. Smart grid due to inherited characteristics such as intelligent sensing, computing, and communication technologies can effectively integrate the . However, the existing smart grid communication architecture faces various cyberattacks, resulting in poor integration, monitoring, and control of . In this respect, blockchain technology can provide fast, secure, and efficient end‐to‐end communication between in the smart grid. In this study, the authors propose a blockchain‐based resilient and secure scheme called for wireless sensor networks ‐based events monitoring and control in . Experimental studies and performance analyses are carried out to predict the efficiency of the proposed scheme by considering numerous standard metrics. The extensive numerical results demonstrated that the proposed scheme is significant in terms of secure, resilient, and reliable information transmission for in .

Assessing the decarbonization of electricity generation in major emitting countries by 2030 and 2050: Transition to a high share renewable energy mix

The urgent need to mitigate the severe environmental impacts of climate change necessitates a transition to a low-carbon energy infrastructure, crucial for decarbonization and achieving global sustainability goals. This study investigates the decarbonization trajectories of five major economies and significant carbon emitters: the United States of America (USA), China, Japan, Germany, and India. We focus on evaluating two decarbonization scenarios for power generation. Scenario 1 explores the use of a generic storage system for reducing critical excess electricity production (CEEP), maintaining the same thermal power plant capacity as in the reference year 2021. In contrast, Scenario 2 models thermal power plants to meet the exact electricity demand without introducing a new electricity storage system. The primary aim is to assess the feasibility and implications of achieving a 100% share of renewable and nuclear energy by 2030 and 2050 in these countries. EnergyPLAN software was utilized to model and simulate the electricity systems of these countries. The two scenarios represent different degrees of renewable energy integration, demonstrating possible transitional pathways towards an environmentally friendly electricity generation system. The study provides a comparative analysis of the outcomes for each country, focusing on carbon emissions reduction and the impact on annual total costs in 2030 and 2050. Results show that by 2030, China could reduce its emissions by 88.5% and 85.14% in Scenarios 1 and 2, relative to 2021 levels. From the two scenarios considered in all the countries, India records the highest percentage reduction while Germany has the least percentage emission in reference to 2021, with a potential decrease of 90.63% and 52.42% respectively. By 2050, carbon emissions in the USA will be reduced by 83% and 79.8% using Scenario 1 and Scenario 2 decarbonization pathways. This research significantly contributes to understanding the decarbonization potential of global electricity generation. It provides vital data for policymakers, energy planners, and stakeholders involved in developing sustainable energy policies.

Time and frequency analysis of daily-based nexus between global CO2 emissions and electricity generation nexus by novel WLMC approach

The studies have focused on changes in CO2 emissions over different periods, including the COVID-19 pandemic. Even if CO2 emissions are temporarily reduced during the pandemic according to annual figures, this may be misleading. Considering annual figures is important to understand the overall trend, but using data with much higher frequency (e.g., daily) is much better suited to investigate dynamic relationships and external effects. Therefore, this study comprehensively analyzes the association between CO2 emissions and disaggregated electricity generation (EG) sources across the globe by employing the novel wavelet local multiple correlation (WLMC) approach on daily data from 1st January 2020 to 31st March 2023. The results demonstrate that (1) based on the main statistics, daily CO2 emissions range between 69 MtCO2 and 116 MtCO2, indicating that there is an oscillation, but no sharp changes over the analyzed period. (2) based on the baseline regression using the dynamic ordinary least squares (DOLS) approach, the constructed estimation models have a high predictive ability of CO2 emissions, reaching ~ 94%; (3) in the further analysis employing the WLMC approach, there are significant externalities between EG resources, which affect CO2 emissions. The results present novel insights about time- and frequency-varying effects as well as a disaggregated analysis of the effect of EG on CO2 emissions, demonstrating the significance of the energy transition towards clean sources around the world.

A novel DWTimesNet-based short-term multi-step wind power forecasting model using feature selection and auto-tuning methods

The share of wind power in global electricity generation is increasing year by year, and the prediction of wind power is a practical and necessary scientific research. In this paper, the TimesNet model is used for multistep prediction of wind power. It is observed that the prediction error of the TimesNet model could be improved by replacing the original convolutional structure with the dilated convolution and weight normalization (WN). And in addition, the population-based training (PBT) algorithm is introduced to guide the model tuning. Missing values in the raw data are imputed to enhance data integrity. And the maximal information coefficient (MIC) method is chosen to select features for the different influences on wind power, which reduces the computational effort of the model. In order to demonstrate the effectiveness of the proposed model MIC-PBT-DWTimesNet, nine models are arranged in this paper as a control group and compared with their predicted values with each other. It can be observed that the RMSE of the proposed model MIC-PBT-DWTimesNet is decreased by 17–33% compared to the base TimesNet method.

LITERATUR STUDY OF UTILIZATION OF SOLAR CELLS FOR SUPPORTING AGRICULTURE

Indonesia is known as a country whose economy depends on or is supported by the agricultural sector. But now climate change poses an increasingly greater threat. The agricultural sector is very vulnerable to climate change because of its dependence on weather. Renewable energy is expected to surpass the use of coal in electricity generation in the second half of the 2020s, and by 2050, renewable energy will account for 50% of global electricity generation. Based on the data, there is a lot of use of solar cells to support energy in the agricultural sector. There are several uses, such as irrigation, drying, spraying, fertilizing, pest control, and controlling pH and temperature. Apart from that, using solar panels also has the advantage of being environmentally friendly, economical, efficient, and can be used for a long period.

Renewable energy sources: is it a panacea for global electricity generation or not?

Renewable energy sources can cover mankind’s entire electricity demand under certain conditions but such carbon-free global power engineering, being heavily dependent on natural factors (wind, insolation, rainfall), will not meet the reliability and fail-safe operation requirements. Nuclear power claims to be the only comparable stabilizing carbon-free energy source to overcome this limitation.

Optimization of pumped hydro energy storage design and operation for offshore low-head application and grid stabilization

The increasing share of renewable energy sources in the global electricity generation defines the need for effective and flexible energy storage solutions. PHES with their technically matured plant design and wide economical potential can generally match those needs. But especially for lowland countries, where low-head PHES applications are needed, the current turbomachinery technologies offer no viable solutions for LH-PHES to be a competitive energy storage technology in the context of realizing the European Green Deal.The new developments in low-head hydraulic turbomachineries, smart operation schemes and powerful site identification algorithms can shape these plants towards a viable future technology. Therefore, this study demonstrates that, through a novel design of a contra-rotating, variable-speed, reversible pump-turbine especially designed for low-head operation, PHES can operate over a wide range of hydraulic heads and discharges at very high efficiencies. Additionally, it shows that, with the use of more than one CR-RPT unit in parallel action, different power settings can be selected to achieve high efficiency with fast reaction times.Furthermore, the newly developed operation simulation code is used to support the RPT design developments considering the most compact plant design, which is achieved by Prototype 0 at LAT of 31 m and dam diameter of 1600 m. Thus, the investment costs are minimized while the revenue is maximized through the delivery of grid services tailored to suit the market needs. Moreover, the novel development of a smart site identification algorithm, supports RPT design development at high potential offshore sites (in the Greater North Sea).

The role of global installed wind energy in mitigating CO2 emission and temperature rising

As a key component in mitigating global warming and achieving sustainable development strategies, wind power has received widespread attention and support from governments around the world. Numerous countries are engineering ambitious programs to map and project the mitigation potential of wind energy expansion to combat future global warming. Here, using the global installed wind capacity data, we identity that a total of 837 GW of wind energy installed capacity (WEIC) in 31 countries generated about 2186 TWh of electricity, that is 1311 Mt of CO2 mitigation, in 2021. Considering power mix transformation, wind power could account for more than 30% of total global electricity generation by the mid-21st century, when many countries expect to realize carbon neutrality, and could reduce CO2 emission up to 14871 Mt by 2050 and 32864 Mt by 2100. Meanwhile, the global phenomenon of the future southward shift of wind energy resources makes the wind energy development in low-latitude countries, such as Brazil, Vietnam, and Central African, more confident. Combined with the Shared Socio-economic Pathways (SSPs), we find that the mitigation benefits of wind energy expansion are significant and will directly reduce global warming by up to 0.64 °C by the end of the century (NZE deployment scenario, SSP3-7.0). For China and the United States, the share of renewable energy will reach 78% and 84% by 2050 (APS scenario) and the cumulative climate mitigation by wind power will be 0.12 °C and 0.11 °C during 2020–2100, respectively. The findings strongly support the development and practice of global climate mitigation energy solutions.

Efficiency analysis of nuclear power plants: A comprehensive review

Nuclear power plants play a significant role in global electricity generation, offering a reliable and low-carbon energy source. Maximizing the efficiency of nuclear power plants is crucial for optimizing energy output and reducing operational costs while ensuring safety and environmental sustainability. This paper presents a comprehensive review of the efficiency analysis conducted on nuclear power plants, covering various aspects such as thermal efficiency, conversion efficiency, fuel utilization, and overall plant performance. The review synthesizes the existing literature, discusses key factors influencing efficiency, and highlights potential areas for future research and improvements. It is revealed from the present review that the efficiency of the Boiling Water Reactor (BWR) of the Nuclear Power Plant is 32% and which can be increased to 33% by using advanced BWR. Also, the efficiency of the Pressurized Water Reactor (PWR) of the Nuclear Power Plant is 33% and which can be increased to 36.5% by using the PWR with Gas Burner and Reheating. On the other hand, the efficiency of the Small Modular Reactor (SMR) of the Nuclear Power Plant is 33.4% and which can be increased to 35.5%, 37.4% and 45% by using SMR with Gas Burner, SMR with Reheating and SMR with CCGT, respectively. Therefore, it is predicted that the Small Modular Reactor (SMR) is the most economic Nuclear Power Plant as it has higher thermal efficiency when it is incorporated with Combined Cycle Gas Turbine (CCGT).

Effects of the circular economy, environmental policy, energy transition, and geopolitical risk on sustainable electricity generation

The recent global paradigm shift toward sustainable green development necessitates revealing the likely green determinants of sustainable electricity generation in order to derive key policy recommendations for dealing with the global energy crisis. As a result, the current study focuses on the drivers of global electricity generation (EG) and identifies environmental policy (EP), energy transition (ET), geopolitical risk (GPR), and circular economy (CE) as novel determinants. The study employs a battery of advanced econometric techniques, including quantile VAR, quantile slope estimate, and wavelet-based correlation methods, for empirical analysis. The quantile VAR-based connectedness confirms the modeled series' significant interconnectedness. Furthermore, the findings suggest that CE plays an important role in promoting the global EG process, as evidenced by positive effects across quantiles. When the effects of ET and EP are considered, a positive relationship between ET, EP, and EG is discovered, implying that ET and EP are important drivers of electricity generation. Furthermore, GPR has significant and negative effects on EG across most quantiles, indicating that the EG process suffers a significant loss as a result of GPR. Furthermore, the wavelet-based correlation method confirms the significant association between selected series, supporting the preceding findings. In order to achieve sustainable electricity generation, several results-based policies are proposed for local and global authorities.

Increased hydropower but with an elevated risk of reservoir operations in India under the warming climate

Hydropower is a significant contributor to clean global electricity generation; therefore, it plays a crucial role in climate change mitigation. Notwithstanding major hydropower dams in India are in diverse climatic regions and exposed to risks because of the warming climate, potential changes in hydroclimate remain largely unexplored. Using observations and climate projections, we demonstrate the hydroclimatic changes in the upstream catchments and their implications for the hydropower generation of 46 major hydropower dams in India. A warmer (up to 5.0°C) and wetter projected climate with a substantial increase (5.0-33%) in precipitation will lead to an increased (7-70%) inflow to reservoirs of major dams. Increased inflow will enhance (9-36%) the hydropower production for most dams in the future, with a more prominent rise in central India dams. A simultaneous rise in extreme inflow and high reservoir storage conditions is projected under future climate for most dams. However, future climate changes project a favorable hydroclimate for hydropower production, with the associated risks related to extremes.

Renewable Energy and Small Business: Synergies and Sustainability Strategies

The article highlights topical and, in many respects, debatable problems of the development of renewable energy both in the world economy and in Russia. Despite a 75% increase in generation from wind and solar stations in 2021, Russia's share in global electricity generation significantly exceeds its share in the use of renewable energy sources. What should be the priorities of the Russian state policy in this area and what are the methodological foundations for the formation of a strategy for the development of “green energy” – ​the solution of these issues lies in line with the priorities of modern economic science? Based on the tools of the general organizational science – ​tektology – ​the paper provides a theoretical justification for the possibility of synergistic effects when small and medium-sized businesses are involved in the development of the renewable energy sector, including for Russian conditions. The result of the formation of new ties between the subjects of the sectors under consideration and the participation of small and medium-sized businesses in the project of creating “green energy” will be to increase the structural stability of the transformable energy complex of Russia, diversify its fuel and energy balance, reduce the negative anthropogenic impact on the environment while reducing the cost of electricity for a wide range of end consumers. Using the example of solar microgeneration on the vertical enclosing surfaces of buildings and structures, the advantages that are currently not fully used for its development in the northern and eastern regions of Russia, which can be realized by small and medium-sized businesses without taking the territories out of economic circulation, are revealed.

The ecological potential of manure utilisation in small-scale biogas plants

The main sources of greenhouse gas emissions, accelerating global climate change, are heat and electricity generation. To lower these emissions, an expansion of renewable energy usage is required. Biogas plants, a flexible renewable power source, are one possibility, and are already widely established in the European energy system. This study focuses on the utilisation of raw manure in closed systems to reduce direct CO2eq. emissions. It is the first to compare manure treatment in different types of small-scale biogas applications and under the impact of increasing temperatures resulting from climate change. The environmental impact in terms of four impact categories is evaluated by means of a life cycle assessment. Two cases are investigated: a biogas plant with either subsequent combustion in a combined heat and power plant or the direct usage of biogas as a simplified and less expensive application. The analysis shows that the first case yields –173 kgCO2eq. per m3 of manure, whereas the simplified one causes 20.9 kgCO2eq. per m3 of manure. If the first case is scaled with the currently existing number of small-manure plants in Germany, emissions of 464 mil. t CO2 eq. are mitigated per year. With increasing average annual temperatures, higher manure credits are generated and so the emissions of both plant options are reduced to –264and –69.5 kgCO2 eq. per m3 of manure, respectively, ascribing the direct biogas usage reductions of GHG emissions. Consequently, both systems have the potential for reducing emissions due to improved manure management and can contribute to mitigating climate change.

Optimizing PV-Hosting Capacity with the Integrated Employment of Dynamic Line Rating and Voltage Regulation

A record amount of renewable energy has been added to global electricity generation in recent years. Among the renewable energy sources, solar photovoltaic (PV) is the most popular energy source integrated into low voltage distribution networks. However, the voltage limits and current-carrying capacity of the conductors become a barrier to maximizing the PV-hosting capacity in low voltage distribution networks. This paper presents an optimization approach to maximize the PV-hosting capacity in order to fully utilize the existing low voltage distribution network assets. To achieve the maximum PV-hosting capacity of the network, a novel method based on the dynamic line rating of the low voltage distribution network, the coordinated operation of voltage control methods and the PV re-phasing technique was introduced and validated using a case study. The results show that the proposed methodology can enhance the PV-hosting capacity by 53.5% when compared to existing practices.

Controlled Bidirectional DC Circuit Breaker With Zero Negative Current for High Load Shift Applications

Global electricity generation by renewable energy sources and the electrification of the transportation system are gaining more importance to mitigate climate change. The dc system plays a significant role in these developments. To protect dc systems, dc circuit breakers with advanced technology are required that are fast and reliable. Various solid-state dc circuit breakers, such as <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$Z$</tex-math></inline-formula> -source and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$T$</tex-math></inline-formula> -source circuit breakers, have been presented in the literature to meet the dc system demand; however, these topologies suffer from limitations such as high conduction loss, complexity in design, no physical isolation, and presence of negative current flow in load during reclosing. To overcome the aforementioned limitations, a bidirectional solid-state dc circuit breaker (BD-SSCB) that detects the overload or short-circuit faults and responds instantaneously to mitigate the fault current has been proposed in this article. The controllable shutoff function is much needed in applications where sudden load change occurs continuously during the normal operation, such as varying acceleration of an electric vehicle. The proposed BD-SSCB is validated using spice simulations and hardware experiments with varying system parameters for a system rating of 400 V/10 A.

Exploring the sustainability challenges facing digitalization and internet data centers

Internet data centers have received significant scientific, public, and media attention due to the challenges associated with their greenhouse gas, water, and land footprint. This resource greedy data services sector continues to rapidly grow driven by data storage, data mining, and file sharing activities by a wide range of end-users. A fundamentally important question then arises; what impact does data storage have on the environment and is it sustainable? Water is used extensively in data centers, both directly for liquid cooling and indirectly to generate electricity. Data centers house a huge number of servers, which consume a vast amount of energy to respond to information requests and store files and large amounts of resulting data. Here we examine the environmental footprint of global data storage utilizing extensive datasets from the latest global electricity generation mix to throw light on this data sustainability issue. The analysis also provides a broad perspective of carbon, water, and land footprints due to worldwide data storage to through some light on the real impact of data centers globally. The findings indicate that if not properly handled, the annual global carbon, water and land footprints resulting from storing dark data might approach 5.26 million tons, 41.65 Gigaliters, and 59.45 square kilometers, respectively.

Targeted Green Recovery Measures in a Post-COVID-19 World Enable the Energy Transition

Despite the significant volume of fiscal recovery measures announced by countries to deal with the COVID-19 crisis, most recovery plans allocate a low percentage to green recovery. We present scenarios exploring the medium- and long-term impact of the COVID-19 crisis and develop a Green Recovery scenario using three well-established global models to analyze the impact of a low-carbon focused stimulus. The results show that a Green Recovery scenario, with 1% of global GDP in fiscal support directed to mitigation measures for 3 years, could reduce global CO2 emissions by 10.5–15.5% below pre-COVID-19 projections by 2030, closing 8–11.5% of the emissions gap with cost-optimal 2°C pathways. The share of renewables in global electricity generation is projected to reach 45% in 2030, the uptake of electric vehicles would be accelerated, and energy efficiency in the buildings and industry sector would improve. However, such a temporary investment should be reinforced with sustained climate policies after 2023 to put the world on a 2°C pathway by mid-century.

Energy storage for large scale/utility renewable energy system - An enhanced safety model and risk assessment

Renewables recorded 26.2% of global electricity generation in 2018 and expected to rise to 45% by 2040 attributed to nations commitment to reduce greenhouse gases since the signing of Paris agreement 2015. Policies friendly towards the development of renewable energy sources are developed, but the risk and safety assessment are still based on the traditional analytic and probabilistic risk-based assessment practices such as Event Tree Analysis (ETA), Fault Tree Analysis (FTA), Failure Mode Effect Analysis (FMEA), Hazards Identification (HAZID), Hazards and Operability (HAZOP). These practices are viewed as own envelop of methodology whilst sharing a lot of common parameters and working principles. Analytic approach is becoming ineffective with increasingly complex energy system integrating renewables. There are on-going research proposing systemic based risk assessment approach but without incorporating advantages from analytic approach. The aim of this paper is to provide a comprehensive analysis of risk and safety assessment methodology for large scale energy storage currently practices in safety engineering today and comparing Causal Analysis based on System-Theoretic Accident Model and Process (STAMP) and Systems-Theoretic Process Analysis (STPA) with fault tree analysis, FMEA, HAZID, HAZOP. This paper demonstrated that systemic based risk assessment such Systems Theoretic Process Analysis (STPA) is suitable for complicated energy storage system but argues that element of probabilistic risk-based assessment needs to be incorporated. This is to ensure holistic risk assessment is performed to energy storage system and provide a new viewpoint for underlying safety model in integrated manner based on performance requirements, human factor, environmental, management, safety, and legislation. The results describe the improvement of risk assessment technique via Systems Theoretic Process Analysis-Hybrid (STPA-H) using a case study of grid connected Photovoltaic (PV) system with Li-ion battery storage. The hazards and mitigation measures identified from STPA-H are presented and compared with existing approach. STPA-H technique proposed is applicable for different types of energy storage for large scale and utility safety and risk assessment. This paper is expected to benefit Malaysian government with the progression of Large-Scale Solar 3 (LSS3) and serve as reference to future energy system risk assessment.

Decarbonization in state-owned power companies: Lessons from a comparative analysis

A rapid decarbonization of the electricity system is urgently required for the Paris Agreement objectives to stand a reasonable chance of being met. While state-owned power companies (SPCs) are the dominant firm type in the global electricity sector, representing nearly two thirds of global electric power generation capacity, most climate policy literature focuses on private sector companies when analyzing decarbonization interventions. SPCs’ distinct corporate governance structures, objectives, relationships with government, and sources of finance, however, can be markedly different from those of private companies. Here, we develop a framework for analyzing the extent to which common and divergent features of SPCs, and the markets in which they operate, affect their relationship to government interventions on decarbonization. We also consider the implications of these relationships for the effective implementation of sector-wide decarbonization strategies. We then apply this framework using a comparative case study analysis of six major SPCs, and highlight how differences in their agency, motivation, capacity, and market exposure may result in different potential responsiveness to government regulatory, policy and market interventions on decarbonization. We generalize these findings by developing four SPC archetypes and illustrate how they might respond differently to government interventions targeting decarbonization. Our analysis posits that SPCs can, under the guidance of governments pursuing ambitious climate policy, be more effective vehicles for decarbonization relative to private sector companies, particularly when they operate with a high degree of operational independence, are insulated from competitive pressures, and have the financial and technical capacity to invest in the decarbonization of their asset base. Similarly, market-wide policy interventions, such as carbon pricing mechanisms, could in practice be less effective interventions with respect to SPCs than their private counterparts when the SPC is ill-equipped to translate these incentives into decarbonization action because it is mandated to pursue supplementary objectives other than profit maximization alone. Ultimately, governments will need to step up their climate action to achieve carbon neutrality. SPCs can, and where they are major market players, must be key actors in driving decarbonization when the appropriate interventions are utilized and therefore deserve significantly more attention in the climate policy debate.