“…where f ðxÞ is the objective function; g i ðxÞ is an inequality constraint; and m is the number of inequality constraints. Therefore, the penalty factor HðxÞ can be solved by Equation (30).…”
“…Compared with the conventional scheme, the operating cost saving rate of the optimized scheme was more than 10%. Keshavarzzadeh et al [ 30 ] used the total revenue rate method to study the economics of the GSHP system and found that the NAGS‐II algorithm gave the best solution compared with five other evolutionary algorithms. However, none of the earlier documents considers the operating characteristics of the heat pump unit.…”
To achieve the global Carbon Neutral goal required by the Paris Agreement, considerable concerns are advanced regarding improving the efficacy of clean energy in recent years. Taking as the research object a ground‐source heat pump (GSHP), which is a recently developed, highly efficient, and energy‐saving air‐conditioning technology, herein, the optimization of operational strategies regarding GSHP systems from the perspective of its individual heat pump units is studied. To attain this aim, an optimal scheduling model of surface water source heat pump regional energy systems with energy storage devices is established and then solved by the neighborhood adaptive particle swarm optimization (NAPSO) algorithm proposed. A method is proposed to transform the mixed integer programming problem into a continuous optimization problem to address the energy storage device model difficulties with integer variables. The experimental results show that the NAPSO algorithm can save 8.65% in cooling conditions and 7.22% in heating conditions in terms of operating costs compared with the empirical operation method. In addition, it can save 11.13% and 9.66% of operating expenses on average compared with the five other intelligent optimization algorithms.
“…where f ðxÞ is the objective function; g i ðxÞ is an inequality constraint; and m is the number of inequality constraints. Therefore, the penalty factor HðxÞ can be solved by Equation (30).…”
“…Compared with the conventional scheme, the operating cost saving rate of the optimized scheme was more than 10%. Keshavarzzadeh et al [ 30 ] used the total revenue rate method to study the economics of the GSHP system and found that the NAGS‐II algorithm gave the best solution compared with five other evolutionary algorithms. However, none of the earlier documents considers the operating characteristics of the heat pump unit.…”
To achieve the global Carbon Neutral goal required by the Paris Agreement, considerable concerns are advanced regarding improving the efficacy of clean energy in recent years. Taking as the research object a ground‐source heat pump (GSHP), which is a recently developed, highly efficient, and energy‐saving air‐conditioning technology, herein, the optimization of operational strategies regarding GSHP systems from the perspective of its individual heat pump units is studied. To attain this aim, an optimal scheduling model of surface water source heat pump regional energy systems with energy storage devices is established and then solved by the neighborhood adaptive particle swarm optimization (NAPSO) algorithm proposed. A method is proposed to transform the mixed integer programming problem into a continuous optimization problem to address the energy storage device model difficulties with integer variables. The experimental results show that the NAPSO algorithm can save 8.65% in cooling conditions and 7.22% in heating conditions in terms of operating costs compared with the empirical operation method. In addition, it can save 11.13% and 9.66% of operating expenses on average compared with the five other intelligent optimization algorithms.
“…Keshavarzzadeh et al [131] define the optimum operating conditions and borehole configurations by a multi-objective evolutionary algorithm. The assessed design parameters, specific for the GHE, are the borehole radius, inner pipe radius, shank spacing (i.e., the distance between inward and outward pipe), borehole spacing, and fluid velocity in the pipes.…”
Geothermal heat pumps have a widespread diffusion as they are able to deliver relatively higher energy output than other systems for building air-conditioning. The exploitation of low-enthalpy geothermal energy, however, presents crucial sustainability issues. This review investigates the primary forms of the environmental impact of geothermal heat pumps and the strategies for their mitigation. As life-cycle analyses shows that the highest impacts arise from installation and operation stages, most optimization studies focus on system thermodynamics, aiming at maximizing the energy performance via the optimization in the design of the different components interacting with the ground and serviced building. There are environmental studies of great relevance that investigate how the climate and ground properties affect the system sustainability and map the most suitable location for geothermal exploitation. Based on this review, ground-source heat pumps are a promising technology for the decarbonization of the building sector. However, a sustainable design of such systems is more complex than conventional air-conditioning systems, and it needs a holistic and multi-disciplinary approach to include the broad environmental boundaries to fully understand the environmental consequences of their operation.
“… Figure 3 Water mass flux across membrane ( a ) Inlet flow rate, Q = 7 cm 3 /s ( b ) Inlet flow rate, Q = 11 cm 3 /s. Symbols indicate experimental data 25 and lines show model results. …”
Section: Introductionmentioning
confidence: 99%
“…DCMD is one of the technologies which is highly dependent on the heat transfer. Multi-objective optimization, therefore, has been employed to obtain the optimized operation conditions [22][23][24][25][26] . Bejan et al 27,28 calculated the suitable size and shape of the heat exchanger which leads to a minimum thermodynamic loss.…”
At the present study, a one-dimensional model for the flat sheet direct contact membrane distillation (DCMD) for desalination purposes is proposed. Flows and membrane properties have been estimated by appropriate temperature-dependent correlations. Results show that the numerical model is in a very good agreement with experimental data at various feed temperatures, flow rates and concentrations. A constructal design is investigated for DCMD to assess how constructal law can improve the DCMD performance. With the same thermal efficiency of 93.5%, constructal design improves the water mass flux by 37.5% in comparison with the conventional DCMD design. Also, an evolutionary-based optimization algorithm is employed to increase the efficiency of the constructal and conventional design. The Pareto frontier of the constructal and conventional design is compared with each other and the correlations between design variables are investigated. Overall, the present study demonstrates how constructal law can increase the performance of energy systems with a simple modification.
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