1,721,257 research outputs found
A modelling methodology for a solar energy-efficient neighbourhood
No full textPurpose: The purpose of this paper is to present a methodology to quantify the solar energy potential for applying photovoltaic systems and find an efficient geometry for urban blocks to obtain a better quality of daylighting in terms of continuous daylight autonomy (DA) and spatial DA with less energy consumption. Design/methodology/approach: The paper is based on a complete simulation of the topography and micro-climate of the area under study. Simulations were performed using ArcGIS and Rhinoceros and urban daylight (UD) and urban modeling interface plugin for a neighborhood in the region of Narmak in Tehran, Iran. Five configurations of a neighborhood were compared using simulations. Findings: It was found that the impact of the geometrical form on daylight gain and energy consumption is significant and the terraced model is the most suitable form for obtaining a constant floor area ratio. Furthermore, it is an optimal form of urban blocks to gain the most energy through photovoltaic systems in the neighborhood as it would be able to satisfy about 42 percent of the energy needs. Originality/value: Planning to achieve sufficient energy factors in cities is a difficult task, since urban planners often do not have adequate technical knowledge to measure the contribution of solar energy in urban plans and this paper aims to introduce a comprehensive modeling methodology by which the urban energy planning can be used and understood in the urban context to make it completely clear as a strategy of implementation
Optimal operation of renewable energy communities under demand response programs
Full text linkWithin the context of renewable energy communities, this paper focuses on optimal operation of producers equipped with energy storage systems in the presence of demand response. A novel strategy for optimal scheduling of the storage systems of the community members under price-volume demand response programs, is devised. The underlying optimization problem is designed as a low-complexity mixed-integer linear program that scales well with the community size. An algorithm for redistributing the demand response rewards corresponding to the optimal solution is also developed in order to guarantee fairness among participants. The proposed approach is evaluated using two different objective functions through extensive numerical simulations. In all cases, economic benefits are demonstrated for producers that participate in a community rather than operating independently
Narrowing uncertainties in forecasting urban building energy demand through an optimal archetyping method
Full text linkThis paper aims at indicating and certifying the implemented framework for forecasting buildings' energy demand of the city of Bologna, Italy. The method is developed through an automated calibration and is based on 7 known, physics-based building parameters and 6 unknown, and highly uncertain variables. The proposed method focuses on reducing computing time while keeping the accuracy of the output by narrowing the uncertainties in predicting unknown parameters. To accomplish this task, 11 archetypes are defined which are representatives of the buildings in a specific neighborhood in Bologna, Italy. For every defined archetype, the most informative unknown variables are recognized and the Gaussian Process (GP) is employed to emulate the variable-to-data map. A wide sampling of the GP outputs is then applied by No-U-Turn Sampler (NUTS). The methodology is validated for 1156 Italian urban buildings based on the city database. The level of evaluation metrics demonstrates no bias in the output of the long-term forecasting while it accelerated the prediction of building energy demand and calibration on the city scale. The method is flexible for application in other contexts and various available urban datasets
Developing a 3D City Digital Twin: Enhancing Walkability through a Green Pedestrian Network (GPN) in the City of Imola, Italy
Full text linkPredominantly, dense historical cities face insufficient pedestrian-level greenery in the
urban spaces. The lack of greenery impacts the human thermal comfort on the walking paths, which
contributes to a considerable reduction in pedestrian flow rate. This study aims at developing a model
to assess pedestrian-level thermal comfort in city environments and then evaluate the feasibility of
creating a green pedestrian network (GPN). Imola, as a historical city in Italy with a compact urban
pattern, is selected as the case study of this paper. To accomplish this, a three-dimensional digital
twin at city scale is developed for the recognition of real-time shade patterns and for designing a
GPN in this city. The 3D model of the proposed digital twin is developed in the Rhinoceros platform,
and the physiological equivalence temperature (PET) is simulated through EnergyPlus, Honeybee,
and Ladybug components in grasshopper. This study provides the city with a digital twin that is
capable of examining pedestrian-level thermal comfort for designing a GPN based on real-time PET
in the compact urban morphology of Imola. The PET model indicates that during the hottest hour
of the 25th of June, pedestrians in open spaces can experience 3 C more than on narrow shaded
streets. The results are validated based on in situ datasets that prove the reliability of the developed
digital twin for the GPN. It provides urban planners and policy makers with a precise and useful
methodology for simulating the effects of pedestrian-level urban greenery on human thermal comfort
and also guarantees the functionality of policies in different urban settings
Robust distributed secondary voltage restoration control of ac microgrids under multiple communication delays
Full text linkThis paper focuses on the robust distributed secondary voltage restoration control of AC microgrids (MGs) under multiple communication delays and nonlinear model uncertainties. The problem is addressed in a multi-agent fashion where the generators’ local controllers play the role of cooperative agents communicating over a network and where electrical couplings among generators are interpreted as disturbances to be rejected. Communications are considered to be affected by heterogeneous network-induced time-varying delays with given upper-bounds and the MG is subjected to nonlinear model uncertainties and abrupt changes in the operating working condition. Robustness against uncertainties is achieved by means of an integral sliding mode control term embedded in the control protocol. Then, the global voltage restoration stability, despite the communication delays, is demonstrated through a Lyapunov-Krasovskii analysis. Given the delays’ bounds, and because the resulting stability conditions result in being non-convex with respect to the controller gain, then a relaxed linear matrix inequalities-based tuning criteria is developed to maximize the controller tuning, thus minimizing the restoration settling-time. By means of that, a criteria to estimate the maximal delay margin tolerated by the system is also provided. Finally, simulations on a faithful nonlinear MG model, showing the effectiveness of the proposed control strategy, are further discussed
Agro-environmental assessment of recycling abattoir blood meal powder as an organic fertilizer using soil quality index and hazard quotient
Full text linkPurpose This study assessed the fertilizing potential and environmental impacts of recycling the blood meal powder (BMP) produced in the abattoir as an organic fertilizer in agriculture.Method In this study, a 70-day laboratory incubation experiment was conducted using a clayey calcareous soil to study the effects of adding abattoir BMP at three rates (1.5, 3.0, and 6.0 ton ha-1). At the end of the incubation period, the pH value, total C and N, inorganic N, and availability of macro- and micronutrient minerals (P, K, Cu, Fe, Mn, Ni, and Zn) were measured. Soil basal respiration, substrate-induced respiration, the abundance of culturable bacteria, fungi, and azotobacter, and dehydrogenase, alkaline and acid phosphomonoesterase, cellulase, invertase, protease, and urease enzymes activities were also determined as biochemical indicators of soil fertility.Results The results showed that the BMP has potential as fertilizer because it increased C, N, P, and Zn as compared to the control soil. Furthermore, the abundance of culturable microorganisms and dehydrogenase activity increased in the amended soil, whereas the other soil enzyme activities and basal respiration did not show an increase. The calculation of the Hazard Quotient (HQ) and the soil quality index (SQI) indicated that 3.0-ton BMP ha-1 is an appropriate treatment to improve soil quality without environmental hazards.Conclusion The results indicate that abattoir BMP application increased the fertility status of calcareous soil without environmental threats
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
A comparison of energy and thermal performance of rooftop greenhouses and green roofs in Mediterranean climate: A hygrothermal assessment in WuFi
Full text linkIn urban areas, a considerable proportion of energy demand is allocated to buildings. Since rooftops constitute one-fourth of all urban surfaces, an increasing amount of attention is paid to achieving the most efficient shapes and component designs compatible with every climate and urban context, for rooftops of varying sizes. In this study, three types of rooftop technologies, namely insulated, green roof, and rooftop greenhouse, are evaluated for energy and thermal performance using computer simulations. Water surface exposure, absorption, and intrusion are the three important factors in the calculation of hygrothermal models that impact energy consumption and building envelope performance; however, a few studies are specifically focused on providing realistic results in multi-dimensional hygrothermal models and the assessment of the impact of moisture in roofing solutions. This paper aims at evaluating the performance of three different roofing technologies through a two-dimensional hygrothermal simulation in software WUFI. To accomplish this, a precise localized microclimate model of a complex urban context on the scale of a neighborhood was employed to evaluate the cooling and heating loads of the buildings, the impact of the water content in the green roof on the thermal behavior of the roof surface, and the feasibility of designing a building with nearly zero cooling needs. A two-story building in the city center of Bologna, Italy is modelled. Simulation results have shown that during the cooling period, the performance of the designed rooftop greenhouse is the most effective by 50% reduction in cooling loads. Besides, the impact of moisture in green roofs has been detected as a negative factor for thermal and energy performance of the building in the Mediterranean climate. The results ultimately highlighted the capability of passively-designed rooftop greenhouses to create a building with nearly zero cooling needs
A hybrid Python approach to assess microscale human thermal stress in urban environments
Full text linkMicroclimate simulations are in high demand to assess the thermal impacts of urban design and vegetation changes. Modeling accurate microclimate dynamics in complex urban settings requires extensive computing power. A hybrid Python approach is introduced to simulate human thermal exposure (mean radiant temperature, MRT) and comfort (Universal Thermal Climate Index, UTCI) in cities. The proposed model combines various engines in Rhinoceros to account for interactions between urban surfaces, tree canopies, and the atmosphere. The model was validated in hot, dry Tempe, USA, using in-situ human-biometeorological observations and then applied to urban archetypes in Bologna and Imola, Italy. MRT and UTCI were simulated at five sites in Bologna, four in Imola, and four in Tempe, with varying building heights and canopy cover for the climatologically hottest week of the year (August 3-9). The model performed well with an RMSE of 5.4 degrees C, an index of agreement of 0.96, and outperformed existing models for tree-shaded sites. MRT and UTCI were driven mainly by shade from dense urban forms and trees. Highrise, medium-to-high tree canopy cover archetypes were the coolest concerning thermal exposure and comfort. Sites in Tempe exceeded the UTCI categories for Very Strong or Extreme Heat Stress independent of archetype. The model enables fast and accurate assessment of urban tree planting strategies
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