Lowest Levelized Cost Of Electricity Research Articles

Numerical analysis and ANN performance prediction of solar composite ventilation wall for built environment regulation

With the aim to achieve winter heating, summer heat insulation and year-round power generation as well as indoor pollutant purification, photovoltaic (PV) combined with phase change heat storage technology is ingeniously embedded in an adjustable solar composite ventilation wall with entire room model (SPVW-PV/PCM) in this study. Then, the effects of key parameters e.g. PCM melting temperature Tm and PV coverage ratio Cr on solar energy conversion and utilization with indoor environment creation are comprehensively illustrated by indoor temperature, exergy efficiency as well as power generation amount. In addition, to further clarify the application potential of the proposed model applied in different typical places in China, the artificial neural network (ANN) has been rarely adopted to predict the annual heating amount, power generation as well as its economic and environmental benefits. Research results show that the three numerical submodels closely align with previously published results, with only minor discrepancies observed in the decoupling model regarding Cout, vroom and PCM melt fraction, well within acceptable numerical tolerances of 9.87% RMSE. The thermal performance is significantly influenced by the key parameters of Tm and Cr, with at least 110 min of advance heating start-up time revealed, and excellent indoor temperature improvement of 1.59 K and 3.02 K are achieved in the heating season at Tm = 318 K or Cr = 0 % simulated group. The highest annual total energy conversion of 1367.39 kWh is surveyed in Guangzhou, corresponding to the lowest levelized cost of electricity (LCOE) of 0.18 $/kWh and the highest CO2 saving cost of 19.03 $/year. The total energy conversion effect and the CO2 saving cost can be effectively improved by 13.88 % and 13.82 % in Guangzhou, respectively, compared to the coupling off-grid PV and conventional wall in building. These research findings offer valuable insights for optimizing the design of SPVW-PV/PVM in indoor environmental construction and enhancing its overall applicability.

Comprehensive onshore wind energy assessment in Malawi based on the WRF downscaling with ERA5 reanalysis data, optimal site selection, and energy production

Malawi, despite its minimal CO2 emissions, faces huge climate impacts and a low electrification rate. Recognizing these challenges, this study presents a comprehensive and nationwide assessment of Malawi's wind energy potential, leveraging the high-resolution capabilities of the Weather Research and Forecasting (WRF) model. Unlike most site-specific studies, this study covers the entire country, factoring in different turbine hub heights. Through sensitivity analysis, the optimal configuration for the WRF model in Malawi was determined and ERA5 reanalysis data was used for initial and boundary conditions. The study's findings were validated using MERRA-2 reanalysis and actual observational datasets. A combination of GIS and the fuzzy analytic hierarchy process (AHP) was employed, integrating key factors like land use and topographical complexity to determine optimal wind farm sites. Notably, the wind suitability map uncovered significant potential for wind farm development. Furthermore, in the evaluation of a 50 MW wind farm, 80 m hub heights consistently outperformed 100 m elevations, both technically and economically. An 80 m wind farm at Site A can potentially power up to 32,931 urban and 84,475 rural households. Economically, 80 m hub heights showcased lower levelized cost of electricity (LCOE) values and faster payback periods than 100 m ones. Furthermore, these proposed wind projects can markedly reduce CO2 emissions, positioning Malawi in tandem with global sustainability aspirations. Overall, this study provides a key foundation for Malawi's renewable energy strategies, highlighting the potential for improved electrification and better climate change mitigation outcomes.

Scaling up 3D printed hybrid sorbents towards (cost) effective post-combustion CO2 capture: A multiscale study

A 3D-printed sorbent containing polyethylene-imine and multi-walled carbon nanotubes (PEI-MWCNT) was studied for post-combustion carbon capture. In this work, the adsorbent was printed on a kg scale and characterized for CO2 adsorption through lab experiments. A 6-step VSA process was simulated using the lab data to capture CO2 from a representative 800 MW power plant. The adsorbent captured >70 % of the CO2 and 95 % CO2 purity was achieved. The levelized cost of electricity (LCOE) was 130.2 $/MWh and the costs of CO2 captured and avoided were 80 and 100.12 $/tonne. However, a zeolite 13X-activated carbon (13X-AC) monolith achieved a lower LCOE of 118.1 $/MWh, with the captured and avoided costs being 63 and 78.4 $/tonne, respectively. The LCOE value for the 13X-AC monolith was 5.1 % lower than a reference-packed bed system with Zeolite 13X pellets. The corresponding cost values were lower by 9.1 % and 13.9 %, respectively for the costs of CO2 captured and avoided. The lab experiments on the PEI-MWCNT sorbent revealed that further work is necessary to improve the thermal stability and stability with long-term storage of the precursor paste.

Toward the Commercialization of Perovskite Solar Modules.

Perovskite (PVSK) photovoltaic (PV) devices are undergoing rapid development and have reached a certified power conversion efficiency (PCE) of 26.1% at the cell level. Tremendous efforts in material and device engineering have also increased moisture, heat, and light-related stability. Moreover, the solution-process nature makes the fabrication process of perovskite photovoltaic devices feasible and compatible with some mature high-volume manufacturing techniques. All these features render perovskite solar modules (PSMs) suitable for terawatt-scale energy production with a low levelized cost of electricity (LCOE). In this review, the current status of perovskite solar cells (PSCs) and modules and their potential applications are first introduced. Then critical challenges are identified in their commercialization and propose the corresponding solutions, including developing strategies to realize high-quality films over a large area to further improve power conversion efficiency and stability to meet the commercial demands. Finally, some potential development directions and issues requiring attention in the future, mainly focusing on further dealing with toxicity and recycling of the whole device, and the attainment of highly efficient perovskite-based tandem modules, which can reduce the environmental impact and accelerate the LCOE reduction are put forwarded.

Thermodynamic and Economic Analysis of a Standalone Supercritical Thermal Power Plant Integrated with Molten Carbonate Fuel Cell

A detailed technoeconomic analysis of a standalone steam cycle integrated with molten carbonate fuel cell and an organic Rankine cycle is presented herein. The modeling and thermodynamic analysis of the proposed plant is performed using a commercially available software tool called Cycle Tempo. The response surface methodology tool is employed to develop regression models to predict the plant's energy, exergy efficiencies, and levelized cost of electricity (LCOE) for varying independent factors: fuel utilization factor (uf) CO2 utilization factor (ϕ), and current density (i) of the fuel cell. The response surfaces developed from the models are used to conduct the parametric analyses on the plant. The desirability test performed for multiobjective optimization has shown the optimum plant configuration, with higher energy, exergy efficiencies, and a lower LCOE is obtained for uf = 0.85, ϕ = 60%, and i = 1000 A m−2 With an intent to reduce CO2 emissions, monoethanolamine‐based carbon capture system is implemented to the plant configuration, that exhibits maximum energy efficiency for ϕ = 90%, and results in an LCOE of 6.53 Rs kWh−1.

Analysis on data center power supply system based on multiple renewable power configurations and multi-objective optimization

With rapid development of data center industry, achieving low energy consumption and costs become important. How to provide an optimal configuration on renewable distributed energy systems combining data centers is challenging. This work discussed possible hybrid configurations by combining diesel, photovoltaic, wind, and battery capacity in data center. For each mode, renewable penetration (RP) and the Levelized Cost of Electricity (LCOE) were used to evaluate the performance of system. A multi-objective optimization analysis of the case is performed based on the entropy weighted-TOPSIS method, genetic algorithm, and NSGA-II aiming to obtain both a high RP and a low LCOE. Then, comparative research on optimal power configuration with conventional or renewable energy was conducted. The results show that it is recommended to take a high-rated PV power. When wind power is taken, it is only meaningful when combined with PV power system. For the hybrid renewable power system without an energy storage unit, it's easy to realize a lower LCOE compared to Diesel mode, and its realizable maximum RP is 28.31 %. When battery energy storage is taken in the hybrid system, six optimal configurations are recommended which can achieve the lowest cost of 0.21 $/kWh and the highest RP of 44.5 %.

Enhanced methanol reforming gas fuel cell system with electrochemical hydrogen pump: Conceptual design, system analysis, and multi-objective optimization

In this work, two methanol-reforming gas fuel cell systems coupled with an electrochemical hydrogen pump (EHP), namely, EHP pre-coupling and post-coupling fuel cell systems were proposed to achieve performance enhancement. A back propagation neural network surrogate model was established for the two systems to accurately describe system behavior, and a second-generation multi-objective non-dominated genetic algorithm was utilized for addressing the multi-objective optimization problem encompassing net output power, carbon mass-specific emission and the levelized cost of electricity. The linear non-weighted multi-attribute preference and technique for order preference by similarity to ideal solution multi-attribute decision-making methods were employed to select the optimal solutions. The optimized EHP pre-coupling fuel cell system exhibited lower carbon emissions (0.69 kgCO2/(kW·h)) and higher net output power (126.02 kW) compared to previous studies. While the EHP post-coupling system achieves a lower levelized cost of electricity (0.36 USD/(kW·h)), and stronger system stability (total efficiency reduction less 1 %). Both EHP-coupling systems offer viable process enhancements for fuel cell systems.

Energy storage as a service to achieve a required reliability level for renewable-rich standalone microgrids

Energy storage systems (ESSs) can help to reduce the intermittency and uncertainty of renewable energy supplies in power systems. ESSs are critical components of renewable-rich standalone microgrids (SMGs) to balance power generation and load demand, which is referred to as reliability. To achieve the same level of reliability as conventional power systems for renewable-based SMGs, significant investment in ESSs is required. However, due to the high investment costs of ESSs, the installation of large ESSs will not result in an affordable solution for achieving renewable SMG at the required reliability. As a result, this paper proposes a new sharing concept for ESS, namely energy storage as a service (ESaaS), to be implemented across microgrids as a low-cost alternative for improving reliability. In the proposed ESaaS concept, microgrids can use ESS from an ESS provider as required for different timeframes such as monthly, weekly, or daily, depending on the renewable resources and load profile characteristics. In this paper, the use of ESaaS is investigated over a range of timeframes for a 100 % renewable-based SMG with photovoltaic (PV), wind turbine (WT), and ESS. The SMG reliability is evaluated using Monte Carlo simulation both before and after the ESaaS strategy has been implemented. To evaluate the ESaaS affordability in improving the reliability of an SMG, this paper proposes the criteria of marginal cost of reliability, which indicates the rate of additional investment amount per percentage of reliability improvement. The marginal cost of reliability combines the economic and technical aspects of ESaaS in one simple criterion for effective decision-making among investment strategies such as different timeframes of ESaaS or permanent ESS. The simulation results show the ESaaS based on daily contract results in a lower marginal cost of reliability for the case study. To validate the effectiveness of the proposed ESaaS approach using marginal cost of reliability, the levelized cost of electricity (LCOE) is also calculated for different strategies of reliability improvement. The results confirm that the lowest LCOE is obtained using the strategy that provides the lowest marginal cost of reliability for the case study. In addition, a sensitivity analysis is performed to assess the difference in marginal cost of reliability under various uncertainties associated with the installed capacity of PV and WT, and the cost of utilising the ESaaS.

Experimental Investigation of a Small-Scale Parabolic Trough Concentrated Solar Power ‎Systems

Large-scale systems have a lower levelized cost of electricity than small-scale concentrated solar power systems. Thus, the purpose of the present study is to evaluate the potential of using standalone small-‎scale ‎concentrated ‎solar power collectors in order to generate process ‎heat ‎at ‎a ‎moderate ‎temperature, which directly utilizes thermal energy without the need to generate electricity. ‎A ‎parabolic trough ‎collector (3.6m2) ‎was ‎designed ‎and ‎manufactured, including a dual-axis solar tracking system with and without an insulating function. An ‎insulating ‎cavity ‎was incorporated to ‎minimize the heat ‎losses collected by the absorbed ‎tube. ‎The experiments ‎were ‎carried out during a time of high winds and unfavorable weather ‎in ‎Sabratha City. The findings of the experiments demonstrated that the produced temperature and the collected heat energy progressively increase until they reach their maximum value, and then gradually decrease. The maximum water ‎temperature ‎was 96ºC at ‎a ‎flow rate ‎of ‎‎0.5L/min, and ‎the highest amount of ‎heat energy was 550W/m². ‎Wind speed showed an important impact on the produced temperature; therefore, various comparative experiments were carried out in the same climate condition; ‎the experiment with the insulating function ‎presented the least heat loss, and it takes a higher edge of 11% in terms of efficiency. ‎In addition, the water temperature rose to 120°C where steam was generated at a zero flow rate, while the oil ‎reached 194ºC. In addition, a mathematical model was also implemented to theoretically study energy balance; with little expected discrepancy, its predictions and the experimental results agreed. In conclusion, the results presented reasonable markers of interest despite the poor environmental conditions during the experiments.‎

Perspective of staged hydrogen economy in Japan: A case study based on the data-driven method

Green hydrogen is an important energy source for replacing fossil fuels for a cleaner transition. While small-scale applications of green hydrogen have proven successful, large-scale nationwide adoption is essential. However, such a change cannot be accomplished overnight. Therefore, this study proposes a staged hydrogen economy scenario for Japan based on the existing energy sources. In this scenario, thermal power generation will be gradually phased out, and the energy shortfall will be compensated by increasing the penetration of renewables and energy storage. Hydrogen and ammonia serve as short- and long-term energy storage solutions, respectively. A data-driven model combining heuristics and optimization methods was designed to address optimal planning and sizing problems. The results show that it is feasible to achieve a 20 % reduction in thermal power by replacing it with renewable energy and hydrogen or ammonia. The lowest levelized cost of electricity (LCOE) in Tokyo (Kanto district) is 0.072 USD·kWh−1, which is comparable to the baseline scenario (using fossil fuels). Hydrogen and ammonia are effective in reducing the LCOE and addressing the mismatch between supply and demand. A higher reduction in thermal power requires further technological and policy support. According to the sensitivity analysis, hydrogen prices and carbon taxes have a high potential to advance the hydrogen economy scenario in the future.

Four failure modes in silicon heterojunction glass-backsheet modules

Silicon heterojunction technology (HJT) is expected to gain a significant market share in the near future. For HJT to deliver a low levelized cost of electricity (LCOE), it needs to have a high initial efficiency and degrade less than 0.5% relative per year. This work investigates damp heat-induced failure modes in silicon HJT glass-backsheet modules. Four unique failure modes are identified after damp heat (DH) testing: point failure (Type-1); failure around the interconnected regions of the busbars and ribbon wires (Type-2); failure between the busbars (Type-3); and failure at/on the interconnected regions of busbars and ribbon wires (Type-4). The Type-1 failure mode is likely caused by a chemical reaction between surface contaminants (introduced to the cells during handling or characterization before encapsulation) and moisture that increase charge carrier recombination and lead to a loss in maximum power (Pmax) of up to 40%rel in this study. Type-2 and Type-3 failure modes cause Pmax losses of ∼5%rel and 50%rel, respectively, in this study and can appear due to exposure to soldering flux used for connecting the ribbon wires and busbars. Finally, the Type-4 failure mode causes a Pmax loss of ∼16%rel in this study after the DH test. The evidence suggests that this failure mode is likely due to the interaction of acetic acid, generated from a reaction between the encapsulation material and moisture, ribbon wires, and silver paste (busbars), resulting in recombination loss. We believe these failure modes must be well understood and mitigated at preferably the solar cell level to ensure that HJT can meet its LCOE potential.

Assessment of the wind energy potential and economic viability of selected sites along Nigeria’s coastal and offshore locations

Wind energy is a promising sector in the power generation industry because it is renewable and globally available. In this research work, the wind energy potential and the economic viability of using wind turbines to generate electricity in some selected sites along Nigeria’s coastline and offshore locations were evaluated. Using the statistical two-parameter Weibull probability density function method, wind speed data retrieved from an indigenous oceanography company and global information system (GIS) were analyzed for wind energy harvest. The energy output, unit cost of electricity generated by three commercially available wind turbine models (3 MW, 4 MW, and 6 MW), net present value (NPV), and payback period were evaluated. Levelized cost of electricity (LCOE) sensitivity to the discount rate, foundation cost, and turbine lifespan were also examined. The findings from the study showed that the offshore sites have four times greater wind power potential than the coastal sites. The offshore sites can be categorized as “class IIIb” wind sites, making the locations suitable for wind energy harvest. The techno-economic analysis showed that the net gains from investing in a 60-MW wind farm in the region can be as high as $62,000,000.00, while the project payback time can be as low as 5.74 years. Two of the offshore sites are recommended for the development of an offshore wind farm in the country because of their relatively low LCOE (0.04 $/kWh), higher NPV, and lower investment payback time. The Vesta-117 model wind turbine is the most suitable wind turbine system and recommended for use in the region because of its low cut-in speed (3 m/s). Sensitivity analysis showed that the LCOE of offshore-01 was reduced by 31% when the lifespan of the V117 turbine was increased from 20 to 25 years. The results also showed that reductions in the discount rate and foundation cost positively affect the LCOE.

Uncertainties in estimating production costs of future nuclear technologies: A model-based analysis of small modular reactors

Predicting future costs of technologies not yet developed is a complex exercise that includes many uncertain parameters and functional forms. In that context, small modular reactor (SMR) concepts that are in a rather early development stage claim to have cost advantages through learning effects, standardized design, modularization, co-siting economies, and other factors, such as better time-to-market even though they exhibit negative economies of scale in their construction costs due to their lower power output compared to conventional nuclear reactors. In this paper, we compare two different approaches from production theory and show that they have a theoretically equal structure. In the second step, we apply these approaches to estimate a range of potential construction costs for 15 SMR projects for which sufficient data is available. These include water cooled, high temperature, and fast neutron spectrum reactors. We then apply the Monte Carlo method to benchmark the cost projections assumed by the manufacturers by varying the investment costs, the weighted average cost of capital, the capacity factor, and the wholesale electricity price in simulations of the net present value (NPV) and the levelized cost of electricity (LCOE). We also test whether the differences between the manufacturer estimates and ours differ between technology families of SMR concepts and apply a sensitivity analysis. Here we contribute to an intensifying debate in the literature on the economics and finance of SMR concepts. The Monte Carlo analysis suggests a broad range of NPVs and LCOEs: Surprisingly, the lowest LCOE is calculated for a helium-cooled high-temperature reactor, whereas all of the light water reactors feature higher LCOEs. None of the tested concepts is able to compete economically with existing renewable technologies, not even when taking their variability and necessary system integration costs into account. The numerical results also confirm the importance of the choice of production theory and parameters. We conclude that any technology foresight has to take as much of the case specifics into account, including technological and institutional specifics; this also holds for SMR concepts.

Optimum operation of an ejector-assisted combined flash-binary geothermal cycle using R245fa-isopentane mixture-based secondary working fluids

Combined flash binary geothermal cycle (CFBGC) is a traditional geothermal energy conversion technology. However, in a CFBGC, substantial exergy destruction occurs during the steam flashing. To address this issue, in the present study, the steam flashing device of the conventional CFBGC is replaced by an ejector. The ejector enhances steam cycle power output by ensuring a higher steam flow rate through the high-pressure steam turbine stage. The modified cycle is designated as the ejector assisted combined flash binary geothermal cycle (EACFBGC). To take advantage of temperature glide, various compositions of R245fa-isopentane mixture are considered as secondary working fluid. Optimum operating parameters corresponding to the maximum second law efficiencies of the proposed and conventional cycles are explored by applying an iterative method. Both considered cycles yield the highest second law efficiencies with the 0.7 mol fraction of isopentane in the working fluid mixture. For geo-fluid available at 170 °C, the second law efficiency of the optimized EACFBGC is about 8.08% higher than that of the optimized conventional CFBGC. The corresponding levelized cost of electricity (LCOE) is also 5.7% lower. In a word, the proposed EACFBGC can be considered as the upgraded CFBGC with higher energy conversion efficiency and a lower LCOE.

Comparative investigation on techno-economics of cascade supercritical CO2 combined cycles for waste heat recovery of typical gas turbines

An advanced supercritical CO2 (sCO2) power cycle for recovering waste heat from the gas turbine (GT) is thought to be an effective way to improve energy utilization efficiency and achieve low-carbon power generation. To obtain the best techno-economic sCO2 cycle configurations at various capacity levels, eight cascade cycle configurations were designed for coupled power generation with typical gas turbines in the power range of 11.4–593 MW, with the number of heaters, the number of split flow branches, and inter-cooling process as variables. The techno-economics of cascade sCO2 combined cycles were assessed and compared using various engineering equations. The results show that adding a heater and inter-cooling process increases the levelized cost of electricity (LCOE) by about 0.53 $/(MWh) and 0.99 $/(MWh) on average, respectively, while adding a split flow branch can decrease the LCOE by about 1.3 $/(MWh) on average. In addition, the increase in installed capacity can lead to a lower LCOE. When the net power range of the combined cycle is 14.9–767.1 MW, the LCOE of the triple cascade cycle ranges from 56.45 to 32.52 $/(MWh). Compared to a conventional combined cycle, using a cascade sCO2 cycle as the bottom cycle can decrease the LCOE by approximately 12.1–16.2%. Sensitivity analysis reveals that natural gas price has the greatest effect on LCOE, followed by annual operating hours, and suggests efficient ways to decrease the LCOE. The triple cascade cycle is recommended at all capacity levels due to its lower LCOE. The specific cost (SC) and LCOE prediction equations for the combined cycle are proposed for the first time to aid in the design and techno-economic assessment of the cascade sCO2 combined cycles.

Eco-Efficiency as a Decision Support Tool to Compare Renewable Energy Systems

Even though eco-efficiency (EE) is already applied to various energy systems, so far, no study investigates in detail the hourly, marginal and seasonal impacts of a decentralized energy system. This study assesses the hourly EE of the Research Park Zellik (RPZ), located in the Brussels metropolitan area for 2022 composed of photovoltaic installations, wind turbines and batteries. A cradle-to-grave life cycle assessment (LCA) to identify the carbon footprint (CF) and a levelized cost of electricity (LCOE) calculation is conducted. An existing design optimization framework is applied to the RPZ. Consumption data are obtained from smart meters of five consumers at the RPZ on a one-hour time resolution for 2022 and upscaled based on the annual consumption of the RPZ. As the EE is presented as the sum of the CF and the LCOE, a lower EE corresponds to an economically and environmentally preferable energy system. In a comparative framework, the developed method is applied to two different case studies, namely, (i) to an energy system in Vega de Valcerce in Spain and (ii) to an energy system in Bèli Bartoka in Poland. The average EE of the RPZ energy system in 2022 is 0.15 per kWh, while the average EE of the Polish and Spanish energy systems are 1.48 and 0.36 per kWh, respectively. When analyzing four selected weeks, both the LCOE and CF of the RPZ energy system are driven by the consumption of the Belgian electricity grid mix. In contrast, due to the very low LCOE and CF of the renewable energy sources, in particular wind turbines, the RPZ energy system’s EE benefits and lies below the EE of the Belgium electricity grid mix.

Reliability index based optimal sizing and statistical performance analysis of stand-alone hybrid renewable energy system using metaheuristic algorithms

Integration of renewable energy systems can provide reliable, environmentally sustainable, and cost-effective alternatives for meeting the demand for electricity in remote locations. In this study, recently developed meta-heuristic techniques are explored to find the optimal design for two combinations of off-grid hybrid renewable energy systems. To evaluate the performance, the Tasmanian devil Optimization (TDO) was compared to three meta-heuristic algorithms, called the COOT bird optimization algorithm (COOT), the Grey wolf algorithm (GWO), and the Beluga whale optimization (BWO), and determined the optimal design of the proposed off-grid energy system in terms of best and worst-case solutions. The system consisting of a solar-battery is more cost-effective, with the lowest total annual cost (TAC) of 36,859 $ and the lowest levelized cost of electricity (LCOE) of 0.0930 $/kWh for 0% LPSPmax level as compared to the wind turbine-battery-diesel generator with the highest TAC (102580 $) and LCOE (0.2589 $/kWh). Hence, a solar-battery hybrid system is more viable for producing clean energy with effective storage and better power system reliability enhancement. Also, the obtained simulation results reveal the supremacy of the TDO compared to the other three meta-heuristic algorithms, where it achieved the optimal solution with a quick convergence time and fewer oscillations.

Multi-Criteria Decision Analysis for Evaluating the Effectiveness of Alternative Energy Sources in China

The transition to renewable energy sources is crucial for mitigating the impacts of climate change and achieving sustainable development goals. In China, the rapid industrialization and urbanization have led to an increasing demand for energy, highlighting the urgent need to transition to alternative energy sources. This study aims to evaluate the effectiveness of alternative energy sources in China, considering multiple criteria such as cost, environmental impact, energy output, reliability, and scalability. We employed a Multi-Criteria Decision Analysis (MCDA) approach to compare and rank different energy sources based on these criteria. Our findings indicate that wind energy is the most effective alternative energy source overall due to its relatively low cost, high efficiency, moderate environmental impact, good scalability, and high reliability. However, geothermal energy had the lowest levelized cost of electricity (LCOE), while hydro energy performed well in terms of efficiency and reliability. The environmental impact of wind energy was found to be moderate but still less severe compared to other energy sources. Our study provides important insights into the trade-offs and considerations that policymakers and industry leaders must make when selecting which energy sources to prioritize. The findings highlight the need for a comprehensive and integrated approach to energy policy that balances economic, environmental, and social considerations. In conclusion, this study contributes to the literature by emphasizing the importance of considering multiple criteria when evaluating alternative energy sources. Our findings can inform policy decisions regarding the development of a sustainable and reliable energy mix in China, and have important implications for other countries seeking to transition to renewable energy sources.

Repowering a Coal Power Plant Steam Cycle Using Modular Light-Water Reactor Technology

This article presents the results of a techno-economic analysis of repowering a coal-fired power plant’s steam turbine system to instead accept heat produced by a pressurized water reactor-type small modular nuclear system (PWR SMR). This type of repowering presents a challenge due to the significantly lower steam pressure and temperature produced by the nuclear system. A 460 MW supercritical power unit with steam parameters of 28 MPa/560 °C/580 °C, operated in the Łagisza Power Plant in Poland, was selected for the analysis. After repowering, the turbine system would be fed with saturated steam from the steam generators of the SMRs at a pressure of 7 MPa and a temperature of 285 °C. In total, four options for repowering were analyzed. In all cases, the existing high-pressure section of the turbine was disconnected, and the existing low-pressure stages of the turbine, as well as all auxiliary and outward components (feedwater heaters, pumps, generator, condenser, condenser cooling, etc.), are re-used in their existing configurations, except for a feedwater-heater pump that needs to be replaced. In three cases, the existing intermediate pressure turbine section acts as the high-pressure stage of the repowered system. These cases include repowering without an additional reheater (case A), with an added single-stage reheater (B) and with an added two-stage reheater (C). In the fourth case (D), the existing intermediate pressure section was replaced by a new high-pressure turbine stage suited to the SMR live steam conditions. While all four repowering options are technically possible and may represent an economic advantage compared to a complete greenfield SMR installation, option D with a new high-pressure stage is clearly the best option available, with significant cost savings, leading to a lower levelized cost of electricity (LCOE) and a higher net present value (NPV) and net present value ratio (NPVR) than the greenfield case and all other repowering. For relatively new coal power plants with equipment in good condition, this type of repowering may present a cost optimal near-term pathway.

Beyond costs: How urban form could limit the uptake of residential solar PV systems in low-income neighborhoods in Ghana

This paper examines the relationship between urban form, residential rooftop solar PV potential, and levelized cost of electricity (LCOE) in high-income, middle-class, and low-income neighborhoods in Accra, Ghana. Using building footprint data, ArcGIS Pro, and linear regression analysis, we find a statistically significant association between urban form parameters (building density, neighborhood compactness, building footprint area, suitable rooftop area, and near distance between buildings) and the rooftop solar PV potential in all the three types of neighborhoods. However, the well-planned high-income neighborhood exhibited the highest rooftop solar PV potential with low LCOE values for most houses, while the lowest rooftop PV potential and highest LCOE values were found in the largely unplanned low-income neighborhood. The low-income neighborhood exhibited higher density with clustered building patterns and, consequently, lower rooftop PV potential. The LCOE ranged between $0.02/kWh-$0.19/kWh for most buildings, with 92 %, 74 %, and 51 % of houses in the high-income, middle-class, and low-income neighborhoods falling within this range, respectively. We conclude that while capital subsidies for residential solar PV can boost their uptake by urbanites, their effectiveness could be limited in low-income neighborhoods due to the limitations imposed by their urban form. It may be more appropriate for policy interventions to target such neighborhoods with community solar schemes while targeting high-income neighborhoods with building integrated solar photovoltaics.