Achieving Faster Building Energy Model Optimization through Selective Zone Elimination

Optimization in building performance simulation (BPS) has become increasingly important due to the growing need for high-performance building design and operation. Numerous research efforts have been dedicated to decreasing optimization runtime by introducing improved optimization algorithms and advanced sampling techniques. This paper presents a novel model order reduction (MOR) algorithm tailored for speeding up building energy simulation. The algorithm identifies archetype zones simplifying the needless repetition of thermal zones. For an entire optimization process, this MOR method can be repeated recursively to reproduce reduced models. The proposed method can be used to speed up large-scale simulations including optimization, uncertainty analysis and model predictive controls. Preliminary results with parametric simulations show a runtime reduction of about 76% reduction for 15 simulations while still maintaining the predicted total annual energy consumption within a 10% margin. Further research will be conducted to compare the optimization results when applying the proposed MOR algorithm and determine if the reduced model produces the same optimal design. The proposed method may significantly improve the optimization runtime with a minor effect on optimization accuracy, thus increasing the overall usability of BPS optimizations

Optimal Power Flow for Integrated Primary-Secondary Distribution Networks with Service Transformers

Secondary distribution networks (SDNets) play an increasingly important role in smart grids due to a high proliferation of distributed energy resources (DERs) in SDNets. However, most existing optimal power flow (OPF) problems do not take into account SDNets with service transformers. Handling the nonlinear and nonconvex SDNet power flow constraints is still an outstanding problem. To meet this gap, we first utilize the second-order cone programming relaxation and linearization to make service transformer constraints convex, respectively. Then, the linearized triplex service line power flow model, including its compact matrix-vector form, is further developed to compose the SDNet OPF model with our proposed service transformer model. This proposed SDNet OPF model can be easily embedded into existing primary distribution network (PDNet) OPF models, resulting in a holistic power system decision-making solution for integrated primary-secondary distribution networks. A case study is presented for an integrated primary-secondary distribution network that demonstrates the practical effectiveness of this model

Data-driven short-term load forecasting for heating and cooling demand in office buildings

Short-term forecasts of energy demand in buildings serve as key information for various operational schemes such as predictive control and demand response programs. Despite this, developing forecast models for heating and cooling loads has received little attention in the literature compared to models for electricity load. In this paper, we present data-driven approaches to forecast hourly heating and cooling energy use in office buildings based on temporal, autoregressive, and exogenous variables. The proposed models calculate hourly loads for a horizon between one hour and 12 hours ahead. Individual models based on artificial neural networks (ANN) and change-point models (CPM) as well as a hybrid of the two methods are developed. A case study is conducted based on hourly thermal load data collected from several office buildings located on the same campus in Ottawa, Canada. The models are trained with more than two years of hourly energy-use data and tested on a separate part of the dataset to enable unbiased validation. The results show that the ANN model can achieve higher forecasting accuracy for the longest forecast horizon and outperforms the results obtained by a Naïve approach and the CPM. However, the performance of the hybrid CPM-ANN method is superior compared to individual models for all studied buildings

Research on the Experimental Teaching Method of Vibration Damping Fastener for Undergraduates Majoring in Rail Transit

Experiment is an important teaching link in talent training. Aiming at the current situation and problems of the experimental teaching of rail transit major, taking the experimental teaching of vibration damping fastener drop weight for railway engineering major of Central South University as an example, the specific methods of the new experimental teaching mode for undergraduates majoring in rail transit are expounded: Improve the subject experimental system, build an open experimental platform, and improve the school-enterprise resource sharing system, etc. This model is conducive to the reform and development of the experimental teaching model for rail transit majors and related science and engineering majors

Research on Practical Teaching of Railway Engineering Specialty Based on Temperature Test of Rubber Sleepers

Experimental teaching plays an important role in cultivating college students' innovative ability. This paper takes the practical teaching of the temperature test of the new rubber sleeper as an example to analyze the current situation and problems of the practical teaching of railway engineering. The specific measures of the new system of practical teaching of railway engineering are put forward: Build a practical teaching curriculum system, improve the practical teaching evaluation mechanism, and promote the sharing of school-enterprise resources, so as to cultivate outstanding railway engineering talents with engineering ability and innovative spirit

Extensive gene flow in secondary sympatry after allopatric speciation

In the conventional view, species are separate gene pools delineated by reproductive isolation (RI). In an alternative view, species may also be delineated by a small set of ‘speciation genes’ without full RI, a view that has gained broad acceptance. A recent survey, however, suggested that the extensive literature on ‘speciation with gene flow’ is mostly (if not all) about exchanges in the early stages of speciation. There is no definitive evidence that the observed gene flow actually happened after speciation is completed. Here, we wish to know whether ‘good species’ (defined by the ‘secondary sympatry’ test) do continue to exchange genes and, importantly, under what conditions such exchanges can be observed. De novo whole-genome assembly and re-sequencing of individuals across the range of two closely related mangrove species (Rhizophora mucronata and R. stylosa) reveal the genomes to be well delineated in allopatry. They became sympatric in northeastern Australia but remain distinct species. Nevertheless, their genomes harbor ∼4000–10 000 introgression blocks averaging only about 3–4 Kb. These fine-grained introgressions indicate continual gene flow long after speciation as non-introgressable ‘genomic islets,’ ∼1.4 Kb in size, often harbor diverging genes of flower or gamete development. The fine-grained introgression in secondary sympatry may help settle the debate about sympatric vs. micro-allopatric speciation. In conclusion, true ‘good species’ may often continue to exchange genes but the opportunity for detection is highly constrained