Minimum Levelized Cost Of Electricity Research Articles

Energetic and economic analysis of novel cascade systems for ammonia-fed solid oxide fuel cell

This study proposes an ammonia-fed cascade recirculation system comprising: (1) two stacks connected in series and (2) an anode off-gas recirculation configuration to enhance electrical efficiency of the system. The proposed system is both energetically and economically investigated. Under energetic analysis, the effects of fuel utilization, temperature, and recirculation rate, are clarified. Information from energetic analysis is employed to investigate levelized cost of electricity (LCOE) value in the entire working range. Due to the high potential of the cascade configuration, a cascade system without recirculation is also investigated using the same methods. The results reveal that the cascade-only and cascade recirculation systems obtain electrical efficiency up to 67.78% and 68.80%, respectively. The minimum LCOEs are 0.485 and 0.486 $/kWh, respectively, which are both higher than grid electricity cost; however, compared with other ammonia-fed SOFC systems, the two cascade configuration-based systems show significant improvements in both efficiency and cost.

Scenario-Based Optimization towards Sustainable Power Generation in Sudan

Sudan faces an electricity supply shortage despite its abundant natural resources. This paper aims to manage these resources for sustainable power generation to meet Sudan’s electricity demand. The sustainability assessment integrates quantitative analysis of power generation’s impacts on water, land, and greenhouse gas (GHG) emissions, in addition to the levelized cost of electricity (LCOE). Cost-effective, resource- and GHG emission-effective, and GHG-stringent scenarios are executed in this study to investigate the impact of different constraints on the sustainability of power generation in Sudan. The average LCOEAV for these three scenarios is 43.64–100.00 USD/MWh, with the lowest in the cost-effective scenario and the highest in the resource- and GHG emission-effective scenario. The LCOEAV for the stringent scenario is 32% higher than the cost-effective scenario. The two governmental and lowest-cost plans, which serve as the business-as-usual cases in this study, are optimized and comparatively evaluated. The sensitivity analysis is conducted by reducing each clean energy pathway to a minimum LCOE of 42.89 USD/MWh. Solar–photovoltaic (PV), wind, and hydroelectricity pathways are the most sensitive to the LCOE and can significantly contribute to Sudan’s total power generation if their costs are minimal. A rational scenario for power generation in Sudan is developed to improve sustainability performance and avoid the unreliability of the studied scenarios and cases. The rational average generation mix comprises 44% clean energy, 46% fossil fuels, and 10% imported electricity pathways.

An adaptive modeling for bifacial solar module levelized cost and performance analysis for mining application

AbstractPower density and efficiency typically dominate design approaches for power electronics. However, cost optimality is in no way guaranteed by these strategies. A design framework that minimizes the (i) levelized cost of electricity (LCOE), (ii) collection of light, and (iii) irradiance of the generation system is proposed as a solution to this flaw. From an improvement of the swarm behavior optimization model to get a minimum LCOE of solar panel, we design to optimize height, tilt angle, azimuth angle, and some parameters to solve the objective function and LCOE improvement problem to obtain the optimal design problem. In adaptive salp swarm optimization (ASSO), this change's proposed model producer swarm behavior is regarded as an adaptive process that keeps the algorithm from prematurely converging during exploration. The proposed algorithm's performance was confirmed using benchmark test functions, and the results were compared with those of the salp swarm optimization (SSO) and other efficient optimization algorithms. LCOE condition as far as “land‐related cost” and “module‐related cost” demonstrates that the optimal design of bifacial farms is determined by the interaction of these parameters. This proposed model can be used to evaluate visibility on building surfaces that are suitable for mining applications like crushing. Experimentation results show Minimum LCOE AS 0.05 (€/Kw)minimum irradiance and collection light as 336.23(w/m2) and 83.02%n proposed framework model. The swarm optimization method is contrasted with the optimal parameters derived from a conventional solver.

Analysis on thermodynamic and economic performances of supercritical carbon dioxide Brayton cycle with the dynamic component models and constraint conditions

Turbomachinery and heat exchanger are key components of the supercritical carbon dioxide (CO2) Brayton cycle system. It is of great necessity to investigate realistic cycle performance coupled with components characteristics. This paper analyzes the efficiency and economy of supercritical CO2 Brayton cycle based on the dynamic component models and constraint conditions. The parametric limits are compressor inlet temperature range from 305 K to 310 K, inlet pressure range from 7.4 MPa to 8.3 MPa, and maximum cycle pressure range from 15 MPa to 30 MPa. The results reveal that the achievable efficiency of a simple cycle is 0.13–0.62% points lower than theoretical maximum efficiency after considering constraint conditions. Meanwhile, the levelized cost of electricity (LCOE) under constraint conditions is 0.00038–0.00085$/(kW·h) higher than the theoretical minimum LCOE. For a recompression cycle, constraint conditions have a more significant impact. The achievable efficiency of the cycle is 0.81–1.21% points lower than the maximum efficiency because of the constraints, and the available LCOE under constraint conditions is 0.0012–0.0018$/(kW·h) higher than the theoretical minimum LCOE.

Flare gas-to-power by direct intercooled oxy-combustion supercritical CO2 power cycles

With more than 150 billion m3 of gases annually flared around the world, gas flaring is a major source of greenhouse gas emissions that contaminates the environment with more than 400 Mt CO2/year. Therefore, utilizing the flared gases efficiently becomes inescapable and one of the most promising utilization technologies is using Gas-to-Power (GTP). However, most of the available GTP technologies are still using conventional power cycles that have limited efficiencies and produce high-level of emissions. Herein, we use direct oxy-combustion (DOC) supercritical CO2 (sCO2) power cycle, instead, to realize the desired no flaring-no emissions solution. Two innovative flared-intercooled sCO2 power cycles that utilize flare gases and natural gas as fuel are introduced. In the first flared power cycle (FPC1), the flare gases are mixed with the natural gas before being combusted in the DOC. While in the second cycle (FPC2), the flare gases are used to perform a reheating process for the exhaust flow of the primary heater (DOC) after being partially expanded in a high-pressure turbine. Comprehensive energetic, exergetic, exergoeconomic, levelized cost of electricity (LCOE), and multi-objective optimization analyses are conducted for each configuration over practical ranges of operating conditions for six flare gas samples that significantly differ in their composition and specifications. A minimum LCOE of 5.02¢/kWh is achieved by sweet flare gas sample in FPC1 at Tmax of 731 °C, Pmax of 300 bar, Pmin of 40 bar, Tmin of 32 °C, and Ẇnet of 50 MW with energy efficiency of 45.10%. At the optimized conditions, FPC1 and FPC2 show superior energetic and economic performances compared to indirect-combustion power cycles, however, indirect combustion of flare gases may perform better than FPC2 at low capacities and therefore recommended for future work.

Thermoeconomic and optimization analyses of direct oxy-combustion supercritical carbon dioxide power cycles with dry and wet cooling

Oxy-combustion supercritical CO2 power cycles have the advantages of high-energy efficiency and near-zero pollutant emissions. Thus, these cycles are considered as an efficient way to reduce CO2 emissions while maintaining economic growth. The major drawbacks of this technology include the lack of validated levelized cost of electricity (LCOE) studies; lower turbine inlet temperatures studies to accommodate the integration of various energy sources; solutions for the thermodynamic imbalance of the regenerator; and investigating the dry- versus the wet-cooling methods. These drawbacks are addressed in this paper by presenting comprehensive thermoeconomic and optimization analyses for three direct oxy-fuel sCO2 power cycles in wet and dry-cooling conditions. The first cycle M1 is a direct oxy-fuel sCO2 power cycle without preheater, the second cycle M2 integrates a preheater in parallel with the low-temperature recuperator of M1 while the third cycle M3 integrates a preheater in parallel with the high and low-temperature recuperators of M1. Results show that the integration of the preheater improves the thermal efficiency of M2 by 5.81% (wet), and 3.27% (dry), and of M3 by 13.27% (wet), and 6.58% (dry). The LCOE of M1 (without preheater) is higher than that of M2 by 10.8% (wet), and 5.7% (dry), and of M3 by 19.1% (wet), and 11.4% (dry). A minimum LCOE of 4.667¢/kWhe is obtained for M3 (wet) and of 6.139¢/kWhe for M3 (dry). At higher waste heat source temperature of 700 °C, the overall efficiency is improved by an average of 11% and the LCOE is reduced by 1.43 ¢/kWhe.

Thermoeconomic optimization of a novel high-efficiency combined-cycle hybridization with a solar power tower system

Today, the international community is obligated to utilize renewable energy due to accelerated energy consumption on the one hand and the necessity of environmental pollution reduction, on the other hand. Meanwhile, the Solar Power Tower (SPT) is at significantly optimum conditions for integration with conventional fossil power plants due to reaching temperatures of up to 1200 °C and a high-power generation capacity. The present paper demonstrates the optimal layout of the new hybrid-cycle power generation section with SPT. The Heliostat field was optimized as a transient optical model at all hours of the year by considering the city of Seville as a case study using the System Advisor Model (SAM). Subsequently, the cycle’s thermo-economic model was developed using Engineering Equation Solver (EES) to minimize the Levelized Cost Of Electricity (LCOE). In the following, four fluids of n-Butane, R245fa, n-Pentane, and R123 were utilized for the final analysis as a downstream fluid. Through this process, the appropriate operating fluid was selected. The study results demonstrate an increase in the efficiency of the novel proposed cycle layout compared to a solar power tower power plant with standard pressurized air-fluid; moreover, it reduced fuel consumption, CO2 emission, and LCOE. The maximum efficiency and the minimum LCOE were53.25% and 61.8 $/MWh, respectively. The n-Pentane fluid was recognized as the most appropriate fluid for the downstream cycle. Due to the optimization of solar parts, the number of heliostat field mirrors were 889, with a total area of 131,525 m2 and a central tower height of 105.87 m. The novel presented cycle layout solves a portion of the pressurized air receiver limitations, enabling access to higher efficiency and lower LCOE with the real payback time (RPBT) of 3.876 years, the annual solar share of 23.1%, and reduction of CO2 production by 33,426 ton/year. Consequently, this study’s proposed cycle layout signifies a promising future for using SPT with high efficiency and better environmental and economic conditions.

Economic-environmental evaluation and multi-objective optimization of supercritical CO2 based-central tower concentrated solar power system with thermal storage

We address the optimal design of central tower-concentrated solar power (CSP) system combined with supercritical CO2 Brayton cycle and thermal storage under economic and environmental objectives. The economic objective is measured by the levelized cost of electricity (LCOE), and the environmental objective by the power plant’s total environmental impact potential (TEIP) considering the system’s global warming, acidification, and eutrophication emission. A multi-objective mixed-integer nonlinear programming (MINLP) model is developed that takes into account the main characteristics of CSP plant, e.g. unit operations, working fluid thermodynamics, equipment sizing, thermal storage capacity. Life cycle assessment and economic evaluation of the manufacturing, construction, operation and decommission stages of the systems are also embedded in the model. The multi-objective MINLP problem is solved by a tailored algorithm, and the resulting Pareto solutions are analyzed to identify the tradeoffs between the economic and environmental performance. The proposed approach is illustrated through a case study of a 50 MWe CSP plant. Results show that the framework is able to obtain the system’s economically-environmentally optimal design in reasonable time. A minimum LCOE of 115.82 $/MWh can be achieved for the most cost-effective design, and a minimum TEIP of 320.54 × 103 mPE90 can also be achieved for the most environmentally friendly design. A ‘balanced’ solution is identified with an LCOE of 116.89 $/MWh and TEIP of 330.29 × 103 mPE90. Numerical studies also reveal that while the Brayton cycle only accounts for a small proportion of the total investment, spending more on enhancing the efficiency of its equipment is cost-effective to improve the overall economic and environmental performance of the system.

Techno-Economic Optimization of CSP Plants with Free-Falling Particle Receivers.

Particle receivers are one of the candidates for the next generation of CSP plants, whose goal is to reduce the levelized cost of electricity (LCOE) to 0.05 $/kWh. This paper presents a techno-economic analysis to study if a CSP system with free-falling particle receiver can achieve this goal. The plant analyzed integrates two ground-based bins to store the excess energy and a supercritical CO2 cycle to generate electricity. The model used for the analysis presents several upgrades to previous particle systems models in order to increase its fidelity, accuracy, and representativeness of an actual system. The main upgrades are the addition of off-design conditions during the annual simulations in all the components and an improved receiver model validated against CFD simulations. The size of the main components is optimized to obtain the system configuration with minimum LCOE. The results show that particle CSP systems can reduce the LCOE to 0.056 $/kWh if the configuration is composed of 1.61 × 106 m2 of heliostats, a 250 m high tower with a 537 m2 falling particle curtain, and 16 h thermal energy storage.

Impacts of solar multiple on the performance of direct steam generation solar power tower plant with integrated thermal storage

Solar multiple (SM) and thermal storage capacity are two key design parameters for revealing the performance of direct steam generation (DSG) solar power tower plant. In the case of settled land area, SM and thermal storage capacity can be optimized to obtain the minimum levelized cost of electricity (LCOE) by adjusting the power generation output. Taking the dual-receiver DSG solar power tower plant with a given size of solar field equivalent electricity of 100 MWe in Sevilla as a reference case, the minimum LCOE is 21.77¢/kWhe with an SM of 1.7 and a thermal storage capacity of 3 h. Besides Sevilla, two other sites are also introduced to discuss the influence of annual DNI. When compared with the case of Sevilla, the minimum LCOE and optimal SM of the San Jose site change just slightly, while the minimum LCOE of the Bishop site decreases by 32.8% and the optimal SM is reduced to 1.3. The influence of the size of solar field equivalent electricity is studied as well. The minimum LCOE decreases with the size of solar field, while the optimal SM and thermal storage capacity still remain unchanged. In addition, the sensitivity of different investment in sub-system is investigated. In terms of optimal SM and thermal storage capacity, they can decrease with the cost of thermal storage system but increase with the cost of power generation unit.

Techno-economic comparison of solar organic Rankine cycle (ORC) and photovoltaic (PV) systems with energy storage

In this work, we compare the technical and economic performance of a solar organic Rankine cycle (s-ORC) system with thermal energy storage (TES) and a solar photovoltaic (PV) system with battery storage at a capacity of 50 kWe. A two-dimensional variable space, comprising solar field area and storage capacity is swept for optimum operational zones of five performance indicators, namely annual energy generation, capacity utilization factor (CUF), capital cost, levelized cost of electricity (LCOE) and energy wasted. Minimum LCOE estimated for the s-ORC system was 0.19 USD/kWh with a CUF of 0.56. For the same CUF value, the PV system incurs a LCOE of at least 0.26 USD/kWh. The minimum LCOE of the PV system yields an attractive value of 0.12 USD/kWh, but it includes no battery storage and thus delivers a significantly lower CUF of 0.27. The results indicate that for achieving minimum LCOE, the operational zones of the two technologies differ in terms of storage requirement. The s-ORC technology potentially offers improved reliability of power supply through cost-effective TES. Visualization of annual energy and costs in the form of contour maps facilitates a holistic comparison of the two technologies with their storage options.

The Most Economical Mode of Power Supply for Remote and Less Developed Areas in China: Power Grid Extension or Micro-Grid?

There are still residents without access to electricity in some remote and less developed areas of China, which lead to low living standards and hinder sustainable development for these residents. In order to achieve the strategic targets of solving China’s energy poverty, realizing basic energy service equalization, and comprehensively building up a moderately prosperous society, several policies have been successively promulgated in recent years, which aim to solve the electricity access issue for residents living in remote and less developed areas. It is of great importance to determine the most economical mode of power supply in remote and less developed areas, which directly affects the economic efficiency of public investment projects. Therefore, this paper focuses on how to select the most economical power supply mode for rural electrification in China. Firstly, the primary modes to supply electricity for residents living in the remote and less developed areas are discussed, which include power grid extension mode and micro-grid mode. Secondly, based on the levelized cost of electricity (LCOE) technique, the life cycle economic cost accounting model for different power supply modes are built. Finally, taking a minority nationality village in Yunnan province as an example, the empirical analysis is performed, and the LCOEs of various possible modes for rural electrification are accounted. The results show that the photovoltaic (PV)-based independent micro-grid system is the most economical due to the minimum LCOE, namely 0.658 RMB/kWh. However, other power supply modes have much higher LCOEs. The LCOEs of power grid extension model, wind-based independent micro-grid system and biomass-based independent micro-grid system are 1.078 RMB/kWh, 0.704 RMB/kWh and 0.885 RMB/kWh, respectively. The proposed approach is effective and practical, which can provide reference for rural electrification in China.

Methodology of determining the optimum performances of future concentrating solar thermal power plants in Algeria

The newly adopted version of the National Renewable Energy Program of Algeria offers the country the possibility to integrate 27% of renewable energy in the national energy mix. Preservation of fossil resources, diversification of electricity production and contribution to sustainable development are among challenges that face the country nowadays. The objective of this paper is to propose a methodology and outline a procedure to determine the best configuration and the optimum design of future solar thermal power plants with minimum levelized cost of electricity (LCOE) and maximum annual power generation as objectives. Our study is based on a Concentrating Solar Power (CSP) plant of capacity of 50 MW to be erected in Hassi R'mel City, in the south of Algeria. In this methodology, the size of the solar field, the fossil fill fraction of backup system and full load hours of storage are optimized for the minimum LCOE using the concept of solar multiple. Moreover, different models, technologies and scenarios for parabolic trough and central tower receiver power plant are presented. LCOE presents a basis of comparison for weighted average costs of different power generation technologies. It is clearly shown that the solar power plant based on central receiver tower technology with 48% of backup system and 8 h of storage is the most attractive and optimum plant. It was also found from financial analysis that the LCOE can decreases by 13% with less interest rate and tax deductions.

A geographically resolved method to estimate levelized power plant costs with environmental externalities

In this analysis we developed and applied a geographically-resolved method to calculate the Levelized Cost of Electricity (LCOE) of new power plants on a county-by-county basis while including estimates of some environmental externalities. We calculated the LCOE for each county of the contiguous United States for 12 power plant technologies. The minimum LCOE option for each county varies based on local conditions, capital and fuel costs, environmental externalities, and resource availability. We considered ten scenarios that vary input assumptions. We present the results in a map format to facilitate comparisons by fuel, technology, and location. For our reference analysis, which includes a cost of $62/tCO2 for CO2 emissions natural gas combined cycle, wind, and nuclear are most often the lowest-LCOE option. While the average cost increases when internalizing the environmental externalities (carbon and air pollutants) is small for some technologies, the local cost differences are as high as $0.62/kWh for coal (under our reference analysis). These results display format, and online tools could serve as an educational tool for stakeholders when considering which technologies might or might not be a good fit for a given locality subject to system integration considerations.

On the Determination of Levelized Cost of Electricity of Wind Energy in the Coastal Areas of Bangladesh

Sustainable energy supply is the key to industrial, social and economic developments of any society. At the same time environment friendly sustainable energy supply is a burning issue nowadays. Among other renewable energy sources, due to geographical location, wind energy harvesting is more prospective in Bangladesh, especially in the coastal area of Bangladesh. In this work we studied the feasibility of harvesting wind energy in the coastal area of Bangladesh through the calculation of levelized cost of electricity (LCOE) at seven different locations. It is found that among seven locations the LCOE is approximately 5 BDT/kWh at Kuakata and St. Martin. We also investigated the effects of blade diameter and tower height on LCOE. It is found that the minimum LCOE may be achieved using blade diameter of 21.5 m and tower height has insignificant effects on the LCOE of wind energy for the coastal area of Bangladesh.

Cost Optimum Parameters for Rock Bed Thermal Storage at 550–600 °C: A Parametric Study

A major advantage of concentrating solar power (CSP) plants is their ability to store thermal energy at a cost far lower than that of current battery technologies. A recent techno-economic study found that packed rock bed thermal storage systems can be constructed with capital costs of less than 10 United States dollar (USD)/kWht, significantly cheaper than the two-tank molten salt thermal storage currently used in CSP plants (about 22–30 USD/kWht). However, little work has been published on determining optimum rock bed design parameters in the context of a CSP plant. The parametric study in this paper is intended to provide an overview of the bed flow lengths, particle sizes, mass fluxes, and Biot numbers which are expected to minimize the levelized cost of electricity (LCOE) for a central receiver CSP plant with a nominal storage capacity of 12 h. The findings show that rock diameters of 20–25 mm will usually give LCOE values at or very close to the minimum LCOE for the combined rock bed and CSP plant. Biot numbers between 0.1 and 0.2 are shown to have little influence on the position of the optimum (with respect to particle diameter) for all practical purposes. Optimum bed lengths are dependent on the Biot number and range between 3 and 10 m for a particle diameter of 20 mm.

ANN-based optimization of a parabolic trough solar thermal power plant

Design and optimization of a solar power plant are very complex and require many calculations, data and time. From this point of view, artificial neural network (ANN) models are desired options to determine techno-economic performances of this kind of plants. Therefore, the objective of this study is to investigate the feed-forward back-propagation learning algorithm with three different variants; Levenberge Marguardt (LM), Scaled Conjugate Gradient (SCG), and Pola-Ribiere Conjugate Gradient (CGP), used in the ANN to find the best approach for prediction and techno-economic optimization of parabolic trough solar thermal power plant (PTSTPP) integrated with fuel backup system and thermal energy storage. The obtained statistical parameters showed that LM algorithm with 38 neurons in a single hidden layer looks as the best ANN model to predict the annual power generation (PGnet) and levelized cost of electricity (LCOE) of the presented PTSTPP. Moreover, the obtained weights from this topology were used in the LCOE analysis for determining the optimum system design. It is therefore available to get a minimum LCOE of 8.88Cent/kWh from the new optimized plant when the plant characteristics are; 34°C and 850W/m2 for both design ambient temperature and solar radiation, 23m for row spacing, 1.7 for solar multiple, and 2.5h number of hours for the storage system.

Thermodynamic and economic optimizations of a waste heat to power plant driven by a subcritical ORC (Organic Rankine Cycle) using pure or zeotropic working fluid

This paper carried out the thermodynamic and economic optimizations of a subcritical ORC (Organic Rankine Cycle) using a pure or a zeotropic mixture working fluid. Two pure organic compounds, i.e. n-pentane and R245fa, and their mixtures with various concentrations were used as ORC working fluid for this study. Two optimizations, i.e. exergy efficiency maximization and LCOE (Levelized Cost of Electricity) minimization, were performed to find out the optimum operating conditions of the system and to determine the best working fluid from the studied media. Hot water at temperature of 150 °C and pressure of 5 bars was used to simulate the heat source medium. Whereas, cooling water at temperature of 20 °C was considered to be the heat sink medium. The mass flow rate of heat source is fixed at 50 kg/s for the optimizations. According to the results, the n-pentane-based ORC showed the highest maximized exergy efficiency (53.2%) and the lowest minimized LCOE (0.0863 $/kWh). Regarding ORCs using zeotropic working fluids, 0.05 and 0.1 R245fa mass fraction mixtures present the comparable economic features and thermodynamic performances to the system using n-pentane at minimum LCOE. The ORC using R245fa represents the least profitable system.

A Study on Solar Multiple for an Integrated Solar Combined Cycle System with Direct Steam Generation

This paper presents a study on optimizing the solar multiple for integrated solar combined cycle (ISCC) systems with direct steam generation (DSG). ISCC systems with different solar multiple values are studied, for which the performance is characterized under design-point and annual conditions. Based on the annual plant performance, levelized cost of electricity (LEC) with different solar multiples are determined and compared. Therefore an optimum solar field size, i.e. solar multiple, which gives the minimum LEC, for the ISCC plant could be obtained.

Cost and performance analysis of concentrating solar power systems with integrated latent thermal energy storage

Integrating TES (thermal energy storage) in a CSP (concentrating solar power) plant allows for continuous operation even during times when solar irradiation is not available, thus providing a reliable output to the grid. In the present study, the cost and performance models of an EPCM-TES (encapsulated phase change material thermal energy storage) system and HP-TES (latent thermal storage system with embedded heat pipes) are integrated with a CSP power tower system model utilizing Rankine and s-CO2 (supercritical carbon-dioxide) power conversion cycles, to investigate the dynamic TES-integrated plant performance. The influence of design parameters of the storage system on the performance of a 200 MWe capacity power tower CSP plant is studied to establish design envelopes that satisfy the U.S. Department of Energy SunShot Initiative requirements, which include a round-trip annualized exergetic efficiency greater than 95%, storage cost less than $15/kWht and LCE (levelized cost of electricity) less than 6 ¢/kWh. From the design windows, optimum designs of the storage system based on minimum LCE, maximum exergetic efficiency, and maximum capacity factor are reported and compared with the results of two-tank molten salt storage system. Overall, the study presents the first effort to construct and analyze LTES (latent thermal energy storage) integrated CSP plant performance that can help assess the impact, cost and performance of LTES systems on power generation from molten salt power tower CSP plant.