Total Cost Rate Research Articles

A novel cascade heat design for a geothermal energy-based combined power plant in integration with water electrolysis and ammonia synthesis processes: Comprehensive thermo-environ-economic analyses

The present paper introduces an innovative integrated system for simultaneous cooling, heating, power, and ammonia production utilizing geothermal energy. The novel configuration incorporates a geothermal-based single-flash power plant, a modified Kalina cycle, an organic Rankine cycle, an electrochemical unit, and an ammonia synthesis process. The Kalian cycle has undergone modifications aimed at enhancing its production capacity, while the electrochemical unit provides hydrogen for the ammonia synthesis process. The research encompasses a thorough assessment of the proposed system's potential with regard to thermodynamic, environmental impact, and economic considerations. Additionally, a parametric assessment is conducted using the flash pressure of the geothermal fluid and the proportion of unreacted gases to the ammonia synthesis reactor in order to analyze the performance variables of the system. The proposed system demonstrates a power generation capacity of 15513.18 kW, a heating load of 24880 kW, a cooling load of 11540 kW, and an ammonia production capacity of 0.282 kg/s. Moreover, the process exhibits irreversibility with a total value of 16977 kW. Consequently, the energy and exergy efficiencies amount to 34.55% and 57.17%, correspondingly. Besides, geothermal energy offers environmental benefits, as its non-polluting nature results in reduced CO2 emissions in comparison to biomass, coal-based, and hybrid energy systems. Eventually, the economic analysis demonstrates that the total cost rate and sum unit cost of products are 825 $/h and 9.57 $/GJ, respectively.

Multi-objective optimization and exergoeconomic analysis of a novel solar desalination system with absorption cooling

This paper presents a novel design for a solar-powered desalination system utilizing a single-effect absorption refrigeration cycle with a flat-plate solar collector. The NH3-H2O working fluid pair in the refrigeration subsystem produces chilled water while the rejected heat from the condenser drives a humidification-dehumidification (HDH) subsystem for freshwater generation. This cycle has been analyzed thermodynamically and exergetically to understand its key performance parameters. Furthermore, for a detailed examination and optimization, an exergoeconomic analysis was also conducted. Design parameters for this study include the tilt angle of the solar collector, Volume fraction of nanoparticles in the CuO nanofluid, Solar collector area, Base fluid mass flow rate in the collector, Mass flow rate of the strong solution, Absorber and condenser temperatures, Mass ratio and Humidifier effectiveness. The Objective functions used to evaluate the system, performance are the Cooling effect of performance (COP), Energy performance (EP), Exergy efficiency (μExe), and the Total product cost rate of the system (Ċp,Tot). The genetic algorithm optimization is employed to find the best system performance using two sets of three objective functions. The effectiveness of multi-objective optimization using LINMAP, TOPSIS, and Shannon Entropy methods is demonstrated. LINMAP and TOPSIS consistently achieved improvements in COP (32–42 %), exergy efficiency (33–48 %), and reduced total cost (89–90 %) compared to the base point, while Shannon Entropy offered slightly lower gains. These methods consistently identify superior system configurations, achieving significant improvements in performance while minimizing the total product cost rate.

Optimal Intermediate Pressure Investigation in a CO₂ Transcritical Distributed Compression Refrigeration Cycle{fr}Recherche sur la Pression Intermédiaire Optimale dans un Cycle de Réfrigération à Compression Distribuée Transcritique au CO₂

The CO2 transcritical distributed compression cycle proposal provides a novel approach for refrigerant cooling in traditional transcritical cycles. This paper employed an exhaustive search method to derive the correlation formula for the optimal intermediate pressure. From the perspectives of thermodynamic performance and economics, a comparative analysis was conducted between the cycle established under the optimal intermediate pressure obtained in this study, the cycle based on equal compression ratios in traditional two-stage compression cycles, and the cycle established using the optimal secondary compression ratio method based on low-pressure stage discharge pressure mentioned in previous literature study. The research results indicate that the system's COP calculated using the obtained optimal intermediate pressure correlation method can be improved by up to 7.26% and 5.32%, respectively, compared to the traditional and literature-based methods. The exergy loss with the optimal intermediate pressure method is less than with the other two methods. The entransy dissipation rate of the system obtained using the optimal intermediate pressure correlation method is 24.61% and 50.14% lower than that of the traditional and literature-based methods, respectively. The investment cost of the main components using the optimal intermediate pressure correlation method is about 5% higher than that of the traditional method and about 1% higher than that of the optimal pressure ratio method. However, the total annual cost rate of the system is the lowest. The research enriches and improves the theory of the CO₂ transcritical distributed compression cycle, thereby facilitating the advancement of practical applications based on this cycle theory.

4E analysis and optimization comparison of solar, biomass, geothermal, and wind power systems for green hydrogen-fueled SOFCs

Integrating renewable energies with hydrogen production via electrolysis and utilizing hydrogen as a fuel for solid oxide fuel cells (SOFCs) presents a synergistic approach towards sustainable energy generation. This coupling offers enhanced flexibility, allowing for efficient energy storage and distribution, thereby addressing intermittency issues associated with renewable sources. Additionally, the utilization of hydrogen in SOFCs enables high-efficiency power generation with reduced emissions, contributing to the transition towards a cleaner energy landscape. In the present study, four types of renewable energies, namely solar, biomass, geothermal, and wind, produce hydrogen by coupling power generation units and a proton exchange membrane electrolyzer (PEME). Then, the produced hydrogen is stored and used for later utilization in an SOFC subsystem. A 4E (energy, exergy, exergy-economic, and environmental) study is conducted for the proposed systems through a sensitivity study and design optimization. In the best output performance mode, the best exergy efficiency is obtained by the biomass-based system, which is equal to 9.40%, and the lowest values for total cost rate and unit cost of outputs are achievable by the geothermal-based system, with values of 27.72 $/h and 43.23 $/GJ.

Multi-criteria study and machine learning optimization of a novel heat integration for combined electricity, heat, and hydrogen production: Application of biogas-fueled S-Graz plant and biogas steam reforming

The current research introduces an environmentally friendly heat design method by employing biogas fuel, aiming to yield electricity, hydrogen, and heating load simultaneously. The proposed arrangement consists of a biogas-powered S-Graz plant and a biogas steam reforming cycle. Although methane-fueled S-Graz plants for multigeneration purposes have been studied in previous studies, research on employing biogas fuel to launch a S-Graz plant and integrating a biogas steam reforming cycle with such a plant has yet to be examined. The model is simulated using the engineering equation solver software, and the study includes thermodynamic, exergoeconomic, and sustainability assessments to show the potential of the suggested configuration. By conducting a sensitivity study, a machine learning optimization method within MATLAB is implemented to exhibit the final optimal solution for the proposed arrangement. This optimization uses artificial neural networks and a non-dominated sorting genetic algorithm-II algorithm in a triple-objective framework based on energy efficiency, sustainability index, and products’ specific cost. The optimization demonstrates that the mentioned objectives reach optimal values of 58.26 %, 4.56, and 15.56 $/GJ, respectively. Also, the optimal net output power and hydrogen production rate equal 5746 kW and 1.45 m3/s, respectively. Besides, the process determines the optimal exergy efficiency, total net present value, and payback period as 52.70 %, 50.3 M$, and 8.96 years, respectively. The total investment cost rate for this system also is found to be 219.8 $/h.

Extractive Distillation of Isobutyl Alcohol and Isobutyl Acetate Using Dimethyl Sulfoxide: Process Design and Intensification

AbstractWe have designed a separation process of isobutyl alcohol (52.0 mol%) and isobutyl acetate (48.0 mol%) mixture using conventional extractive distillation (ED) and extractive dividing‐wall column (E‐DWC) with the solvent dimethyl sulfoxide (DMSO). The binary mixture exhibits a minimum boiling azeotrope that is sensitive to pressure. Thermodynamic analyses have shown that the vacuum pressures work better compared to the atmospheric pressure when DMSO is the solvent. Based on the separation with a purity of 99.9 mol%, the E‐DWC process has resulted in 9.6 % and 4.8 % reductions in the total annual cost and CO2 emission rates, respectively, in comparison to the conventional method. After further intensification using the heat pump technique, the E‐DWC process with the solvent DMSO has provided more than 40.0 % reduction in energy consumption compared to the ED systems studied in the literature using the solvents butyl propionate and dimethylformamide.

Economic and technical optimization of a tri-generation setup integrating a partial evaporation Rankine cycle with an ejector-based refrigeration system using different solar collectors

Three collector types, namely parabolic trough solar collector (PTSC), linear Fresnel collector (LFC), and dish collector, are employed to drive a tri-generation configuration composed of a partial evaporation Rankine cycle (PERC), a hot water production unit (HWPU), and a cascade ejector-based compression refrigeration system (ECRS) for electricity, cooling, and heating production. The ECRS is integrated with the topping PERC through an absorption refrigeration system (ARS). Moreover, the collector is indirectly connected to the system by a storage tank to increase the operating hours of the system. The performance of the system is evaluated by thermodynamic and economic analysis. The three-objective optimization result is a testament to the fact that utilizing PTSC brings about the best performance of the system. The system exergy efficiency (ηex) in the case of PTSC is 8.1 % and 24.9 % higher than in the case of LFC and dish collector, respectively. The economic performance of the system in the case of PTSC is superior to that of the dish collector. Furthermore, the PTSC case results in a relatively similar economic performance to the LFC case. The system produces power, cooling, and heating at rates of 200.8 kW, 564.9 kW, and 795.7 kW in the optimum case of utilizing PTSC, respectively. Moreover, ηex, total cost rate (C˙tot), and specific cost of tri-generation (ctri) are obtained as 11.48 %, 204.7 $h−1, and 44.91 $GJ−1, correspondingly. The results indicate that ηex of the proposed layout in the case of PTSC is superior to a comparable tri-generation configuration introduced in the field by 2.78 % points.

Thermo-economic investigation and comparative multi-objective optimization of dual-pressure evaporation ORC using binary zeotropic mixtures as working fluids for geothermal energy application

This contribution performs an energy, exergy, and exergoeconomic (3E) analysis of a dual-pressure evaporation organic Rankine cycle system employing twenty different binary zeotropic mixtures as working fluids for power production from a geothermal field. To this end, the designed system is modeled, invoking the mass and energy conservation laws and the exergy and cost balance analyses. Specific Exergy Costing (SPECO) procedure is utilized to provide practical insights into the exergoeconomic aspect of the system. Comparative optimization based on the multi-objective genetic algorithm is accomplished for each mixture in order to simultaneously maximize the exergy efficiency and minimize the total cost rate using the design variables of pressure factor in low-pressure and high-pressure stages, mixture fraction, pinch point temperature differences in low-pressure and high-pressure heat exchangers, and degree of superheat in the high-pressure heat exchanger. In this regard, the Pareto frontiers are drawn for the system with all twenty different binary zeotropic mixtures. The optimal point for each mixture is obtained via the decision-making technique of LINMAP. Subsequently, the LINMAP is re-utilized to find the preferred mixture. The optimization results suggest the R123/C2Butene (96.89/3.11) mixture for this system as the optimum working fluid, considering a trade-off between a low-cost rate of $88.0651 per hr and a high exergy efficiency of 64.07 %. Finally, the exergy flow diagram is plotted to provide the exergy flow rate and the amount of exergy destruction in each segment of the system considering the optimal working fluid. In the proposed system, exergy destruction chiefly occurs within the low-pressure preheater with a value of 1061 kW, followed by the low-pressure turbine and condenser with magnitudes of about 669 kW and 266 kW, respectively.

Multi-criteria optimization next to a comparative analysis of a polygeneration layout based on a double-stage gas turbine cycle fueled by biomass and hydrogen

The significance and advantages of utilizing renewable energy sources are widely recognized. Upon examining past studies, it was revealed that there has been a lack of research on harnessing the waste energy from double-stage gas turbines powered by biomass-hydrogen hybrid fuel for polygeneration applications. Thus, a new configuration is proposed in the study for the multi-production of electricity, cooling, heating, and potable water. In the current research, a high-pressure turbine is driven by a combustion chamber fed by a biomass gasifier. Meanwhile, a low-pressure turbine is driven by a post-combustion chamber fed by hydrogen as fuel. The heat loss of the topping gas turbine cycle is recuperated by a supercritical Brayton cycle (SBC), a steam Rankine cycle (SRC), and a water heater. The waste heat of the supercritical Brayton cycle and steam Rankine cycle is recovered through an absorption refrigeration cycle and a thermoelectric generator, respectively. Thus, the heat loss of the topping system is completely recovered. The net power output of the gas turbine cycle is considered the electricity production of the system while the output power of the SBC and SRC is utilized in a reverse osmosis desalination system to produce potable water. The investigations conducted on the system are thermodynamic and exergy-economic assessments and three-objective optimization utilizing 5 gases (i.e., CO2, CO, Nitrogen, Air, and Helium) in the SBC. The final results reveal the superiority of Helium as the supercritical gas, bringing about an exergy efficiency () of 32.11%, a total cost rate () of 103 , a payback period (PP) of 0.159 years, and a specific cost of polygeneration () of 22.03 for the system. Although the levelized cost of products of the configuration is high due to the freshwater production, of the proposed system is higher than the previous systems based on a double-stage gas turbine cycle driven by biomass and hydrogen.

Thermoeconomic modeling of new energy system based on biogas upgrading to multigenerational purpose

The following article outlines an integrated approach toward the valorization of biogas for energy, chilled water, hot water, freshwater, and liquid carbon dioxide production. The suggested system includes a biogas upgrading unit with a biomethane-fueled burner, a Kalian cycle, an LNG regasification process, and a multi-effect desalination unit that can provide CO2, electricity, cooling, and heating. The new ideas in the proposed system include a cryogenic biogas upgrading process that can be used in many industrial settings, the production of liquid carbon dioxide through biogas upgrading, and the use of biomethane in the integrated combustion process. Furthermore, the grey wolf optimization technique is applied in various multi-objective optimization contexts to achieve optimal operating conditions and preferred performance outcomes. In this simulation, the generation of electricity reaches a value of 755 kW. Attached to it is a cooling load of about 5102 kW, with a heating load of 4725 kW, freshwater capacity about 1.33 kg/s, production rate of liquid CO2 at 0.58 kg/s, and natural gas at 3.1 kg/s. Thermodynamic results reveal that the proposed multigeneration performance scheme providently enhances energy and exergy efficiencies up to 59.82 % and 5.74 %, respectively, compared to the condition of a single product. The performed exergy analysis shows that the overall irreversibility of the suggested configuration is equal to 18,047 kW while about 42.6 % of this value is contributed from the heat exchanger E-104. Moreover, the CO2 emission intensity of the process can be kept as 0.35 kg/kWh. Cryogenic separation can obtain about 88 % of CO2 in biogas and turn it into its liquid phase. The performed economic assessment has resulted in the following total cost rate as well as cost per unit exergy: 321.38 $/h and 83.06 $/GJ, respectively. Under optimal conditions, an exergy efficiency of 13.40 % and a net power output of 2034.39 kW are attained.

4E analysis of novel waste heat-driven combined cooling and power (CCP) systems based on modified Kalina-ejector refrigeration cycles

Global warming and environmental pollution are becoming increasingly severe problems due to the excessive use of fossil fuels. Recovering and utilizing waste heat from different energy systems can considered a sustainable solution to this destructive trend. This study proposes two modified Kalina cycle structures that use ejector refrigeration for combined cooling and power (CCP) generation in low-temperature waste heat. While to recover energy from a lean ammonia solution uses a two-phase expander. Thermodynamic analysis shows that the modified Kalina cycles E and F operate with a thermal efficiency of 0.3066 and 0.2557, respectively, representing a significant improvement of more than 123% and 86%, respectively, compared to the base cycle. Also, the exergy efficiency of the improved configurations E and F has been calculated as 0.083 and 0.089, respectively, showing an improvement of 53.8% and 64.8%, respectively, compared to the base cycle. The exergoeconomic analysis also revealed that the total capital cost rate for improved cycles E and F is estimated at 2.62 and 2.76 $/h, respectively. In addition, from an environmental perspective, the improved Kalina cycle F has proven to have a more eco-friendly performance with a pollution index of 0.2281 mPts/s. Moreover, a parametric study is conducted to investigate and analyze the effect of changes in significant performance parameters such as ammonia concentration, evaporator temperature, turbine inlet temperature and pressure, and turbine back-pressure for both presented modified cycles.

Thermo-environmental analysis of a renewable Allam Cycle for generating higher power and less CO2 emissions

Although CO2 emissions from burning fossil fuels have caused numerous environmental problems, the utilization of oxy-fuel cycles has proven to be an effective method for generating more power while minimizing CO2 emissions. In this study, an innovative power generation system was presented that integrates renewable energies (solar and wind) with a small-scale oxy-fuel cycle (Allam Cycle). The system underwent modeling, simulation, and optimization from energy, exergy, exergoeconomic, and environmental perspectives. Generating higher power and emitting lower CO2 emissions compared to conventional gas turbines was the main goal of this study. Additionally, to present results meaningfully, comparisons were made between two different weather conditions: St. Petersburg in Russia (cold climate) and Tehran in Iran (normal climate). In this regard, dynamic analysis was performed using TRNSYS and Engineering Equation Solver (EES) tools. Furthermore, a multi-objective optimization was conducted using the TOPSIS multi-criteria method on functional parameters. The optimization results revealed that the maximum energy efficiency and minimum total cost rate were achieved at 75 % for Tehran and 1.84 $/h for St. Petersburg. Providing power for internal components, the highest power sold to the grid was reported to be 8365 kWh in December in St. Petersburg and 9646 kWh in May in Tehran. Additionally, the flat plate collector (FPC) demonstrated maximum efficiency and stored heat of 36 % in Tehran and 2.25 kWh in St. Petersburg, respectively. Ultimately, the results of pollutant emissions indicated that the Allam Cycle achieved a significant CO2 reduction compared to a conventional gas turbine, with a reduction ratio of 117 times in St. Petersburg and 119 times in Tehran.

Optimal 4E design and innovative R-curve approach for a gas-solar- biological waste polygeneration system for power, freshwater, and methanol production

BackgroundCogeneration power plants traditionally rely on fossil fuels to produce stable power and heat. However, increasing energy demand and population growth have intensified the emission of biological pollutants due to fossil fuel use. The Global Alliance on Health and Pollution advocates for integrating renewable energy sources to mitigate these issues. ObjectivesThis study aims to evaluate the integration of a solar-biomass polygeneration system with a hybrid solar-waste-fossil fuel cogeneration system. The goal is to analyze the system from technical, economic, and environmental perspectives, focusing on optimizing energy demand and minimizing environmental impact. MethodsTo assess energy demand and supply, the R-curve methodology was applied to the hybrid cogeneration system, with a specific focus on solar and biomass renewable energies. Various scenarios were analyzed, including total annual costs, pollutant emissions, water footprint, and overall environmental impact based on life cycle assessment. The study examined and compared the performance of three types of biomass waste (Municipal solid waste, mixed paper waste, and date palm waste). Multi-objective optimization was performed using artificial intelligence and machine learning techniques, employing four meta-heuristic algorithms. The conditions generated by each algorithm were analyzed and compared. ResultsMunicipal solid waste, being the most readily available fuel, provided the most favorable economic conditions for the system. Environmentally, municipal solid waste ranked in the middle compared to other fuels. Among the optimization algorithms, the Salps swarm algorithm proved to be the most efficient in terms of calculation time and system efficiency improvements. The optimization improved net power generation by 5.25 %, overall energy efficiency by 16.27 %, total cost rate by 10.19 %, and total environmental impact rate by 14.02 %. ConclusionThe integrated system's performance was analyzed across different climatic change throughout the year. The multi-objective Salps swarm algorithm optimization demonstrated significant benefits in enhancing system efficiency and reducing costs and environmental impacts.

Optimizing trigeneration energy systems: Biogas-centric methanol production via direct CO2 hydrogenation with advanced integration of PEM electrolyzer and LNG cold technology

Biogas, a sustainable alternative to fossil fuels, addresses issues of non-renewability and accessibility. Its structural similarity to fossil fuels makes it a potent option for energy systems. With this in mind, this paper discusses a novel trigeneration system that utilizes biogas and Liquefied natural gas cooling to produce methanol, electricity, cold water, hot water, oxygen, and natural gas. The system integrates various components such as a biogas burner, Kalina cycle, organic Rankine cycle, liquefied natural gas liquid gasification cycle, proton exchange membrane electrolyzer, and methanol synthesis unit. Simulation via Aspen HYSYS software includes an analysis of energy, exergy, economic, and environmental aspects. Efficiency assessment in single generation, cogeneration, trigeneration, and chemical trigeneration modes concludes chemical trigeneration as most efficient, with the proton exchange membrane electrolyzer being the most efficient subsystem. Key variables like Kalina cycle evaporator temperature, gas flow rate to the methanol reactor, and organic Rankine cycle working fluid pressure are assessed. Predictions on thermodynamic, environmental, and economic behaviors, along with their fluctuations, are made. Using a thermoeconomic approach, the economic analysis determines an exergy unit cost of 59.79 $/GJ and a total cost rate of 2764 $/h. Overall, this work presents a novel and efficient chemical trigeneration system that utilizes biogas and LNG cooling to produce multiple products.

Optimized multi-criteria performance of a poly-generation layout including a Stirling engine and a supercritical Brayton cycle using biogas and methane as two potential fuels of a topping gas turbine cycle

The combination of a supercritical Brayton cycle, an absorption chiller, a Stirling engine, a reverse osmosis desalination system, and a proton exchange membrane electrolyzer is investigated for waste heat recovery of a topping gas turbine cycle. The required electricity for hydrogen and freshwater production is supplied by the Stirling engine and supercritical Brayton cycle, respectively. In addition, the output power is provided by the gas turbine cycle, and the exiting cold stream of the Stirling engine is considered hot water for domestic utilization. A comparison is made between biogas and pure methane as two possible fuels for the system. Energy and exergy analyses, economic analysis using the specific exergy costing approach, and environmental analysis considering the carbon dioxide emissions are employed in the study. The three-objective optimization of the configuration discloses an exergy efficiency (ηex) of 39.49 % and 39.85 % in the cases of biogas and methane, respectively. The proposed system can improve ηex by 6.18 % points compared to the stand-alone GTC. The specific cost of poly-generation (cpoly) and the total cost rate (C˙tot) are obtained as 25.92 $GJ−1 and 249.5 $h−1 in the biogas mode, while these values are calculated as 36.75 $GJ−1 and 336.7 $h−1 in the methane case. The environmental cost rate (C˙env) of the system is 24.78 $h−1 in the case of biogas and 17.47 $h−1 in the methane mode. The results confirm the superiority of the methane case from the environmental viewpoint over biogas. However, the low values of cpoly and C˙tot in the biogas case indicate that biogas is superior to methane from a general standpoint. The utilization of the present setup for waste heat recovery of biogas-driven GTCs is recommended due to the higher ηex than the previous layouts.

Coupling a thermoelectric-based heat recovery and hydrogen production unit with a SOFC-powered multi-generation structure; an in-depth economic machine learning-driven analysis

This study presents a comprehensive technical, environmental, and economic analysis of a thermal power plant utilizing solid oxide fuel cells (SOFC) to meet urban demands for electrical power, fresh water, and hydrogen. The integrated system includes SOFC with anode and cathode recycling, multi-effect desalination, a power generation cycle with a heat recovery unit using a thermoelectric generator, and a hydrogen compression unit. A detailed parametric analysis was conducted to identify optimal conditions for key outputs such as total cost rate and exergy efficiency, employing genetic algorithms and artificial neural networks. According to the economic evaluation, the SOFC stack accounts for 65.11 % of total costs at 139.8 $/h, with the inverter contributing 11.9 %. The environmental analysis shows that the proposed system emits the least CO2 per energy unit compared to SOFC/GT and SOFC/GT/RC systems. The parametric study indicates that increasing the pressure ratio enhances the output power of the SOFC and the production of the gas turbine. However, this also leads to higher compressor consumption, thereby reducing net power. Furthermore, increasing the current density results in greater production of electricity, hydrogen, and freshwater, while also raising the exhaust gas temperature, which aids in the desalination process. The optimization results show an exergy efficiency of 61.38 % and a total cost rate of 132.9 $/h, with artificial neural networks reducing optimization time from 124 h to 14 min.

Assessing the thermoeconomic performance of a solar-powered trigeneration system with an upgraded transcritical carbon dioxide unit

With the intervention of the industry in every aspect of human lifestyle on the one hand, and the prompt reduction in fossil fuel and their harms to the environment, including global warming, on the flip side, the importance of renewable sources of energy has been revealed more than ever. The presented study attempted to investigate a new configuration for a trigeneration configuration based on a solar renewable source. The proposed system comprises a parabolic trough solar collector segment to drive a transcritical carbon dioxide power and refrigeration subsystem, a dual-pressure organic Rankine cycle, and a thermal vapor compression process combined with a multi-effect desalination unit. The suggested configuration is carefully inspected from thermodynamic and economic perspectives, encompassing an analysis of a certain condition and a detailed parametric evaluation. Four decision parameters are employed for the parametric evaluation, in conjunction with two scenarios from a multi-objective particle swarm optimization combined with a linear programming method for multidimensional preference analysis as a decision-maker. The examination outputs bring out a net output power of 12.147 MW, a 7.707 MW cooling load, a 4.448 kg/s freshwater, and energetic and exergetic efficiencies of 15.286 % and 10.192 %, respectively. Moreover, examining the system's performance from an economic perspective reveals a total product cost rate of 954.249 $/h, leading to a 4.694-year payback period. This study optimizes energy usage and minimizes waste, offering industrial applications such as reducing fossil fuel dependence and lowering greenhouse gas emissions. It supports sustainable development and facilitates the global transition to cleaner energy sources.

Multi-objective optimization and long-time simulation of a multi-borehole ground heat exchanger system

Multi-objective optimization and CFD simulation are conducted to optimize the design of a multi-borehole ground heat exchanger (GHE) system and assess its long-time performance. The multi-objective optimization is performed to minimize the entropy generation number (EGN) and total cost rate by using various evolutionary algorithms, including NSGA-II, GDE-3, MOEA/D, PESA-II, SPEA-II, and SMPSO. NSGA-II and GDE-3 algorithms perform best in obtaining Pareto optimal solutions. Three prominent points on the NSGA-II Pareto frontier, representing the results of single-objective thermodynamic, single-objective economic, and multi-objective optimizations, are simulated in three dimensions over three months. The trends of EGN variations extracted from the transient CFD simulation agree well with those from the steady analytical model. The EGN obtained from multi-objective optimization is 58.8% lower than the EGN obtained using single-objective economic optimization and 1.9 times higher than that calculated from single-objective thermodynamic optimization. Likewise, the total cost rate obtained from multi-objective optimization is 64.4% lower than the value obtained from single-objective thermodynamic optimization and four times higher than that calculated using single-objective economic optimization. The proposed optimization approach can be reliably applied to improve the design of multi-borehole GHE systems.

Techno-economic analysis and optimization of a binary geothermal combined district heat and power plant for Puga Valley, India

This article investigates the energy, exergy, and economic performance of a Puga Valley-specific binary geothermal combined district heat and power plant, taking into account geotechnical data and related cost functions. The power plant uses an organic Rankine cycle (ORC) with R123 as the working fluid, utilizing waste heat for district heating to enhance efficiency. Variations in operating and design parameters such as geothermal fluid flow rate, temperature, and ORC temperature of the evaporator and condenser are found to have significant effects on the overall performance of the system and cost rate. A multi-objective grey wolf optimization technique based on artificial neural networks has been used to determine the ideal values of the above-mentioned parameters. The optimization study revealed a Pareto optimal curve with overall exergy efficiency and total cost rate as objective functions from which the optimal point was identified using the technique for order preference by similarity to the ideal solution (TOPSIS) method. While operating the proposed CHP plant at TOPSIS optimal point, the plant delivers a net electrical output of 1.08 MW alongside 4.19 MW of thermal energy, resulting in a total cost rate of 33.84 USD/h, with energy and exergy efficiencies peaking at 32.26 % and 36.8 %, respectively. The exergy analysis at the optimal point also revealed a notable reduction of 550 kW in the total exergy destruction rate compared with the base-case scenario. Furthermore, the design requirements of a 5 MW net power output CHP plant for effective recovery of the Puga Valley geothermal resource are discussed.

Exergy, exergoeconomic optimization and exergoenvironmental analysis of a hybrid solar, wind, and marine energy power system: A strategy for carbon-free electrical production

In this research, aligned with global policies aimed at reducing CO2 emissions from traditional power plants, we developed a holistic energy system utilizing solar, wind, and ocean thermal energy sources, tailored to regions optimal for ocean thermal energy conversion (OTEC). The selected site, characterized by favorable wind and solar conditions close to areas with high OTEC potential, is designed to meet the electricity needs of a coastal community. The system's core components include an Organic Rankine Cycle, turbines, thermoelectric elements, pumps, a heat exchanger, a wind turbine, and a solar collector. A detailed system analysis and thermodynamic evaluation based on thermodynamic principles were carried out using the Engineering Equation Solver (EES) software. Key factors such as wind speed, solar radiation, and collector area were critical in determining system performance. To enhance the system's effectiveness, we conducted a comprehensive comparison of optimization algorithms, incorporating the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and utilizing a Pareto front for value optimization. This approach significantly outperformed other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA) in terms of system efficiency and cost-effectiveness. The developed system achieved an exergy efficiency of 14.46 % and a cost rate of $74.98 per hour, demonstrating its suitability for its intended functions. Moreover, exergoenvironmental evaluation was conducted for the proposed plant. The findings revealed that key component HEX has a high exergoenvironmental factor due to their use of hot water, which has zero unit exergoenvironmental impact. Additionally, pumps demonstrated a zero exergoenvironmental impact factor, indicating negligible component-related environmental impacts. Sensitivity analysis further evaluated critical performance parameters, revealing that increases in solar irradiation lead to decreased total system cost rates, while higher turbine temperatures resulted in a remarkable 14.08 % reduction in the system's cost rate. These results underscore the economic viability of operating the system at higher temperatures and strengthen the argument for its adoption from a financial perspective.