Electricity Generation Industry Research Articles

Least-cost decarbonization pathways for electricity generation in Finland: A convex quantile regression approach

This study investigates the least-cost decarbonization pathways in the Finnish electricity generation industry in order to achieve the national carbon neutrality goal by 2035. Various abatement measures, such as downscaling production, capital investment, and increasing labor and intermediate inputs, are considered. The marginal abatement costs (MACs) of greenhouse gas emissions are estimated using the convex quantile regression method and applied to unique register-based firm-level greenhouse gas emission data merged with financial statement data. We adjust the MAC estimates for the sample selection bias caused by zero-emission firms by applying the two-stage Heckman correction. Our empirical findings reveal that the median MAC ranges from 0.1 to 3.5 euros per tonne of CO2 equivalent. The projected economic cost of a 90% reduction in emissions is 62 million euros, while the estimated cost of achieving zero emissions is 83 million euros.

Research on the Collaborative Pollution Reduction Effect of Carbon Tax Policies

This study builds a Computable General Equilibrium model to investigate the synergistic effects and simulate the co-benefits of carbon tax policies. The conclusions are as follows: After implementing a carbon tax policy, when the carbon tax increases from 30 CNY/ton to 130 CNY/ton, and the reduction in CO2 emissions increases from 1.223 billion tons to 3.943 billion tons. At the same time, the reduction in SO2 emissions rises from 326,200 tons to 1,052,200 tons. However, overall, the reduction rate of SO2 is around 88.87% of the CO2 reduction rate. Thus, a carbon tax is also an effective policy pathway for synergistic pollution reduction and carbon mitigation. In terms of industry output, among the 15 industries, sectors such as electricity generation, aviation, and tertiary industries have increased their output, with the electricity sector achieving the highest increase of 2.9816%. Other industries have exhibited varying degrees of decline, especially coal, natural gas, oil, nonferrous metals, chemicals, steel, and building materials, with the coal industry output decreasing the most, by −49.4924%. Regarding energy consumption, as the carbon tax increases, the consumption of coal, oil, and natural gas all show a downward trend, with coal experiencing the largest decrease, at −49.5640%.

Water and Hydroelectric Power Sharing

A rational, defensible water allocation plan for current and future water supply conditions is critically important. According to the request and suggestion of State natural resources negotiators, our team developed a water allocation plan for five states (AZ, CA, WY, NM, and CO) Since general industrial water and power generation water are very important, we comprehensively analyze and establish a multi-objective optimal allocation model, which involves social benefits, economic benefits and water environmental benefits. Using the foal attain function in MATLAB to solve the model, we get Satisfaction of water demand for electricity generation and general industry in each state.

A Comparative Study Of Reliability-Centered Maintenance And New-Based Maintenance Approaches On A Working-Hours Engine: A Case Study

Maintenance is an important system in operation. In an era where the electricity generation industry focuses on 24-hour operations to maximize the production of electrical energy, which is needed for development and as a driving force for office equipment and the economy of the people in Timor- Leste, it is pushed to its absolute limit to meet this demand. With the increase in the operation of the electric energy generation unit, the wear and tear of the engine components will increase. So, the need for increased engine parts, to prevent failure. To remedy this situation and guarantee the machine’s continued peak performance, preventative maintenance is executed. Preventive maintenance (PM) is one subfield of maintenance that aims to forestall failures before they manifest. The maintenance, production, and management teams will need to work closely together to make PM a success. This article is a case study of Electrical Diesel Timor-Leste (EDTL), a firm with two power production facilities located in Hera and Betano, and it examines the causes of inefficient PM activity and the ramifications this has for the organization.

Fatigue life prediction of mistuned steam turbine blades subjected to deviations in blade geometry

The blades of the steam turbine are subjected to bending of the steam flow, centrifugal loading, vibration response, and structural mistuning. These factors mentioned contribute significantly to the fatigue failure of steam turbine blades. Low pressure (LP) steam turbines experience premature blade and disk failures due to the stress concentrations in the root location of the blade of its bladed disk. This study of mistuned steam turbine blades subjected to variation in blade geometry will be of great significance to the electricity generation industry. A simplified, mistuned, scaled-down steam turbine bladed disk model was developed using ABAQUS finite element analysis (FEA) software. The acquisition of the vibration characteristics and steady-state stress response of the disk models was carried out through FEA. Such studies are very limited. Subsequently, numerical stress distributions were acquired and the model was subsequently exported to Fe-Safe software for fatigue life calculations based on centrifugal and harmonic sinusoidal pressure loading. Vibration characteristics and response of the variation of the geometric blade of the steam turbine were investigated. Natural FEA frequencies compared well with the published literature of real steam turbines, indicating the reliability of the developed FEA model. The study found that fatigue life is most sensitive to changes in blade length, followed by width and then thickness, in this order. Analytical life cycles and Fe-Safe software show a percentage difference of less than 4.86%. This concludes that the numerical methodology developed can be used for real-life mistuned steam turbine blades subjected to variations in blade geometry.

The UAE’s energy system and GHG emissions: pathways to achieving national goals by 2050

Abstract In recent years, the United Arab Emirates (UAE) has developed strategies to increase renewable power generation and reduce emissions to net zero by 2050. Electricity generation and energy-intensive industries (EII) have the largest potentials for emission reduction. Therefore, an up-to-date inventory of greenhouse gas emissions and a study of the pathways to achieving the 2050 targets are essential. This study focuses on power production and EII (aluminium, steel and cement). The structure of these sectors is modelled and simulated up to 2050 using a system dynamics (SD) methodology. The SD model is validated to reflect the real-world state of the system using the emissions inventory projections as reference modes. Nineteen mitigation policies are considered in the selected sectors and four policy scenarios were simulated. The results show that implementing the Energy Strategy 2050 in the power sector can result in a reduction of 63.5% in emissions in that sector, which translates into a reduction of 33.5% overall by 2050. Additionally, implementing all identified mitigation strategies to full utilization in EII yields a 94% reduction in that sector, which translates into a 78% reduction overall. Decarbonizing the aluminium industry yields the highest emissions reductions, followed by power production, then cement and finally steel. In the best-case scenario, 22.1% of the business-as-usual emissions are still released and further decarbonization—mainly in the power sector—will be required. This is achievable given the trajectory of the UAE’s successful nuclear energy programme and the prospect of utilizing carbon capture, utilization and storage even further.

Prediction of fatigue life of mistuned steam turbine blades subjected to variations in blade geometry

There is a large number of power stations suffering from fatigue failures of the steam turbine blades. The steam turbine blades are also subjected to steam flow bending, centrifugal loading, vibration response, and structural mistuning. These mentioned factors significantly contribute to the fatigue failure of the steam turbine blades. Low-Pressure (LP) steam turbines experience premature blade and disk failures due to the stress concentrations at the blade root area of its bladed disk. Driven by the problems encountered by the steam power plant electricity generating utilities with regards to steam turbine blades fatigue failure, this study of the mistuned steam turbine blades subjected to variation in blade geometry will be of great significance to the electricity generation industry. A simplified, scaled-down mistuned steam turbine bladed disk model was developed using ABAQUS finite element analysis (FEA) software. Acquisition of the vibration characteristics and steady-state stress response of the disk models was performed through FEA. Thereafter, numerical stress distributions were acquired, and the model was subsequently exported to Fe-Safe software for fatigue life calculations based on centrifugal and harmonic sinusoidal pressure loading. The vibration characteristics and the response of the variation steam turbine geometric blade was conducted. The FEA natural frequencies compared well with published literature of the real steam turbines indicating reliability of the developed FEA model. The study found that the fatigue life is most sensitive to changes in blade length, followed by the width, and then the thickness, in this order. The analytical life cycles and Fe-Safe software shows the percentage difference of less than 4.86%. This concludes that the developed numerical methodology can be used for real-life mistuned steam turbine blades subjected to variations in blade geometry.

Decarbonization of the electricity generation sector and its effects on sustainability goals

The substitution of fossil fuels, especially coal, with renewable energy is a crucial step for the CO2 emissions reduction and the avoidance of Global Climate Change. The electric power generation industry is the first economic sector that will have to transition to renewable energy. However, wind and solar energy, the two most abundant renewable energy forms, are not dispatchable. The high penetration of these renewables in the energy market will create a demand–supply mismatch, which can only be alleviated with large-scale energy storage. This paper uses the case of Texas—a state that generates and consumes more electricity than several large, industrialized nations—to quantitatively examine the required infrastructure for the decarbonization of the electricity generation industry, while satisfying the current electric power demand in the State. Among the parameters that are examined are: the additional solar and wind capacity; the necessary energy storage infrastructure; the energy dissipation in the storage/regeneration process; and the effect of decarbonization on the cost of electricity and the welfare of the citizens. The computations show that the technology is available for the transition to a decarbonized electric power sector but requires significant investment in new wind and photovoltaic units as well as substantial energy storage. This would increase the electricity prices by a factor between 2.9 and 3.7 and, would have a disproportionate impact on the citizens in the lower income brackets.

The effect of investment and financing optimization policies for developing photovoltaic power generation in Cameroon; a dynamic CGE model assessment

With less than a decade remaining until 2030, global investment in clean energy access falls short of the anticipated levels required to achieve the sustainable development goals. Notably, nations with the greatest gaps in electricity access, particularly those in Sub-Saharan Africa, have been largely excluded from energy access funding. Interestingly, the energy sector policy documents of these countries have neglected to incorporate financing strategies or plans for photovoltaic (PV) power generation. This discrepancy in the literature underscores the need to assess the economic impact of finance and investment policies that align with long-term PV power generation targets. To address this gap, our study employs a dynamic Computable General Equilibrium model to evaluate the macroeconomic consequences of achieving Cameroon’s Nationally Determined Contributions for PV power generation through optimized PV investment and finance. The model examines three policy scenarios: the Business-as-Usual, SC1 scenario involving a stable 100% increase in PV investment, and SC2 scenario featuring a stepwise 5%–100% increase in PV investment. By simulating these scenarios, we aim to shed light on their effects. The results reveal that SC1 and SC2 exhibit a 50% higher final demand for PV investment compared to the BAU scenario. Optimizing PV finance and investment in both scenarios leads to a slowdown in Cameroon’s economic growth, with SC1 showing a more pronounced impact. Additionally, SC2 encourages rapid decarbonization in energy-intensive sectors such as crude oil production and electricity generation industries. However, the SC1 policy scenario results in a rapid reduction in total investment expenditure for PV power generation. By 2035, PV power generation is projected to be three times higher in both SC1 and SC2 compared to the BAU scenario. The SC2 policy scenario also predicts relatively high levels of consumption among rural affluent and urban impoverished households. In conclusion, our study highlights the pressing need for enhanced investment and finance strategies to propel PV power generation, particularly in underserved regions. By leveraging the findings of this research, policymakers can make informed decisions and implement policies that promote sustainable and inclusive energy access, driving progress towards the fulfillment of SDGs.

Toward carbon neutrality in China: A national wide carbon flow tracing and the CO2 emission control strategies for CO2-intensive industries

Massive emission of CO2 as a potential driver of climate change has become a global issue presented in front of the whole human beings. Motivated by the CO2 cut-down requirement, China has aggressively undertaken restrictions aiming for peaking the carbon dioxide by 2030 and achieving carbon neutrality by 2060. However, due to the complex structures of industry and fossil fuel consumption in China, specific carbon neutrality route and the CO2 reduction potential are still open questions. To address the bottleneck of the “dual-carbon” target, quantitative carbon transfer and emission of different sectors are traced based on mass balance model. The future CO2 reduction potentials are predicted based on structural path decomposition, with consideration of energy efficiency enhancement and process innovation. Electricity generation, iron & steel industry and cement industry are identified as the top three CO2-intensive sectors, with CO2 intensity of at around 517 kg CO2/MWh, 2017 kg CO2/t CS and 843 kg CO2/t clinker, respectively. Non-fossil power is suggested to substitute coal-fired boilers to achieve decarbonization of the electricity generation industry, which is the largest energy conversion sector in China. As two dominant energy end-users, the iron & steel industry and cement industry exhibit different CO2 emission sources, requiring divergent approaches for low-carbon development. For the iron & steel industry, around 89 % direct CO2 emission comes from fossil fuel. Immediate energy efficiency enhancements are suggested, followed by process innovations such as oxy-blast furnaces, hydrogen-based reduction, and scrap-based electric arc furnaces. For the cement industry, around 66 % of direct CO2 emission comes from carbonate decomposition. The process innovation with CO2 enrich and recovery would be the most effectiveness for carbon reduction. Staged low-carbon policies of the three CO2-intensive industries are introduced at the end of this paper, which is capable of achieving 75–80 % cut down of CO2 emission intensity in China till 2060.

West Virginia v. EPA: Behind the Supreme Court's Principled Decision

Amongst the US Supreme Court's more controversial decisions this past term was one which, by most accounts, garnered equal amounts of approbation and dismay. In the June 30, 2022 West Virginia v. Environmental Protection Agency (“West VA”) ruling, a staunch majority of the High Court ruled that the Environmental Protection Agency (EPA) lacked the statutory authority to impose radical changes upon the electricity generation industry. Some applauded the decision as a much‐needed check on unbridled administrative power. Others disapproved of thwarting the regulators from compelling a much‐needed shift in energy production away from fossil fuels and toward renewable energy generation sources.

A Framework for In-Service Life Extension of Hydroelectric Generation Assets

Abstract The integrity assessment of aged or worn out large electromechanical equipment units, such as in hydroelectric generators, for possible life extension has been identified as a growing challenge in the electrical power generation industry worldwide. Although the available recommended practices provide a general assessment process, it is necessary to have more detailed guidelines. This can be achieved by adding relevant theories and models which can capture time-dependent equipment unit degradation more precisely. Seeking to fulfill this gap, this work aims to present a framework that combines several techniques of data analysis, reliability, and decision-making to support engineers, operators, and managers in the often-complex decision process, regarding whether or not to extend the time in service of an equipment or system, thus postponing the moment of a scheduled maintenance shutdown. To demonstrate the application of the proposed framework, a case study is presented considering simulated scenarios based on data and information from a real Hydroelectric Power Plant. The results show how the reliability of the components and the remaining useful life of those in fault can impact the decision-making regarding the in-service life extension of a system.

Determinants of Renewable Electricity Generation in Africa

Abstract Africa’s electricity insecurity issues are getting worse. However, there has been significant foreign direct investment (FDI) absorbed by the renewable electricity generation (REG) industry in the last twenty years. To date, the impact of FDI on REG in Africa has yet to be investigated. This study thus empirically examines REG determinants with a special focus on FDI in forty African countries between 2000 and 2019. By using the Prais-Winsten panel corrected standard errors model, a range of promising results are revealed. Importantly, we find compelling evidence that FDI inflows directly and indirectly limit, or even impede, REG development. What’s more, Africa’s population growth undermines REG. However, the encouraging result is that raising awareness in Africa of renewable energy boosts REG. We conclude that there is a necessity for the gradual reform of lax environmental laws and renewable energy education plans in Africa.

Economic-Environmental-Social Benefits Assessment of Wind Power Hydrogen Production Project Based on Cloud-MULTIMOORA Approach

This study explores methods to assess the benefits of WPHPP from three aspects: economic, environmental, and social. Decarbonization has become an inevitable trend in the electricity generation industry. Storage integrated renewable energy generation plants have enhanced the stability of the output of renewable energy to a certain degree. Wind power hydrogen production projects (WPHPPs) could be a promising solution to the Chinese government’s peak carbon dioxide emissions goal. To achieve this goal, an evaluation system consisting of 12 main benefits factors is established. Then, an assessment approach based on Cloud-MULTIMOORA is proposed to select the best alternative. Specifically, HELTS-Cloud model is used to describe the information given by decision-makers and experts. Then, the SWARA and CRITIC methods are applied to obtain the subjective and objective weights. Additionally, a constrained optimization model is introduced to obtain the comprehensive weights. Finally, the MULTIMOORA-EDA method is used to obtain the final ranking of alternatives. Additionally, a case study is made to certify the usability and feasibility of the proposed method. This paper provides a method for assessing the benefits of WPHPP and promotes the application of this new kind of green energy project in the future.

Private management and strategic bidding behavior in electricity markets: Evidence from Colombia

This paper studies two key aspects of the introduction of private management in the Colombian electricity generation industry: (1) It quantifies the impact of changes to private management on bidding prices; (2) Verifies empirically the basic predictions from the theory of mixed oligopoly markets. Specifically, it investigates how the market concentration and the level of forward contracting affect the potential changes in the exercise of market power subsequent to the switch to private management. It applies a differences-in-differences model with staggered adoption on bidding daily data of the firms in the Colombian wholesale electricity market between 2002 and 2018. The results suggest that: (1) switches to private management provoke a non-permanent increase in bidding prices, consistent with an initial dominance of a market power effect which is gradually offset by cost improvements; (2) Higher levels of market concentration are associated with a greater increase in bidding prices resulting from the change to private management; (3) Lower levels of forward contracting are linked with higher bidding prices for both, public and private firms.

Relationship between alcohol consumption, stress, and depression in Ecuadorian workers: the moderating role of social support and sex

ABSTRACT This paper aims to analyze the association between alcohol consumption, work stress, and depression and the moderating effect of social support and sex in this relationship. In a sample of workers from an electric generation industry from Ecuador (N = 99), hierarchical linear regressions were conducted to test the direct and moderation effects. Results show that alcohol consumption is positively associated with work stress and depression; social support moderates alcohol consumption’s impact on depression but not on stress. This interaction effect is different according to sex. Further, an increase in alcohol consumption is associated with higher stress in women but not in men, and it relates to higher depression in men but not in women. Finally, we discuss the role of sex and social support as key factors to cope with the adverse effects of alcohol on well-being at work.

Diversified Sustainable Resource Availability by Optimizing Economic Environmental and Supply Risk factors in Malaysia's Power Generation Mix.

Population growth and economic development contribute to the rise in the demand for electricity. To meet the demand, electricity generation has been relying on fossil fuels. This practice has three major drawbacks: inevitable resource depletion, environmental concerns, and supply risk. Renewable fuels are touted to be the future of sustainable power generation. However, there is a need to assess and optimize the use of the available resource in an effective and efficient manner. In order to accomplish the desired objectives, this study adopted the multi-perspective approach for efficient utilization of resources, both in terms of cost and diversification, and also aimed to propose the optimum combination of technologies for electricity generation in Malaysia. In this regard, first, the potential of the resources was identified from the Malaysian prospective compliance with the five fuel energy action plan 2020. All the five fuels were examined in terms of economic, environmental and security parameters, and evaluated in the terms of cost to measure the total exposure in monetary units. For the economic analysis, the LCOE cost quantification method was used. Similarly for the restriction of carbon emission, a carbon-tax policy was proposed and a novel technique was designed for the quantification of excessive cost of security in the electricity generation industry. This study applied the simulation mathematical modelling and the graphical evaluation approach to optimize the power generation mix in terms of cost and diversity index. Hence, this study will assist the policy-makers in making efficient long-term policies considering the impact of various factors on total generation cost while adopting the concept of diversification for an efficient and uninterrupted power generation process.

Portfolio management and performance improvement with Sharpe and Treynor ratios in electricity markets

After 1980s, liberalization in energy industry accelerated. At that times, private sector started to show more tendency to electricity thanks to regulations and policies made by governments so electricity markets emerged and spread very rapidly, which created market risk that needs to be managed carefully along. Decision makers in electricity generation industry had to be faced this market risks besides other operational risks. They had to review policies regarding to risk management and they noticed that determining the right bidding strategy for electricity market and bilateral contract market was crucial. In this paper, Mean–variance, Semi-variance, and Down-side risk methods, which are common in portfolio optimization of financial literature are used to manage risk and to optimize electricity market bidding strategies and decision policy for an electricity generation company. Apart from the other limited studies, performances of optimal portfolio solutions are measured and further more improved with the help of Sharpe and Treynor ratios for electricity market. It is seen that direct use of portfolio management tools in electricity markets can cause sub-optimal solutions, so risk aversion constant of utility functions should be adapted. This study shows that optimal bidding strategies for electricity generators can be improved with the help of Sharpe and Treynor ratios. In order to demonstrate the results, two consecutive years of Turkish Day-ahead Market data are used in an empirical case study.

Thermal Storage for District Cooling—Implications for Renewable Energy Transition

The utilization of air conditioning in public and private buildings is continuously increasing globally and is one of the major factors fueling the growth of the global electricity demand. The higher utilization of renewable energy sources and the transition of the electricity-generating industry to renewable energy sources requires significant energy storage in order to avoid supply–demand mismatches. This storage-regeneration process entails dissipation, which leads to higher energy generation loads. Both the energy generation and the required storage may be reduced using thermal energy storage to provide domestic comfort in buildings. The development and utilization of thermal storage, achieved by chilled water, in a community of two thousand buildings located in the North Texas region are proven to have profound and beneficial effects on the necessary infrastructure to make this community independent of the grid and self-sufficient with renewable energy. The simulations show that both the necessary photovoltaics rating and the capacity of the electric energy storage system are significantly reduced when thermal storage with a chilled water system is used during the air conditioning season.

Microgrid for a Cluster of Grid Independent Buildings Powered by Solar and Wind Energy

The reduction of CO2 emissions and the avoidance of Global Climate Change necessitate the conversion of the electricity generation industry to rely on non-carbon sources. Additionally, the mitigation of the duck-curve effects in microgrids requires the development of grid-independent buildings. Computations were performed for a cluster of one thousand grid-independent buildings in the North Texas area, where air-conditioning demand is high in the summer months. The electricity demand is balanced with energy supply generated from wind turbines, photovoltaic cells, or stored energy in hydrogen tanks. The results indicate that with one wind turbine operating, each building must be fitted with 10.2 kW rating photovoltaics capacity and a tank with 5.2 m3 of hydrogen storage capacity to satisfy the hourly demand of the buildings’ community. The addition of more wind turbines significantly reduces the needed PV rating but increases the required storage. Investing in energy conservation measures in the buildings significantly reduces both the needed storage capacity and the PV cell ratings.