Search Results (27)

Building energy consumption is a major source of carbon emissions, with the heating energy demand of rural buildings in the hot summer and cold winter (HSCW) zone having increased 575-fold over the past 15 years. This research investigated an optimized solar–air source heat pump (SASHP) system to meet the heating demand of rural residences in this region. First, a typical rural building model was developed using SketchUp, and its heating load was simulated using TRNSYS, revealing an average load of 3.38 kW and a peak load of 5.9 kW. Based on the latest technical standards, the SASHP system was designed and simulated using TRNSYS, achieving an overall coefficient of performance (COP) of 3.67 while maintaining indoor thermal comfort within ISO 7730 Category II. Subsequently, the system was optimized through GenOpt to minimize the annual equivalent cost, yielding key parameters: a 15 m² solar collector at a 40.75° tilt, a 0.35 m³ water tank, and a 10.16 kW air source heat pump. Compared with the initial design, the optimized configuration achieved reductions of 35.60% in initial investment and 32.68% in annual equivalent costs. By ensuring thermal comfort and overcoming the economic barrier, this study provides a viable pathway for adoption and promotion of renewable heating technology in rural areas. Full article

This study investigates the thermal resilience of naturally ventilated Lebanese residential buildings in the context of future climates, based on four climate zones: coastal (moderate and humid), low mountain (cool and seasonally variable), inland plateau (semi-arid with high summer heat), and high mountain (cold, with significant winter conditions). The aim of the study is to evaluate how passive envelope interventions can enhance indoor thermal resilience under five present and future work scenarios: TMY, SSP1-2.6 (2050 and 2080), and SSP5-8.5 (2050 and 2080). A baseline model was developed for typical building stock in each climate using EnergyPlus-23.2.0. The passive design parameters of window type, shading depth, and building orientation were systematically altered to analyze their effect on thermal comfort and building thermal resilience. Unlike previous studies that assessed either individual passive strategies or a single climate condition, this research combines multi-objective optimizations with overheating resilience metrics, by optimizing passive interventions using the GenOpt-3.1.0 and BESOS (Python-3.7.3 packages to minimize indoor overheating degree (IOD) and maximize climate change overheating resistivity (CCOR) index. Our findings indicate that optimized passive interventions, such as deep shading (0.6–1.0 m), low-e or bronze glazing, and southern orientations, can reduce overheating in all climate zones, reflecting a substantial improvement in thermal resilience. The novelty of this work lies in combining passive envelope optimization with future climate situations and a long-term overheating resilience index (CCOR) in the Mediterranean region. The results provide actionable suggestions for enhancing buildings’ resilience to climate change in Lebanon, thus informing sustainable design practice within the Eastern Mediterranean climate. Full article

In modern agriculture today, the cultivation of agricultural products cannot be imagined without greenhouses. This paper presents an energy optimization of a solar greenhouse with a photovoltaic system (PV) and a ground-source heat pump (GSHP). The PV system generates electricity, while the GSHP is used for heating and cooling. A greenhouse is designed with an Open Studio plug-in in the Google SketchUp environment, the EnergyPlus software (8.7.1 version) was used for energy simulation, and the GenOpt software (2.0.0 version) was used for optimization of the azimuth angle and PV cell efficiency. Results for different solar greenhouse orientations and different photovoltaic module efficiency are presented in the paper. The obtained optimal azimuth angle of the solar greenhouse was −8°. With the installation of a PV array with higher module efficiency (20–24%), it is possible to achieve annual energy savings of 6.87–101.77%. Also, with the PV module efficiency of 23.94%, a concept of zero-net-energy solar greenhouses (ZNEG) is achieved at optimal azimuth and slope angle. Through the environmental analysis of different greenhouses, CO₂ emissions of PV and GSHP are calculated and compared with electricity usage. Saved CO₂ emission for a zero-net-energy greenhouse is 6626 kg CO₂/year. An economic analysis of installed renewable energy systems was carried out: with the total investment of 19,326 € for ZNEG, the payback period is 8.63 years. Full article

This contribution investigates whether the use of the MATLAB Optimization Toolbox on a parameter identification problem for a TRNSYS model provides better performance in iteration time. It presents the development of a framework connecting the MATLAB Optimization Toolbox with TRNSYS on the one hand and coordinating the optimization process of a TRNSYS model by GenOpt through MATLAB on the other hand. A benchmark framework in MATLAB was created to link TRNSYS and MATLAB and to configure the optimization process of GenOpt and the MATLAB Optimization Toolbox. Using this framework, a comprehensive comparison of the optimization solvers in GenOpt and the MATLAB Optimization Toolbox for the identification of the overall heat transfer coefficient of a TRNSYS heat exchanger model regarding the optimization time and number of iterations is presented as a use case. The results for the given problem show that GenOpt gives slightly better results in optimization time, whereas MATLAB has more potential and flexibility. Full article

The number of high-rise residential buildings in China has a large base and rapid growth, with huge energy-saving potential. Most of the existing research focuses on the use of renewable energy to reduce energy consumption and optimize energy systems. When optimizing the renewable energy system configuration of residential buildings for solar-air source heat pump systems, the optimization algorithm and the setting of parameter ranges will have an impact on the optimization results. Therefore, to make up for the shortcomings of a single optimization process, this study proposes a joint solution based on simulations and multi-stage multi-objective optimization to improve the energy efficiency of the system and maximize economic benefits. This method was applied to perform energy consumption and economic optimization analyses for typical high-rise residential buildings in four cities in China (Shanghai, Nanjing, Wuhan, Chongqing) characterized by hot summers and cold winters. First, DeST software is used to model and calculate the building load. Then, TRNSYS software is used to establish a system simulation model. Next, the GenOpt program and the Hooke–Jeeves algorithm are used to perform the first stage of optimization with the lowest annual cost value as the objective function. Finally, MATLAB software and the NSGA-II algorithm are used to perform the second stage of optimization with the lowest annual cost value and the highest system energy efficiency ratio as the objective function, respectively. Moreover, the TOPSIS method is used to evaluate and sort the Pareto optimal solution sets to obtain the optimal decision solution. Overall, the two-stage optimization of the solar-air source heat pump system brings multiple benefits and a more significant improvement in overall performance compared to a single-stage optimization. In terms of energy utilization efficiency, the tilt and azimuth adjustments in the first stage allow the collectors to be better oriented towards the sun and to absorb solar energy more fully. This helps to improve the energy utilization efficiency of the system. For the economy of the system, the increase in the collector area and the reduction in the heat production of the air source heat pump in the second stage, as well as the increase in the volume of the water tank, have combined to reduce the operating costs of the system and improve its economy. Results demonstrate that the proposed two-stage optimization significantly improves the overall performance of the solar-air source heat pump system across all four cities, providing a robust framework for sustainable urban residential energy systems. This is a positive aspect for sustainability and environmental friendliness. Taken together, the two-stage optimization improves the performance of the system in a more comprehensive manner compared to the single-stage optimization. Full article

To address the energy consumption issue in mining area buildings, this paper proposed a solar-coupled mine water-source heat pump combined heating and cooling (SMWHP-CHC) system, taking the employee dormitory building group of a coal mining enterprise in Tongchuan City, China, as a case study. The system utilizes renewable solar energy and waste heat recovered from mine water as composite heat sources, and utilizes the cold energy in mine water as a cooling source to meet the demands for space heating, space cooling, and annual domestic hot water of the building in a sustainable manner. The simulation model of the system was established by TRNSYS to analyze the system’s annual operational performance. The results indicated that the system exhibited a positive energy efficiency and environmental performance under different operating conditions. The heating coefficients of the performance of the system (COP_sys) during the space heating season and transition season were 3.54 and 18.6, and the cooling energy efficiency ratio of the system (EER_sys) was 3.79. In addition, aiming to minimize the annual cost of the system, multiple crucial device parameters were synchronously optimized employing the PSO-HJ hybrid optimization algorithm through the GenOpt 2 software. The annual cost of the optimized system was reduced by 8.82%, and the investment cost was significantly reduced, while the performance was also improved. This study can provide theoretical support for the sustainable engineering application of the SMWHP-CHC system in mining area buildings. Full article

An office building located at Jinan equipped with ground-source heat pump (GSHP) system was selected as the research object. The GSHP system model was established using TRNSYS software. With the total energy consumption of the system as the objective function, several control strategies were proposed for the optimization work of water supply temperature at the load side of the heat pump unit. Firstly, a variable water temperature control strategy was adjusted according to the load ratio of the unit. In addition, the TRNSYS-GENOPT (TRNOPT) optimization module in TRNSYS was used to find the optimal water supply temperatures for different load ratios. After simulating and comparing the system’s energy consumption under the three control strategies, we found that the total annual energy consumption under the variable water supply temperature scheme is less than that under the constant water supply temperature scheme by 10,531.41 kWh. The energy saving ratio is about 5.7%. The simulation found that the total annual energy consumption under the optimized water supply temperature based on TRNOPT is lower than that under the variable water supply temperature scheme by 1072.04 kWh, and it is lower than that under the constant water supply temperature scheme by 11,603.45 kWh. The annual energy saving ratio of the system is about 6.3%. It is concluded that the optimized water supply temperature scheme based on TRNOPT has a better energy saving effect than the first two water supply temperature schemes. Full article

Simultaneous satisfaction of both thermal and visual comfort in buildings may be a challenging task. Therefore, this paper suggests a comprehensive framework for the building energy optimization process integrating computational fluid dynamics (CFD) daylight simulations. A building energy simulation tool, IDA Indoor Climate and Energy (IDA-ICE), was coupled with three open-source tools including GenOpt, OpenFOAM, and Radiance. In the optimization phase, several design variables i.e., building envelope properties, fenestration parameters, and Heating, Ventilation and Air-Conditioning (HVAC) system set points, were selected to minimize the total building energy use and simultaneously improve thermal and visual comfort. Two different scenarios were investigated for retrofitting of a generic office building located in Oslo, Norway. In the first scenario a constant air volume (CAV) ventilation system with a local radiator in each zone was used, while an all-air system equipped with a demand control ventilation (DCV) was applied in the second scenario. Findings showed that, compared to the reference design, significant reduction of total building energy use, around 77% and 79% in the first and second scenarios, was achieved respectively, and thermal and visual comfort conditions were also improved considerably. However, the overall thermal and visual comfort satisfactions were higher when all-air system was applied. Full article

Maximising genetic diversity in conservation efforts can help to increase the chances of survival of a species amidst the turbulence of the anthropogenic age. Here, we define the distribution and extent of genomic diversity across the range of the iconic but threatened Acacia purpureopetala, a beautiful sprawling shrub with mauve flowers, restricted to a few disjunct populations in far north Queensland, Australia. Seed production is poor and germination sporadic, but the species occurs in abundance at some field sites. While several thousands of SNP markers were recovered, comparable to other Acacia species, very low levels of heterozygosity and allelic variation suggested inbreeding. Limited dispersal most likely contributed towards the high levels of divergence amongst field sites and, using a generalised dissimilarity modelling framework amongst environmental, spatial and floristic data, spatial distance was found to be the strongest factor explaining the current distribution of genetic diversity. We illustrate how population genomic data can be utilised to design a collecting strategy for a germplasm conservation collection that optimises genetic diversity. For this species, inclusion of all field sites will capture maximum genetic diversity for both in situ and ex situ conservation. Assisted cross pollination, within and between field sites and genetically structured groups, is recommended to enhance heterozygosity particularly at the most disjunct sites and further fragmentation should be discouraged to avoid loss of genetic connectivity. Full article

Improving the energy efficiency of existing buildings by implementing building automation control strategies (BACS) besides building envelope and energy system retrofitting has been recommended by the Energy Performance of Buildings Directive (EPBD) 2018. This paper investigated this recommendation by conducting a simulation-based optimization to explore cost-effective retrofitting combinations of building envelope, energy systems and BACS measures in-line with automation standard EN 15232. Two cases (i.e., a typical single-family house and apartment block) were modeled and simulated using IDA Indoor Climate and Energy (IDA-ICE). The built-in optimization tool, GenOpt, was used to minimize energy consumption as the single objective function. The associated difference in life cycle cost, compared to the reference design, was calculated for each optimization iteration. Thermal comfort of the optimized solutions was assessed to verify the thermal comfort acceptability. Installing an air source heat pump had a greater energy-saving potential than reducing heat losses through the building envelope. Implementing BACS achieved cost-effective energy savings up to 24%. Energy savings up to 57% were estimated when BACS was combined with the other retrofitting measures. Particularly for compact buildings, where the potential of reducing heat losses through the envelope is limited, the impact of BACS increased. BACS also improved the thermal comfort. Full article

Thermal energy storage (TES), which features an innovative technology, can enhance energy efficiency in the building sector and reduce CO₂ emissions. Due to their high heat storage capacity, phase change materials (PCMs) have impressed many researchers. This paper investigates the energy performance of an individual house integrating a solar Trombe wall containing PCM with respect to heating demand and thermal comfort applications. The thermal energy performance of the design house was simulated using Dymola/Modelica, the thermal building simulation tool, whereby the optimization of objective functions as regards heating demand and thermal comfort was executed using GenOpt, the generic optimization software. Optimization of the solar Trombe wall focuses on the feasibility to find the optimal PCM parameters when running GenOpt, which consist of latent heat, melting temperature, PCM thickness and thermal conductivity, in order to minimize both the annual energy consumption for heating and the number of hours of thermal discomfort. The parametric study was first conducted for each PCM parameter so as to not only observe its effect on the identified energy performance, but also ensure the absence of errors in simulation runs before performing the optimization. The ‘Coordinate Search’ Generalized Pattern Search (GPS) algorithm was applied to minimize the objective function, whereas the ‘Weighted Sum Approach’ was used to solve the multi-objective function problem. Results showed that the higher the latent heat, the lower the heating demand and the greater the thermal comfort. The results of these parametric studies show that for the effect of the parameter on heating, demand is quite limited (1–2 kWh·m${}^{-2}$·year${}^{-1}$) whereas the effect on thermal comfort is more significant. The optimal PCM melting temperature is higher for warmer climates; it is also higher for the studied case applying the optimization method to minimize the objective function by assigning the number of hours of thermal discomfort (from 32.8 ${}^{\circ }\mathrm{C}$ to 35.9 ${}^{\circ }\mathrm{C}$, depending on weather) than it is when applying the optimization method to reduce the objective function by assigning heating demand (from 31.5 ${}^{\circ }\mathrm{C}$ to 32.9 ${}^{\circ }\mathrm{C}$, again depending on weather). Full article

It is well known that nowadays a significant part of the total energy consumption is related to buildings, so research for improving building energy efficiency is very important. This paper presents our investigations about the dimensioning of horizontal overhangs in order to determine the minimum annual consumption of building primary energy for heating, cooling and lighting. In this investigation, embodied energy for horizontal roof overhangs was taken into account. The annual simulation was carried out for a residential building located in the city of Belgrade (Serbia). Horizontal overhangs (roof and balcony) are positioned to provide shading of all exterior of the building. The building is simulated in the EnergyPlus software environment. The optimization of the overhang size was performed by using the Hooke Jeeves algorithm and plug-in GenOpt program. The objective function minimizes the annual consumption of primary energy for heating, cooling and lighting of the building and energy spent to build overhangs. The simulation results show that the building with optimally sized roof and balcony overhangs consumed 7.12% lessprimary energy for heating, cooling and lighting, compared to the house without overhangs. A 44.15% reduction in cooling energy consumption is also achieved. Full article

In Western tonal music, tension in chord progressions plays an important role in defining the path that a musical composition should follow. The creation of chord progressions that reflects such tension profiles can be challenging for novice composers, as it depends on many subjective factors, and also is regulated by multiple theoretical principles. This work presents ChordAIS-Gen, a tool to assist the users to generate chord progressions that comply with a concrete tension profile. We propose an objective measure capable of capturing the tension profile of a chord progression according to different tonal music parameters, namely, consonance, hierarchical tension, voice leading and perceptual distance. This measure is optimized into a Genetic Program algorithm mixed with an Artificial Immune System called Opt-aiNet. Opt-aiNet is capable of finding multiple optima in parallel, resulting in multiple candidate solutions for the next chord in a sequence. To validate the objective function, we performed a listening test to evaluate the perceptual quality of the candidate solutions proposed by our system. Most listeners rated the chord progressions proposed by ChordAIS-Gen as better candidates than the progressions discarded. Thus, we propose to use the objective values as a proxy for the perceptual evaluation of chord progressions and compare the performance of ChordAIS-Gen with chord progressions generators. Full article

This research paper introduces a mathematical model to predict the performance of photovoltaic–thermal systems (PV-T), based on a thin layer flexible panel and an air pipe, by using the Trnsys^® software tool to simulate energetic systems. The main advantage of these types of panels is their easy portability, making them ideal to address thermal needs in several scenarios. In the military field, there is an important concern about the use of sustainable energy; for instance, cooling facilities for infantry tents used in their deployments. In this research, a PV-T panel to cover electrical power needs for an infantry’s hangar unmanned air vehicle (UAV) is introduced. The proposed thermal model, based on the novelty of inertial mass (lump) as an approach to real panel behavior, has been validated through the comparison between Trnsys’ model simulation data, a real weather station, and data obtained in a test bed. Genopt’s simulation software is used to fit the model, allowing for the prediction of heat transmission coefficient values. The good match between simulated and experimental data makes the proposed model suitable for the photovoltaic–thermal prediction of panel behavior. Full article

In rooms with underfloor heating (UFH), local on–off controllers most often regulate the air temperature with poor accuracy and energy penalties. It is known that proportional–integral (PI) controllers can regulate most processes more precisely. However, hydronic UFH systems have long time constants, especially in low-energy buildings, and PI parameters are not easy to set manually. In this work, several potential PI parameter estimation methods were applied, including optimizing the parameters in GenOpt, calculating the parameters based on simplified models, and tuning the parameters automatically in Matlab. For all found parameter combinations, the energy consumption and control precision were evaluated. Simpler methods were compared to the optimal solutions to find similar parameters. Compared with an on–off controller with a 0.5 K dead-band, the best PI parameter combination found was with a proportional gain of 18 and an integration time of 2300 s, which could decrease the energy consumption for heating by 9% and by 5% compared with default PI parameters. Moreover, while GenOpt was the best method to find the optimal parameters, it was also possible with a simple automatic test and calculation within a weekend. The test can be, for example, 6-h setbacks applied during the nights or weekend-long pseudo-random changes in the setpoint signal. The parameters can be calculated based on the simplified model from these tests using any well-known simple method. Results revealed that the UFH PI controller with the correct parameters started to work in a predictive fashion and the resulting room temperature curves were practically ideal. Full article