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A hybrid energy system, comprising a diesel engine as the prime mover, electrical and absorption chillers, a backup boiler, and a multi‐effect distillation through thermal vapor compression (MED‐TVC) unit, has been utilized to meet the requirements of a residential complex. This study focuses on redesigning and optimizing the system to enhance environmental conditions, reduce pollutants, and minimize the use of fossil energy. The feasibility and design of renewable energy systems, including wind turbines (WTs), photovoltaic panels (PVs), and flat plate collectors (FPCs), have been examined. Genetic algorithm (GA) has been employed for optimization. The hybrid system employs 21 design variables, with 24 design variables chosen for optimization alongside renewable energies. The total annual cost (TAC), encompassing investment, operation, and pollution emission fines, has been chosen as the objective function for minimization. The results indicate that the use of WTs has not been cost‐effective, and solar energy can enhance the system's performance in Bandar Abbas, Hormozgan province in Iran. In the case of using a combined system, the objective function value was 2.0472 × 106 $/year, and when using renewable energies, the objective function became 1.6795 × 106 $/year. Thus, the proposed combined‐renewable system has reduced the objective function by 17.96%. [ABSTRACT FROM AUTHOR]

The combined heating, cooling, power (CCHP) and freshwater system are designed separately with two types of desalination plants including multi-effect desalination with thermal vapor compression (MED-TVC) and reverse osmosis (RO). This combined system meets the heating, cooling, power and fresh water needs of a hotel in Iran. Gas turbines and diesel engines are considered as prime movers (PM) for conversion of fuel to power and heat. The integration of the CCHP system with RO desalination was investigated in two modes of RO without colloidal fouling (first day of operation) and with colloidal fouling formation rate in a period of 90 days. The genetic algorithm (GA) was implemented to find the optimal values of 21 design parameters in the case of CCHP system with RO desalination and 22 design parameters in the case of CCHP system with MED-TVC desalination to minimize the annual cost. Optimization results showed that the diesel engine prime mover has a greater advantage over the gas turbine in the all studied modes. In addition, combination of CCHP + RO without colloidal fouling and with colloidal fouling and combination of CCHP + MED-TVC with diesel engine as PM showed 9.66 %, 1.80 % and 11.68 % reduction in annual cost compared with gas turbine as PM, respectively. [ABSTRACT FROM AUTHOR]

• Rotary regenerator (RR) is optimized using constructal theory. • Effectiveness and total annual cost (TAC) are considered as objective functions. • Multi objective optimization algorithm is used to obtain optimal value of 10 design variables. • Optimum design parameters and objective functions are compared with conventional RR. In this research, rotary regenerator (RR) is optimized using constructal theory. For this aim, a heat exchanger with two branches is considered. RR effectiveness and total annual cost (TAC) are deliberated as objective functions and 9 design variables are selected. The multi-objective optimization algorithm is used to obtain the optimal values of objective functions and design variables. The optimum results in the case of constructal are contrasted with optimum results in the conventional RR. The optimum results showed better thermoeconomic results in the case of constructal than conventional RR for the effectiveness higher than 0.6572. As an example, effectiveness improved by 6.98% in the case of constructal in comparison to conventional RR for the constant value of TAC=1821$/year. In addition, the optimum results showed 4.55% improvement in the maximum effectiveness in constructal compared with conventional RR. Finally, distribution of design parameters along with some important parameters such as heat transfer surface area and pressure drop for both studied cases are illustrated, compared and discussed. [ABSTRACT FROM AUTHOR]

In this paper, after thermal and economic modeling of cogeneration plant, this system is optimized to find the optimal prime mover and their benefit for various cooling, heating, and electrical demand loads. To find the optimal prime mover and their benefit for each triple load, two new nondimensional design parameters including electric cooling ratio and nominal power ratio are defined. It is observed that, for example, for higher electrical and lower heating load demands, the gas engine is more profitable while for higher electrical and heating load demands, diesel engine is more profitable. In addition, some ranges of demand loads at which using CCHP plant is not profitable (in comparison with traditional system) are also obtained and presented. The optimum results obtained in NO SELL mode show that the highest values of actual annual benefit (AAB) are obtained for highest values of electrical load demand. This region corresponds with values of Hdmn/Qdmn (heating to cooling load demand ratio) in the range of 1.5–3.5. The highest values of AAB for SELL mode are obtained to be in the range of 0.5–3.5 for Hdmn/Qdmn (heating to cooling load demand ratio). [ABSTRACT FROM AUTHOR]

In this study, a cross flow heat exchanger is optimized based on multi objective optimization algorithm by considering the effects of flow maldistribution for both cold and hot sides. For this purpose, total annual cost (TAC) and effectiveness of exchanger are selected as fitness functions and six decision variables including the heat exchanger and fin geometries are considered as decision variables. The optimization is performed for the three non-uniform velocity inlet profiles including linear, parabolic and power law and their optimum results are compared with the uniform (constant) profile. It is observed that, the Percentages of reduction in effectiveness for the final optimum solution are in the range of 2.93–4.88%, 1.50–3.38% and 0.79–1.24% respectively in the cases of linear, parabolic and power law profiles compared with constant inlet profiles. Moreover, Percentages of growth in the TAC for the final optimum solution are in the range of 13.00–16.49%, 6.97–10.49% and 0.77–1.63% respectively in the cases of linear, parabolic and power law profiles compared with constant inlet profiles. In addition, the higher hot and cold stream flow lengths and lower fin height and fin spacing are needed in the cases of linear, parabolic and power law profiles compared with the constant velocity profile for the fixed value of effectiveness. [ABSTRACT FROM AUTHOR]

An optimal design of a cogeneration plant assisted by a heat pump is presented. The total annual profit ratio is selected as an objective function to find the best prime mover (PM) and its profit in triple loads. Two dimensionless parameters, electric and heating ratios, are introduced as decision variables. The results reveal that the best studied PM is a diesel engine followed by a gas engine and gas turbine. This system is more economical for a high heating and electricity load demand, whereas it is less economical for a low heating and electricity load demand. Furthermore, for low power and heating load demands, no PM is selected and all the demanded power is requested from the grid, whereas for the higher heating and lower electricity load demands, all the demanded power is provided by the PM and there is no need to buy electricity from the grid. Finally, sensitivity analysis is performed on the change in the period of cooling and heating load demands. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a thermoeconomic optimization of a shell and tube condenser, based on two new optimization methods, namely genetic and particle swarm (PS) algorithms. The procedure is selected to find the optimal total cost including investment and operation cost of the condenser. Initial cost includes condenser surface area and operational cost includes pump output power to overcome the pressure loss. Design parameters are tube number, number of tube pass, inlet and outlet tube diameters, tube pitch ratio and tube arrangements (30, 45, 60 and 90°). Therefore, shell diameter should be selected less than 7m, tube length should be less than 15m, and ratio of diameter to tube length should be in the range of 1/12 to 1/3. In addition, it is found that GA provides better results for computer CPU running time, compared to PS algorithm. Finally, a sensitivity analysis of design parameters at the optimal point is conducted. Results show that an increase in the tube number leads to decrease in the objective function first then it leads to a considerable increment in objective function. [Copyright &y& Elsevier]

• A new configuration for fin and tube heat exchanger is proposed and optimized. • The mentioned configuration is motivated by constructal theory. • 16 parameters are considered as decision variables. • Both effectiveness and cost are selected as objective functions. • The optimal results are compared with conventional heat exchanger In this study, constructal (branch type) fin and tube heat exchanger (FTHE) is modeled and optimized. Effectiveness and total annual cost (TAC) are selected as objective functions and 8 variables for each section of exchanger are considered as design parameters (16 design parameters in total). Then, multi objective form of genetic algorithm is used to find the optimal Pareto front. The optimization is implemented for conventional FTHE as well and their results are compared with branch type condition. The optimum results show 6.65% improvement in the maximum effectiveness in the branch type condition compared with conventional FTHE. In the constructal state, lower volume is selected in the second section as compared with the first section. The same trend is also found for heat transfer surface area. Finally, optimum design parameters in terms of effectiveness for the both studied conditions are illustrated and discussed. [ABSTRACT FROM AUTHOR]

This paper comprehensively investigates performance of evolutionary algorithms for design optimization of shell and tube heat exchangers (STHX). Genetic algorithm (GA), firefly algorithm (FA), and cuckoo search (CS) method are implemented for finding the optimal values for seven key design variables of the STHX model. ∊ -NTU method and Bell-Delaware procedure are used for thermal modeling of STHX and calculation of shell side heat transfer coefficient and pressure drop. The purpose of STHX optimization is to maximize its thermal efficiency. Obtained results for several simulation optimizations indicate that GA is unable to find permissible and optimal solutions in the majority of cases. In contrast, design variables found by FA and CS always lead to maximum STHX efficiency. Also computational requirements of CS method are significantly less than FA method. As per optimization results, maximum efficiency (83.8%) can be achieved using several design configurations. However, these designs are bearing different dollar costs. Also it is found that the behavior of the majority of decision variables remains consistent in different runs of the FA and CS optimization processes. [ABSTRACT FROM AUTHOR]