Multi-generation Energy System Research Articles

Performance analysis on combined energy supply system based on Carnot battery with packed-bed thermal energy storage

Pumped-thermal electricity storage (PTES) is a promising energy storage technology with high-efficiency, energy density, and versatility of installation conditions. In this study, a 20 kW/5 h phase change packed-bed thermal energy storage experimental system is established and employed to validate the accuracy of thermal energy storage (TES) component within the broader PTES system. Moreover, a novel combined system based on latent TES is proposed, incorporating Joule-Brayton and organic Rankine cycle-based subsystems for supplying cold, heat, electricity, and hydrogen. Operational strategies are also explored to optimize the multifunctional capabilities of the system. The thermal energy density of the system, when phase change materials (PCMs) are used instead of sensible heat storage materials, can be improved from 167.85 kWh/m3 to 272.58 kWh/m3. Proton exchange membrane electrolyzer cycle (PEMEC) is coupled into the Carnot battery system, and a comprehensive analysis of the system's performance is conducted. With the charging time of 5 h, the energy performance of the multi-generation system (EPMG) can be reached up to 143 % and 146 % in combined cooling, heating, and power (CCHP) and multi-generation energy system (MGES) modes, respectively. The MGES mode is made 3.44 % more exergy efficient than the CCHP mode as a result of the ingenious coupling of the hydrogen production process with the power generation process and heating/cooling processes. The system in one charging/discharging process has the capability to generate 240.86 kg of hydrogen, 34.82 MWh of heat, 12.97 MWh of cold, and 40.90 MWh of electricity.

Sustainable biomass-driven heating, Bio-hydrogen, and power production scheme with desalination unit

In this study, a multi-generation energy system is modeled for the purpose of simultaneous producing distilled water as well as biofuels, electrical power, and thermal energy from wood chip biomass. The system is triggered by a gas turbine cycle with two different agents of steam and air. The system performance is evaluated by changing the gas turbine cycle working fluid and their performances are compared in details. The research findings indicate that the air-powered system demonstrated an efficiency of 67.38 %, surpassing the steam-powered system which exhibited a slightly lower efficiency rate of 67.17 %. The results indicated that the air-driven system displayed superior emission characteristics in comparison to the steam-driven system. The air-based system was found to release 510.3 g/kWh of carbon dioxide, whereas the steam-based system exhibited a marginally higher emission rate of 511.9 g/kWh. The study's results indicated that the air-powered system exhibited superior performance in comparison to the steam-powered system. The study illustrated that the integration of wood chip biomass into energy systems offers an environmentally sustainable and economically viable solution to address the increasing need for clean technologies.

Advancing energy transition with novel biomass-solar based multigeneration energy system using hydrogen and storage options for sustainable cities

An integrated energy system is designed to produce various useful products, such as hydrogen, electricity, heat and cooling. This integrated plant utilizes various subsystems; solar power system, biomass energy system, steam Rankine cycle (SRC), Brayton cycle (BC), organic Rankine cycle (ORC), double-effect absorption system (DEAS), reverse osmosis system, and sonohydrogen production unit. The specific energetic, exergetic, economic and environmental impact assessment studies are carried out to evaluate the system's performance and sustainability. The engineering equation solver (EES) is used for these studies. The energy efficiencies for the BC, ORC and SRC are recorded as 29.69 %, 10.49 %, and 30 %, respectively. In regard to exergy efficiency, the BC, ORC and SRC achieve the following: 46.74 %, 62.73 %, and 53.43 %, respectively. Furthermore, the DEAS attains energetic and exergetic COPs of 1.67 and 0.65, respectively. Additionally, the overall system's energy and exergy efficiencies are found to be 37.68 % and 71.25 %, respectively. The results from the thermal energy storage system indicate that the heat production begins at 7:00 a.m., and the charging of the storage unit commences two hours after and continues until 5:00 p.m., in coinciding with the availability of sunlight. The economic analysis demonstrates that with an initial investment of $53.80 million, the integrated multigeneration system achieves a net present value ranging from $6.87 million to $173.4 million across different hydrogen selling prices, from $7000 to $13,000 per ton up to 2054.

Exergoeconomic and exergoenvironmental analyzes of a new biomass/solar-driven multigeneration energy system: An effort to maximum utilization of the waste heat of gasification process

In addition to improving the sustainability and thermodynamic efficiencies of an energy conversion system, a solar/biomass-driven integrated energy system can also reduce environmental impacts. The current work presents a detailed evaluation (thermodynamic simulation and exergoenvironmental and exergoeconomic analyzes) of a solar/biomass-powered multigeneration energy system (MGES). Accordingly, four units were considered for electric power generation. A linear Fresnel concentrator (LFC)-driven solar farm, a municipal solid waste (MSW) gasification cycle, an alkaline water electrolyzer (AWE) unit (to produce hydrogen gas), and a multi effect desalination (MED)-based Seawater desalination cycle are also considered in the MGES. A multi-objective optimization (regarding the technical, cost, and environmental objective functions) was also developed for the offered MGES. The proposed configuration for the MGES has a new components process that had not been reported in the publications. The power generation level was improved by utilizing the energy available in waste heat in the different downstream units. The offered MGES can generate 154.1 MW of electrical power, ∼ 280 kg per day of hydrogen gas, and 265.4 m3/h of fresh water. Meantime, the offered MGES can 38.8 % and 32.2 % efficient in terms of energy and exergy, respectively. Besides, the LCOE value and the environmental impacts index for the offered MGES were approximately 3.82 USD/GJ and 0.545 Pts/GJ, respectively. Also, raising the syngas temperature at the inlet of the combustion chamber can be a reasonable decision from the exergetic, economic and (especially) environmental standpoints.

A machine learning study on a municipal solid waste-to-energy system for environmental sustainability in a multi-generation energy system for hydrogen production

Municipal solid waste (MSW)-to-energy systems have gained significant attention in recent years for their potential to produce renewable energy from waste. These systems involve the conversion of MSW into electricity, heat or fuel. One of the most promising applications of MSW-to-energy systems is the production of hydrogen, which is considered a clean and sustainable fuel. Machine learning algorithms have the potential to revolutionize the way MSW-to-energy systems are managed. The integration of machine learning into MSW-to-energy systems has the potential to significantly improve the sustainability and profitability of this industry. In this study, a novel integrated MSW-to-energy system is modeled to produce hydrogen, power, and oxygen and with capacities of heating water and air. Hydrogen production, power production, oxygen storage, hot water, hot air, and system emission are predicted using machine learning algorithms based on regression models with high validity and R2 values more than 99.8% having errors smaller than 1%. The reduced regression models are developed by eliminating the insignificant variables from the full algorithms using the analysis of variance. The findings reveal high accuracy for the reduced regression models while their errors slightly decrease to 2%. This suggests that the machine learning algorithms can also be used as an effective tool to further improve MSW-to-energy systems.

Environmental sustainability by an integrated system based on municipal solid waste fluidized bed gasification using energy, exergy, and environmental analyses

As an eco-friendly method of waste disposal, municipal solid waste (MSW)-to-multi-generation energy systems based on gasification reduces the amount of waste sent to landfills, generates clean energy that can be used to power homes and businesses, reduces our reliance on fossil fuels, and helps to reduce greenhouse gas emissions. In this study, a novel system is developed based on MSW gasification by combining a fluidized bed gasifier, a solid oxide fuel cell (SOFC), and a heat recovery to produce heat and power. In-depth research is done on the power output, heating capacity, energy and exergy efficiencies, and emissions of this innovative combined heating and power system. Electrical and exergy efficiencies of the system are improved with the steam to MSW ratio from 40.6 % to 41.4 % and from 36.4 % to 37.0 %, respectively, and the emission is reduced. Increasing utilization factor enhances electrical (from 37.2 % to 44.4 %) and exergy (from 33.4 % to 39.6 %) efficiencies and declines the emission (from 955.2 to 800.7 kg/MW.s). Decreasing current density and increasing SOFC temperature boost the system performance from energy, exergy, and environmental viewpoints. The future of multi-generation energy systems based on MSW gasification looks bright, as they offer a sustainable way to manage waste while meeting the growing demand for clean energy.

Optimization of an eco-friendly municipal solid waste-to-multi-generation energy scheme integrated by MSW gasification and HSOFC: Regression analysis and machine learning study

The utilization of regression models and machine learning algorithms in waste-to-energy systems has the potential to enhance the efficiency and effectiveness of these systems. The predictive capacity to ascertain energy production and optimize operational methodologies can contribute to increased efficacy and proficiency of waste-to-energy systems, thereby diminishing waste generation and fostering the generation of sustainable energy. The gasification technology for Municipal Solid Waste (MSW) provides a multitude of environmental advantages and holds significant importance in safeguarding the environment. This approach entails the use of sustainable and environmentally friendly practices in waste management, which effectively mitigates the release of greenhouse gases while also preserving finite natural resources. Considering the plethora of benefits it offers, it is anticipated that the utilization of MSW gasification as a waste management technique will experience a noticeable surge in popularity in the near future. This study presents a modeling approach for a multi-generation energy system that utilizes municipal solid waste (MSW) gasification technology integrated with a proton conducting solid oxide fuel cell (SOFC). Machine learning algorithms have been devised for the purposes of predicting and optimizing the performance of systems. The heating generation, power generation, electrical efficiency, exergy efficiency, and emission levels of the system have been accurately predicted, exhibiting a substantial level of precision as indicated by R2 values predominantly exceeding 94%. The optimization procedure reveals that the optimal solutions entail a heating generation rate of 854.2 g/s, power generation of 323.6 kW, an electrical efficiency of 40.3%, an exergy efficiency of 36.1%, and an emission rate of 893.5 g/kWs

Multi-criteria thermo-economic analysis of solar-driven tri-generation systems equipped with organic Rankine cycle and bottoming absorption refrigeration and Kalina cycles

Optimal thermo-economic integration of renewable energy sources with multi-generation energy systems is a prime research topic today. The present study proposes a multi-criteria evaluation method of such integration, based on combined heating and power (CHP), and combined cooling and power (CCP) scenarios, for three different solar intensities. Three novel solar-driven tri-generation systems are selected. They include different organic Rankine cycle (ORC) architectures and a Kalina cycle system (KCS) and a double-effect absorption refrigeration cycle as bottoming cycles. Evaluation of the tri-generation systems, both with and without the KCS system, indicates a performance improvement of up to 23% in various thermoeconomic characteristics when the KCS system is present. Selection of the suitable tri-generation system for each condition and optimization of the working fluid are carried out based on a multi-attribute decision-making method. P-xylene is found as the optimal organic working fluid for ORC and ORC (ORC integrated with internal heat exchanger) based systems, and benzene for the regenerative ORC-based system in both CHP and CCP scenarios. Multi-criteria analysis shows that ORC-based system outperforms other systems with net outranking flow of 0.44 (0.39) for CHP (CCP) application. The optimal configuration gives 95.6 M$ and 1.99 years for net present value and dynamic payback period, and 83.03% and 34.55% for energy and exergy efficiencies, respectively.

Environmental sustainability by a comprehensive environmental and energy comparison analysis in a wood chip and rice straw biomass-fueled multi-generation energy system

Biomass-based energy systems are gaining popularity as a clean and renewable source of energy, and have the potential to be a major contributor to the transition towards a sustainable energy future. In this regard, a novel multi-generation energy system is developed based on the biomass combustion. Wood chip and rice straw biomass is combusted with air agent and triggers an integrated system comprises a gas turbine cycle, a proton exchange membrane electrolyzer, a supercritical carbon dioxide Brayton cycle, and a humidification-dehumidification desalination system. The performances of wood chip and rice straw in triggering the system are compared from environmental and energy indicators viewpoints. The system fueled by wood chip emits lower carbon dioxide emission compared to the system fueled by rice straw (8.294 g/kWh compared to 10.41 g/kWh). However, the rice straw-fueled system results in higher efficiency than the wood chip-fueled system (69.9% compared to 69.1%). The system fueled by wood chip produces 2.68 kg/h of hydrogen while this value if 1.96 kg/h for the system fueled by rice straw. The research validated the possibility of utilizing energy systems that incorporate wood chip and rice straw biomass across various generations and showed the superiority of the wood chip in most cases.

Thermal investigation and bi-objective optimization of a multi-product system with concentrated solar system

The current research is conducted with the aim of investigating a multi-generation energy system (MGS) for electricity, hydrogen, heating, cooling and hot water production using SRC, Kalina cycle and proton exchange membrane (PEM) electrolysis as the main subsystems. The thermodynamic analysis namely energy, exergy, and exergo-economic examination carried out. Analysis for each component is done after thermodynamic modeling. The exergy investigation showed that regenerator 2, vapor generator and condenser had the highest exergy destruction rate, respectively. A comparison was made between the current work and the basic system, and according to the results obtained, the system's ability to produce electricity, cooling, heating and hydrogen are calculated as 782 kW, 173.2 kW, 2265 kW and 0.01613 mol/day, respectively. Also, the energy and exergy efficiency of the proposed system increased by 3.13% and 5.37%, respectively. The optimization based on PSO method was carried out. The results of PSO optimization represented that in the case exergy destruction and exergy efficiency will be the optimization target these two outputs can reach the value of 2208 kW and 9.84%, while optimization based on exergy efficiency and production cost rate will lead to 9.86% and 166.6 $/h.

Techno-environmental assessment and machine learning-based optimization of a novel dual-source multi-generation energy system

The utilization of high-temperature hybrid energy systems has a vital and promising role in reducing environmental pollutants and coping with climate change. So, in the present research, a dual-source multigeneration energy system composed of a gas turbine, a supercritical carbon dioxide recompression Brayton cycle, an organic Rankine cycle, an absorption refrigeration system, and a reverse osmosis desalination unit is designed and analyzed from thermodynamic, environmental and economic perspectives. The system supplies power with a stable load to follow the changes in the demand side which is important for off-grid distributed energy systems. The dual-source operation of the system makes it possible to generate sustainable electricity leading to less utilization of fossil fuels in the gas turbine subsystem and reduction in environmental pollution, and furthermore, malfunctioning of a subsystem will not lead to the failure of the entire plant. Three multi-objective optimizations with different objective functions are accomplished using artificial neural network from data learning and genetic and Greywolf algorithms to obtain the best-operating conditions. Under the base conditions, for the total input energy of 699 MW to the entire system, the energy and exergy efficiencies, the unit exergy cost of products, the carbon dioxide emission index, and the payback period, respectively, were found to be 45 %, 54 %, 15.3 $/GJ, 112.2 kg/MWh, and 7.2 years. The net output power of the proposed system was calculated as 288.2 MW. A sensitivity analysis revealed that with a change in the pressure ratio of the supercritical carbon dioxide cycle, the net generated power and overall efficiency take maximum values of 293.9 MW while the unit exergy cost of products and carbon dioxide emission index take minimum values of 15.3 $/GJ and 110.1 kg/MWh, respectively. Furthermore, increasing the pressure ratio of the gas turbine leads to maximum values of 45 % and 54 % in overall energy and exergy efficiencies, respectively.

Exergo-economic and exergo-environmental evaluations and multi-objective optimization of a novel multi-generation plant powered by geothermal energy

An innovative multi-generation energy system is proposed to generate simultaneous power, drinking water, cooling, heating, and H2. The aimed plant comprised of an absorption chiller, a heat pump unit, a reverse osmoses unit, a double flash cycle, and a proton exchange membrane. The devised system is surveyed comprehensively based on the thermodynamic, thermo-economic, and exergoenvironmental indicators for offering an in-depth assessment of the plant. Besides, multi-objective optimization has been employed in the proposed system. The net proportions of output work, unit cost, thermal and exergetic efficiencies, and H2, and purified water production of the system are 99.25 kW, 124 $/GJ, 24.4%, 32.1%, 1.218 kg/h, and 0.9662 kg/s, separately. The outcomes related to thermodynamic and thermo-economic evaluations demonstrate that the greatest amount of total cost rate occurred in the first employed turbine. Owing to the findings of the parametric study, by increasing geothermal temperature, exergoenvironmental parameters are reduced, and with increasing the pressure of FT1, cooling load and energetic efficiency increase while SUCP, net output work, and exergetic efficiency decrease dramatically.

Thermodynamic and thermoeconomic assessment of hydrogen production employing an efficient multigeneration system based on rich fuel combustion

The recent development of distributed multigeneration energy systems is changing the focus of producing different energy vectors from large centralized plants to local energy systems. A novel multigeneration system is designed in the present work to supply domestic energy demands of power, hydrogen and heating. The proposed system mainly consists of a supercritical CO2 cycle, a gas turbine equipped with a rich-fueled combustion chamber, a membrane for hydrogen separation and a water-gas shift reactor. Feeding the combustion chamber with a rich fuel mixture leads to the availability of a significant hydrogen amount in the products, which can be separated and stored. Thermodynamic analysis revealed that the highest irreversibility belongs to the combustion chamber, which is responsible for almost half of total exergy destruction. The cost of the produced hydrogen is estimated to be 2.2–6.8 $/kg for a natural gas price of 9.51 $/GJ and equivalence ratios of 2.9–1.65. The overall energy and exergy efficiencies, hydrogen production rate, total system cost rate, and cost of produced electricity are found to be 75.1%, 58.9%, 40.6 kg/h, 222 $/h and 51 $/MWh, respectively, assuming an equivalence ratio of 2.

Optimal management with demand response program for a multi-generation energy system

• Methodology for the simultaneous optimization of load shifting and MES management. • Optimal dispatch strategy of real-world load profiles over one year. • Primary energy consumption reduction of about 1% compared to baseline scenario. • Operational cost reduction of about 8% compared to baseline scenario. The optimal management of a multi-generation energy system is one of the challenges that an ever-growing energy demand requires to deal with. To tackle this urgent issue, this paper presents a methodology to identify the optimal dispatching strategy for a multi-generation energy system. The so-called time-of-use rate is one of the main time-based demand response programs which allows shifting the critical loads from a time interval to another (e.g., shifting electricity use to lower-priced hours of a day when demand is lower). Thus, the time-of-use rate is adopted in this paper in order to add flexibility to the management of the multi-generation energy system and thus optimize the interaction between energy production and user demand. In this paper, the goal is the minimization of primary energy consumption or operating costs. Whatever the considered objective function, the goal can be achieved by simultaneously acting on two levels, i.e., optimization of the demand response program and identification of the most favorable management strategy of the multi-generation energy system. A mixed-integer linear programming algorithm is employed to identify the optimal strategy. The case study considers an entire year of operation with a time step of one hour, by means of a real-world load profile. The proposed methodology allows both saving primary energy (more than 1%) and reducing operating costs (more than 8%). The proposed methodology demonstrates that the implementation of a demand response program within the optimal strategy for energy dispatch allows both saving primary energy and reducing operating costs with respect to the baseline scenario (i.e., no load shifting). The reduction of both primary energy consumption and operational costs is higher in the scenario with higher load shifting (in this paper, 30% of the daily electrical energy peak).

Thermodynamic and exergetic analysis of a novel multi-generation system based on SOFC, micro-gas turbine, s-CO2 and lithium bromide absorption refrigerator

To improve the utilization of waste heat from a solid oxide fuel cell (SOFC), a novel multi-generation energy system is proposed and analyzed from the viewpoints of energy and exergy. It consists of a SOFC, a micro-gas turbine (MGT), a supercritical carbon dioxide (S-CO2) Brayton cycle and a lithium bromide absorption refrigerator. The main part of the SOFC-MGT waste heat is recovered by a S-CO2 Brayton cycle to generate excessive electric power. The residual exhaust heat of MGT is respectively recovered by a domestic heating device and a lithium bromide absorption refrigerator to produce heating and cooling. In this study, a mathematical model of the proposed system is developed to evaluate the system thermodynamic characteristics and determine the influences of input parameters like ambient temperature, fuel flow rate, current density and air flow rate. The results reveal that the multi-generation energy system obtains the electric power of 696.9 kW, heating capacity of 24.98 kW and cooling capacity of 88.81 kW under design condition, and the energetic round trip efficiency and electrical efficiency of the system are 70.49% and 60.59%, respectively. According to sensitivity analysis, the current density has the greatest influence on the system round trip efficiency and electrical efficiency and the reformer intake fuel flow rate shows the most influential effect on SOFC voltage. The burner accounts for the maximum exergy destruction among all components. Overall, the multi-generation energy system based on SOFC is superior to the standalone SOFC power system in the respect of energy and exergy.

Modified cost analysis integrated with dual parametric sensitivity study for realistic cost assessment of a novel modified geothermal-based multi-generation energy system

In this investigation, an innovative modification process has been employed to enhance the capability of a novel multi-generation energy system (MGS) utilizing a dual-flash binary geothermal cycle incorporated with two main subsystems. These subsystems include a novel cooling, heat, and power (CCHP) unit by an ejector-based cooling cycle (ERC) joint to an organic Rankine power cycle (ORC) and a hydrogen generation setup via a low-temperature electrolyzer. In addition, a binary mixture consisting of Pentane and R142b has been utilized for the CCHP subsystem as a working fluid. Nonetheless, to assess the actual operating cost of investigated system, the exergetic and energy level-based exergoeconomic (modified exergoeconomic) analysis has been implemented instead of using conventional exergoeconomic analysis; afterward, due to the conflicting trend between design and performance parameters, dual parametric sensitivity study and double-objective optimization using NSGA-II approach have been carried out. According to the outcomes of dual parametric study, the results are further sensitive to the simultaneous variation in second flash tank inlet pressure and vapor generator temperature. Optimization results indicate that the net electricity production has increased from 33.04 kW to 40.59 kW, which improves the exergetic efficiency of the system by 4.39 %. Also, in this case, the total unit product cost has ameliorated by 3.4% and 2.62% in terms of modified and conventional cost approaches. The best representative optimal solution has the optimal energetic efficiency, exergetic efficiency, and unit product cost of 38.35%, 43.50%, and 52.52 $/GJ, respectively.

Analysis of a Multi-Generation Renewable Energy System With Hydrogen-Fueled Gas Turbine

Abstract Solar energy is considered one of the most affordable renewable resources for meeting current energy demands and mitigating environmental problems. However, the exploitation of solar energy is challenging because of both diurnal and seasonal variations. Power-to-hydrogen technologies can play a key role to counterbalance the variation of solar irradiance. Moreover, hydrogen-fueled gas turbines are considered promising technologies to decarbonize the electricity sector. To tackle these concerns, this paper presents a multigeneration energy system operated in island mode in which a hydrogen-fueled gas turbine is coupled with a solar photovoltaic plant, an electrolyzer, an absorption chiller, electric and thermal energy storage, as well as a hydrogen storage. Therefore, the energy system is 100% based on renewable energy. The sizes of the components are optimized by maximizing the exploitation of renewable energy sources, while the supply of electricity from the national grid must be null. Moreover, the effect of ambient conditions on the optimal sizing is also investigated by considering the thermal, cooling, and electrical energy demands of two case studies located in two different climatic zones. The paper demonstrates that the adoption of hydrogen-fueled gas turbines coupled with power-to-hydrogen technologies can effectively support the transition toward a clean energy supply. Moreover, this study provides a procedure for the optimal sizing of a multigeneration energy system fully based on solar energy, by also demonstrating that both photovoltaic (PV) panel area and hydrogen storage volume are feasible, if compared to the considered district layout.

Performance evaluation and multi-objective optimization of an innovative solar-assisted multigeneration energy storage system for freshwater/O2/H2 generation

A novel multigeneration energy system encompassing a two-stage water purification unit, high-temperature solid oxide electrolysis cell (SOEC), heliostat solar field, and power generation cycles including organic and two-stage steam Rankine cycles is introduced in this study. The two-stage desalination system comprises humidification, dehumidification, and reverse osmosis units. A thermoelectric generator is also utilized to convert dissipated heat into electricity. The proposed system is comprehensively analyzed from energy, exergy, economic, and sustainability standpoints. The effect of design parameters such as heliostat concentration ratio, view factor, desalination mass flow ratio, SOEC operating temperature, and current density on the hydrogen, oxygen and freshwater generation rate, sustainability index, total cost rate, and overall performance of the energy system are discussed. Further, multi-objective optimization based on non-dominated sorting genetic algorithm (NSGA-II) is implemented to identify the optimal operating state of the system. Comparative assessment of the system in the actual condition in the Middle East region showed that the plant has higher performance in June compared to December. Also, optimization revealed that by choosing C = 988, P7 = 1500 kPa, P8 = 300 kPa, MFD = 2.5 and Tcell = 1250 K, the highest obtainable exergy efficiency and minimum total cost rate in the optimal operating state would be 11.32 % and 78.18 $/h, respectively.

Technical assessment of Multi-generation energy system driven by integrated renewable energy Sources: Energetic, exergetic and optimization approaches

The integration of renewable resources such as solar, biomass and geothermal energies with other technologies and energy production cycles can lead to a more efficient power generation process. In addition, the development of multi-generation energy configurations can increase the sustainability, popularity, and flexibility of energy production process. In this regard, this article presents and evaluates an annotative multi-generation configuration based on solar and geothermal energies integrated with Kalina (KC), organic Rankine (ORC), refrigeration, water electrolysis, and thermoelectric (TEG) cycles. The thermal energy of the process is supplied through geothermal well, parabolic trough solar collectors (PTSC) and biomass sources. Kalina and organic Rankine cycles are installed to generate electricity. A thermoelectric generator is also embedded to increase electricity generation rate by exploiting the cycle heat losses. Meanwhile, water electrolysis and refrigeration cycles are responsible for producing a cooling load and a clean hydrogen fuel. The performance of the multi-generation configuration is evaluated and discussed from the points of view of thermodynamic, energetic, exergetic, and exergoeconomic. Moreover, a multi-objective optimization algorithm is established to optimize the exergetic efficiency and products unit cost. It was found that under the optimum case, the proposed multi-generation configuration can produce 80.1 kW and 1930 g/h of electricity and hydrogen fuel, respectively. In such a context, it can achieve 35.9 % for the exergetic efficiency and 36.95 USD per GJ for the products unit cost. Furthermore, the Levelized Cost of Electricity and hydrogen of the configuration were 5.67 USD per kg and 0.098 USD per kWh, respectively.

Development of a novel flexible multigeneration energy system for meeting the energy needs of remote areas

This paper introduces a flexibility concept in development of a novel multigeneration energy system driven by a renewable energy heat source. Nevertheless, the energy system can be upgraded to a highly productive system by incorporating other subsystems for achieving more production such as domestic hot water and freshwater. A novel design is proposed for a system comprising organic Rankine cycle, absorption compression heat pump, liquid natural gas to natural gas converting system, domestic water heater, and humidifier-dehumidifier desalination to exploit the Sabalan geothermal source for multigeneration purposes. Due to its high-efficient and environmentally friendly characteristics, n-pentane is utilized in the organic Rankine cycle. Also, the Ammonia-water is employed in the absorption compression heat pump subsystem. Energy, exergy, and thermoeconomic analysis is conducted on the plant along with multi-objective optimization based on the parametric study of key variants. According to the results, the novel step-by-step flexibility analysis can give a wide viewpoint to the designers to make the best multiple plant. The results of multi-objective optimization indicate that the freshwater production increases from 0.803 kg/s to 0.834 kg/s, the capacity of the domestic water heater rises from 1254 kW to 1265 kW, and the net output power surges up by 137.96 kW. However, the heating production falls from 1276 to 1088 kW. Furthermore, the total energy and exergy efficiencies increase by 6.43% and 4.47% with a 2.08 $/GJ reduction in the unit cost of the product.