Cost Of Electricity Research Articles

Estimation of Electric Energy Cost Thresholds in Analytical Energy Security Forecasts

Estimation of Electric Energy Cost Thresholds in Analytical Energy Security Forecasts

Treadmill to Generate Electricity by Human Power: A Review

Abstract: The increasing cost of electricity is largely due to insufficient power production and the growing demand for energy. Conventional power generation methods, especially those dependent on non-renewable resources, contribute significantly to environmental degradation. As a result, there is a critical need to develop alternative, environmentally friendly methods of generating electricity. This study investigates an innovative technique that involves generating power using manual treadmills. By connecting a generator to the rotating shaft of the treadmill, human motion can be transformed into electrical energy. This method produces no pollution and is capable of generating around 50–60 watts of power per hour. As a person walks on the manual treadmill, the force they apply causes the shaft to spin. This rotational motion is then mechanically transferred to a DC generator, which creates electricity. Due to the uneven application of force, the power output can be inconsistent, so a charge controller is used to regulate the electricity, ensuring a steady output. The energy produced is stored in a battery for future use. This technique presents a sustainable and creative solution for generating electricity on a small scale

The Role of Human Capital and Energy Transition in Driving Economic Growth in Sub-Saharan Africa

This research investigates the role of fossil fuel energy, renewable energy, and education in terms of years of schooling and mean years of schooling on the economic growth of 19 selected Sub-Saharan African countries. The primary objective is to assess whether renewable energy and educational attainment serve as viable long-term drivers of economic development in a region still heavily reliant on fossil fuels. We employed the newly developed and robust econometric estimators, including “Residual Augmented Least Squares (RALS) co-integration”, to estimate long-term links among the facets of study. Moreover, “Pooled Mean Group–Autoregressive Distributed Lag model (PMG-ARDL) and Quantile Autoregressive Distributed Lag (QARDL)” econometric estimator was employed to estimate the long and short coefficients of the antecedents of study. The estimations obtained from the PMG-ARDL and QARDL estimators provide evidence that the coefficients of fossil fuel energy and renewable energy on economic growth are positive. But surprisingly, the magnitude of renewable energy is greater than fossil fuel energy in Sub-Saharan countries that still depend on fossil fuels. Moreover, human capital and capital stock boost economic growth in the countries studied. The outcomes reveal that not only quality but also quantity of education play a vital role in boosting economic development. To deepen the understanding of the observed effects, the study also explores the transmission channels through which renewable energy and education foster economic growth. Renewable energy contributes by lowering the marginal cost of electricity, encouraging green industrial transformation, and serving as a catalyst for technological innovation. Concurrently, improvements in education—measured by both expected and mean years of schooling—elevate labor productivity and facilitate the absorption and diffusion of new technologies across sectors, thereby stimulating sustained economic performance. The empirical results provide valuable insights for government officials and policymakers in specific Sub-Saharan African countries.

Assessing the Implications of Integrating Small Modular Reactors in Modern Power Systems

This paper investigates the long-term impact of integrating emerging Small Modular Reactors (SMR) in modern power systems. A chronological simulation of the Greek day-ahead market and real-time balancing market with fine time granularity is conducted for a future 20-year period (2032–2051) under four SMR penetration scenarios using a specialized integrated market simulation software. Simulation results indicate that SMR units can be regarded as a promising electricity generation solution in the forthcoming energy transition landscape. The introduction of up to 3 GW of SMR capacity is projected to significantly decrease reliance on gas imports by up to 62%, reduce carbon emissions by up to 52%, and lower overall electricity costs for end-consumers by up to 21% as compared to a baseline scenario without SMRs. It is anticipated that SMR units are expected to leverage their operating advantages and generally achieve positive financial results when participating directly in the wholesale market. However, their economic viability is highly dependent on their initial capital expenditure and other operating cost components, which at present are highly uncertain.

A Metaheuristic Framework for Cost-Effective Renewable Energy Planning: Integrating Green Bonds and Fiscal Incentives

The integration of non-conventional renewable energy sources (NCRES) plays a critical role in achieving sustainable and decentralized power systems. However, accurately assessing the economic feasibility of NCRES projects requires methodologies that account for policy-driven incentives and financing mechanisms. To support the shift towards NCRES, evaluating their financial viability while considering public policies and funding options is important. This study presents an improved version of the Levelized Cost of Electricity (LCOE) that includes government incentives such as tax credits, accelerated depreciation, and green bonds. We apply a flexible investment model that helps to find the most cost-effective financing strategies for different renewable technologies. To do this, we use three optimization techniques to identify solutions that lower electricity generation costs: Teaching Learning, Harmony Search, and the Shuffled Frog Leaping Algorithm. The model is tested in a case study in Colombia covering battery storage, large- and small-scale solar power, and wind energy. Results show that combining smart financing with policy support can significantly lower electricity costs, especially for technologies with high upfront investments. We also explore how changes in interest rates affect the results. This framework can help policymakers and investors design more affordable and financially sound renewable energy projects.

Design Strategy and Optimization of a Renewable-Based Energy Mix in Latvia Region

The global increase in energy consumption is forcing the energy sector to evaluate the energy transition from fossil-based systems to renewable energy sources. Unfortunately, the impact of non-dispatchable generation affects grid stability and the ability to meet night time loads. In addition, a shift from summer to winter is required to increase the penetration of renewables. The introduction of storage technologies and the energy mix could overcome some of the problems associated with the green revolution. The aim of the work is to assess the best combination of generation systems and storage to meet the electricity needs of a 100 MW peak load city in the Latvian region with an annual energy load of 700 GWh. The energy hub considered, shown in the figure, represents a valuable evolution of a traditional gas-fired power plant coupled with the most cost-effective renewable resource generators: photovoltaic and wind turbines. To exploit the renewable surplus, part of the electricity is converted into hydrogen, which drives a fuel cell and a methanation system linked to the gas turbine. The method used is Trnsys-based numerical modelling coupled with multivariable particle swarm optimization to minimise the levelized cost of electricity under different renewable penetration scenarios. The LCOE is 0.96 EUR/kWh for a 50 % RES production and doubles for a fully renewable system. The optimised energy mix includes an electrolyser with a capacity equivalent to 24 % of the renewable capacity. The results of the analysis show the crucial role of the H2 system, which is 20 times larger than the CH4 system.

Feasibility Analysis of District Cooling Technologies in Cold Climate: a Comparative Study

Climate change-induced heat waves are becoming increasingly frequent in Europe, thereby affecting people's health, comfort and productivity. Hot summers and population growth have escalated the space cooling demand of urban energy landscapes, even in cold climates. It is in direct correlation with the increased demand for residential air-conditioning units and individual heat pumps. A relatively new technology, District Cooling (DC) is seen as an alternative to individual cooling solutions. Typical DC system consists of a centralized cooling plant that serves the cooling demand of multiple buildings by circulating chilled water through underground pipes. In some European cities, DC systems are competing with individual cooling solutions due to their ability to scale down carbon emissions and promote energy efficiency. However, these DC systems suffer from techno-economic challenges such as high investment costs and electricity cost fluctuation. In this scenario, the integration of energy storage technology with DC systems presents a promising solution through peak shifting, load sharing, energy savings etc. Chilled water energy storage is one of the widely considered technologies in the DC industry. Though some studies are reported in literature, the potential of thermal energy storage for DC applications is not fully explored. The feasibility of space cooling systems is influenced by location dependent factors such as climatic conditions, load profile and economic parameters. The aim of the study is to investigate the feasibility of district cooling technologies in cold climates from customer’s perspective. Based on preliminary results, it is observed that the district cooling plant coupled with chilled water storage has the lowest levelized cost of cooling (53.35 EUR/MWh) as compared to typical DC system and on-site electric chillers. This finding is highly influenced by the inputs and assumptions considered by the user. The current study also involves Modelica-based modelling of main components, simulation of developed models to assess the system performance and estimation of economic competitiveness of system configurations. It is expected that these findings shed light on the design and planning of the proposed system, thereby strengthening its widespread application across northern European cities.

The Optimal Operation of Ice-Storage Air-Conditioning Systems by Considering Thermal Comfort and Demand Response

The purpose of this paper is to discuss the optimal operation of ice-storage air-conditioning systems by considering thermal comfort and demand response (DR) in order to obtain the maximum benefit. This paper first collects the indoor environment parameters and human body parameters to calculate the Predicted Mean Vote (PMV). By considering the DR strategy, the cooling load requirements, thermal comfort, and the various operation constraints, the dispatch model of the ice-storage air-conditioning systems is formulated to minimize the total bill. This paper takes an office building as a case study to analyze the cooling capacity in ice-melting mode and ice-storage mode. A dynamic programming model is used to solve the dispatch model of ice-storage air-conditioning systems, and analyzes the optimal operation cost of ice-storage air-conditioning systems under a two-section and three-section Time-of-Use (TOU) price. The ice-storage mode and ice-melting mode of the ice-storage air-conditioning system are used as the analysis benchmark, and then the energy-saving strategy, thermal comfort, and the demand response (DR) strategy are added for analysis and comparison. It is shown that the total electricity cost of the two-section TOU and three-section TOU was reduced by 18.67% and 333%, respectively, if the DR is considered in our study. This study analyzes the optimal operation of the ice-storage air-conditioning system from an overall perspective under various conditions such as different seasons, time schedules, ice storage and melting, etc. Through the implementation of this paper, the ability for enterprise operation and management control is improved for the participants to reduce peak demand, save on an electricity bill, and raise the ability of the market’s competition.

Empirical Insights into Economic Viability: Integrating Bitcoin Mining with Biorefineries Using a Stochastic Model

This study explores integrating Bitcoin mining with lignocellulosic biorefineries to create an additional revenue stream. Profits from mining can help offset internal costs, reduce business expenses, or lower consumer prices. Using sensitivity analysis and Monte Carlo simulations, this study identifies key profitability drivers, such as electricity costs, hardware expenses, starting year, and operational time. Time emerged as an extremely sensitive factor and showed that delaying mining operations significantly raised production costs and the probability of profitable outcomes. In contrast, longer mining durations had a smaller yet sizable impact. Hardware costs, computational efficiency, and electricity prices also strongly influenced the outcomes. The majority of simulated events showed a loss. Moreover, the model showed that the marginal profitability of mining decreases over time. Nonetheless, the model demonstrated that under favourable conditions, it is possible to integrate Bitcoin mining into biorefineries and other productive ventures, thereby allowing for cost recovery using Bitcoin profits. For a biorefinery to mine Bitcoin and maximise cost recovery, it must start early, access low electricity prices, and preserve hardware capital characterised by low expenditure and high revenues. Finally, a discussion about the opportunities, risks, and regulations is highlighted.

DESIGN AND ANALYSIS OF AN AXIAL FLUX PERMANENT MAGNET GENERATORS WIND TURBINE FOR AUTOMATIC STACKING CRANES

Automatic Stacking Cranes are indispensable tools in modern ports that can transfer containers between the landside and the waterside. These cranes are powered by electricity and consume significant amounts of energy to meet annual production demands. This substantial electricity consumption often strains the port's power grid during voltage and current fluctuations, which can destabilize the ASC's power supply. Wind turbines offer a promising alternative energy source to address these problems. This study delves into the analysis of the optimal Axial Flux Generator structure for wind turbines and calculates the associated energy losses to determine the feasibility of a wind turbine system capable of supporting the ASC's power demands. The findings reveal that employing an AFG-based wind turbine can generate the required 88,497 Watts of power for the ASC, with an average rotational speed of 1,655 rpm. This represents an annual electricity cost saving for the port of approximately 39,701,029 Rupiah.

Evaluating the technical and economic feasibility of PV/wind/diesel hybrids in Mudug, Somalia, using a metaheuristic algorithm

ABSTRACT The reliance on fossil fuels for electricity generation drives carbon emissions and climate change. This study evaluates the technical and economic feasibility of a hybrid photovoltaic (PV)/wind turbine (WT)/diesel generator (DG) system in the north-central Mudug region of Somalia. Using MATLAB simulations, ten system configurations were analysed, including standalone DG, hybrid PV/DG, WT/DG, and PV/WT/DG, with and without battery storage (BS). Key metrics assessed include net present cost, levelized cost of energy, renewable fraction, excess electricity, and CO₂ reduction. The optimal configuration (Case 8) consists of a 50 kW DG, 80 kW PV, 90 kW WT, and 14 BS units, achieving a 71.5% renewable fraction, a net present cost of $701,083, and an energy cost of $0.2/kWh. This system reduces net present cost by 51% and fuel costs by 19% compared to DG alone. The findings highlight the economic and environmental viability of hybrid renewable systems in Mudug.

Techno-Economic Comparison of a Large-Scale Nuclear Power Plant, Small Modular Reactors, and Wind and Solar Power Plant Deployment

A comparison of the net present value, the payback period, and the levelized cost of electricity for three different projects of construction and exploitation of plants for electricity production with the aim of decarbonizing the energy sector is conducted. The first project is the building of a large-scale nuclear power plant with a light-water reactor, the second one is the deployment of several identical small modular reactors, and the third project is based on solar and wind power plants. Given that the sun and wind are intermittent renewable energy sources, it is inevitable to take into account the construction of an energy storage facility in the last project. The results show that the most profitable are the small modular reactors, while the investment into solar and wind power plants is burdened with the necessary electricity storage plant costs. Another drawback of an investment in solar and wind power plants is their shorter exploitation lifetime of 25 years compared to the long-term operation of nuclear power plants of 60 years or even more.

Comprehensive investigation of rooftop photovoltaic power plants with monocrystalline polycrystalline and thin-film technologies for exergy economic and environmental assessments

This research aims to conduct an exergy, economic, and environmental analysis of a 6.57 kWp rooftop photovoltaic (PV) power plant that combines different PV technologies, comprising 2 kWp of poly-crystalline (p-Si), 1.87 kWp of mono-crystalline (m-Si), and 2.7 kWp of thin-film amorphous silicon (a-Si) technologies. A comprehensive assessment was conducted to evaluate the environmental and techno-economic parameters of a PV plant system. This study is based on the performance data obtained over four years of energy production under the weather conditions of Kuala Lumpur, Malaysia. The embodied energy required for the manufacturing of the PV power plant was estimated using embodied energy indices available in the literature. Additionally, a detailed economic evaluation was conducted based on the electricity costs in Malaysia. Moreover, the environmental impact was assessed over the plant’s life cycle, considering the emission factors of coal power plants. Results indicate that the exergy payback time for the different technologies i.e., m-Si, p-Si, a-Si, when operated individually, and when combined within a single PV system, are found to be ~ , and years, respectively. Over its life cycle, it was found that the PV plant emits about . Emission breakdown analysis has revealed that the manufacturing process of the m-Si, p-Si, a-Si, and the monitoring systems contribute to , , , and of emissions, respectively. However, the PV power plant could offset about annually, equivalent to the emission of a car over approximately 3 years. This study offers critical insights into the exergy efficiency, environmental impact, and economic viability of a grid-connected rooftop PV power plant that integrates multiple PV technologies under tropical climate conditions.

Research on optimal scheduling and carbon revenue distribution strategy of "source-grid-load-storage" projects based on CCER methodology.

Research on optimal scheduling and carbon revenue distribution strategy of "source-grid-load-storage" projects based on CCER methodology.

The Mutriku Breakwater Wave Plant: Improvements and Their Influence on the Levelized Cost of Electricity (LCoE)

The Basque Energy Agency commissioned the Mutriku Wave Power Plant, using an Oscillating Water Column technology in 2011, and although the cumulative total power has been over 3 GW/h until 2023, the initial expectations of efficiency and LCoE have not been accomplished. This paper proposes a series of modifications to the breakwater and chamber geometry of the plant to increase energy production and efficiency. These proposed improvements were tested in experimental campaigns in the modular wave flume in the Energy Engineering Department at the University of the Basque Country, using a mock-up of the original installation. Some results also came from validated numerical simulations, showing that the response amplitude operator and the capture width ratio values were better than those in the original L-shaped power plant. The best configurations appear to be U-shaped and when harbor walls are used. In conclusion, this paper reports the proper configurations and localizations for new wave power plants that could be commercially competitive.

Thermodynamic and technoeconomic feasibility assessment on liquefaction of CO2 by-product of Afyon biogas power plant

The composition of the biogas produced in Afyon biogas power plant is approximately as follows: 55% CH4 (methane) - 40% CO2 (carbon dioxide)- 4.5% H2O (water) and trace amounts of other components. The methane produced is used in gas engines to generate electricity. Carbon dioxide, however, increases greenhouse gas emissions when released into the atmosphere. The model designed in this study includes the liquefaction and storage of CO2 and the technoeconomic analysis of this process. The analysis was performed in the Aspen Plus software, which is widely used in the analysis of complex processes involving numerious chemical reactions. According to the results of the thermodynamic analysis, the energy efficiency, exergy efficiency, net electrical power and liquid CO2 production rate of the plant were determined as 14.92%, 13.08%, 4,000 kW and 99 kg/h, respectively. According to the results of the technoeconomic analysis, unit electricity cost, liquid CO2 flow cost and TCC (total capital cost) are 77.5 $/MWh, 993.68 $/h and 47,548,200 $ respectively. The designed model has the potential to prevent the release of CO2 into the atmosphere at reasonable prices.

Ventilation Fans Offset Potential Reductions in Milk Margin from Heat Stress in Wisconsin Dairy Farms

Heat stress is becoming an increasing concern for dairy farmers due to elevated temperatures and wind shadow caused by rural development. Mechanical ventilation helps mitigate heat stress; however, transitioning from natural to mechanical ventilation increases operational costs. In this study, the number of days with no heat stress, as well as mild, moderate, and severe heat stress, was calculated for Madison, Wisconsin, over the past five years. Monthly milk margins were determined using all milk prices and feed costs from the Dairy Margin Coverage (DMC) program. The goal was to compare the potential reduction in milk margin coverage to the electricity costs of operating ventilation fans. The results indicated that while the five-year average milk margin reduction due to heat stress was USD 20,204 for a 600-head facility, the electricity cost accounted for approximately 42.6% of this amount. However, milk margins fluctuated annually due to volatility in milk and feed markets. For example, in 2021, the reduction in milk margins was estimated at USD 9804, while electricity costs reached USD 8574. It was concluded that in some years, when no severe heat stress occurs, the benefits of ventilation may be close to the expenses. Therefore, adhering to best management practices is critical for minimizing electricity costs while using ventilation fans in dairy operations.

Smart home energy management with long-term memory artificial rabbit algorithm for cost and load optimization

The optimization of home energy management (HEM) in the context of smart grids remains a significant challenge, particularly in balancing the effective regulation of smart devices with consumer energy demands. This study addresses this issue by introducing the Artificial Rabbit Optimization (ARO) algorithm and its enhanced version, the Long-Term Memory Artificial Rabbit Optimization (LMARO), specifically designed for optimizing energy consumption. Initial assessments for the proposed LMARO algorithm are performed on 7 Congress on Evolutionary Computation (CEC) test functions, and its obtained results were compared with recent optimization algorithms such as original ARO, northern goshawk optimization (NGO), wild horse optimizer (WHO), and grey wolf optimizer (GWO). Then, the simulations were carried out to manage electricity demand during peak periods. The proposed approach uses a multiple knapsack model to keep consumption below a set threshold. Simulations evaluate the LMARO algorithm's performance, revealing considerable reductions in both electricity costs and the peak-to-average ratio (PAR). Results demonstrate that LMARO surpasses ARO and unscheduled scenarios, achieving up to a 22% reduction in costs for individual households (compared to 8% for ARO) and a 39% reduction in scenarios involving ten households (versus 24% for ARO). Additionally, LMARO reduces PAR by up to 25% for 50 households and 30% for 100 households. These findings highlight the LMARO algorithm's effectiveness in optimizing residential energy management.

Life Cycle Cost Concept in Maintenance of Office Building of Karhutla Workshop Uptd Kphp Berau Barat

In Indonesia, Building Maintenance Guidelines have been stipulated in the Regulation of the Minister of Public Works No. 24/PRT/M/2008 concerning Guidelines for Building Maintenance and Care. The construction of the office building of the KARHUTLA workshop of UPTD KPHP Berau Barat is certain to increase every year, of course it must be followed by good and planned management, not only construction costs but there are important costs that need to be considered as a reference for managers to run and operate the building, namely planning the future costs of the building itself including operational costs, maintenance costs and replacement. The Life Cycle Cost (LCC) method is one part of the building management and maintenance strategy. From the background of the problem, a study was conducted entitled Analysis of Maintenance Based on Life Cycle Cost in the Office Building of the KARHUTLA Workshop of UPTD KPHP Berau Barat. The solution method in this calculation is for Investment Feasibility Analysis using Initial Cost Analysis, Operational Cost Analysis, Maintenance and Care Cost Analysis, Demolition Cost Analysis. From the results of the analysis, it was obtained that there were three groups that compiled the Life Cycle Cost analysis plan for the UPTD Berau Barat workshop building, namely, initial construction costs, operational costs, maintenance costs and demolition costs. The initial construction cost of the UPTD Berau Barat workshop building cost Rp2,515,780,000.00 (48%), operational costs of Rp870,000,000.00 (17%), maintenance and care costs of Rp1,601,275,363.86 (30%), demolition costs of Rp251,178,000.00 (5%). The total Life Cycle Cost of the UPTD Berau Barat workshop building for 25 years is Rp5,234,233,363.86. In operational costs, the largest cost is the utility cost of Rp540,000,000.00 (62%) followed by employee salary costs of Rp330,000,000.00 (38%). In terms of maintenance costs, the largest costs are architectural costs of Rp. 1,433,035,692.66 (92%), followed by mechanical & electrical costs of Rp. 123,719,815.22 (8%).

A Multi-Scheme Comparison Framework for Ultra-Fast Charging Stations with Active Load Management and Energy Storage Under Grid Capacity Constraints

Grid capacity constraints present a prominent challenge in the construction of ultra-fast charging (UFC) stations. Active load management (ALM) and battery energy storage systems (BESSs) are currently two primary countermeasures to address this issue. ALM allows UFC stations to install larger-capacity transformers by utilizing valley capacity margins to meet the peak charging demand during grid valley periods, while BESSs rely more on energy storage batteries to solve the gap between the transformer capacity and charging demand This paper proposes a four-quadrant classification method and defines four types of schemes for UFC stations to address grid capacity constraints: (1) ALM with a minimal BESS (ALM-Smin), (2) ALM with a maximal BESS (ALM-Smax), (3) passive load management (PLM) with a minimal BESS (PLM-Smin), and (4) PLM with a maximal BESS (PLM-Smax). A generalized comparison framework is established as follows: First, daily charging load profiles are simulated based on preset vehicle demand and predefined charger specifications. Next, transformer capacity, BESS capacity, and daily operational profiles are calculated for each scheme. Finally, a comprehensive economic evaluation is performed using the levelized cost of electricity (LCOE) and internal rate of return (IRR). A case study of a typical public UFC station in Tianjin, China, validates the effectiveness of the proposed schemes and comparison framework. A sensitivity analysis explored how grid interconnection costs and BESS costs influence decision boundaries between schemes. The study concludes by highlighting its contributions, limitations, and future research directions.