Abstract

Long-term optimized operation has been looking to unit commitment to replace the traditional power flow for more accurate modeling of system operation. Alongside the intuitive advantage of representing not only the production of the generation units of consecutive time periods but also their commitment status, comes the heavier computational burden for the multi-unit long-term model. In fact, representing the commitment status of each unit with a binary variable in the corresponding constraints alone complicates the optimization, let alone other accessory variables, such as those for switch actions. Moreover, unit commitment is usually conducted over a narrow window of time, e.g., one day or one week with an hourly resolution; ordinary unit commitment models that run over an annual load profile will be hindered from even converging to a solution by heavy computation. As such, clustering techniques are proposed to be equipped with the unit commitment in two dimensions, one to select representative periods for the load profile of a long horizon, the other to group homogeneous or similar units. As the former is conducted in the time dimension, it can be named the temporal clustering, and the latter hence named the spatial clustering. As a result, this new method with both is therefore named the tempo-spatially clustered unit commitment. The case study on a 39-node 17-unit system proves the efficacy and efficiency of the proposed unit commitment approach.

Abstract

In modern power system, traditional transient stability assessment(TSA) methods undergo great challenges as the time domain and space structure complexity continue to increase. Taking into account the massive features generated by the power system, in order to avoid the dimensionality disaster problem in artificial intelligence methods and machine learning models, this paper proposes a novel feature selection method. Based on interaction gain, this method measures both the effectiveness and combination effects of certain feature subset, thereby simplifying the original input without information loss. Case study on IEEE 39-bus system TSA verifies the validation in accuracy, false alarms, calculation efficiency and feature size.

Abstract

This paper reports on the construction of a two stage loop thermosyphon cooling system and the analysis of its heat transfer mechanisms. The temperature and heat resistance distributions under various liquid filling ratios and heat loads are summarized. Further, the heat transfer boundary of the system and conditions for the two operating limits (dry out and immersion) were determined. Finally, the heat transfer paths obtained under standard and immersion limit operating conditions and the characteristics of coolants were analyzed and compared.

Abstract

Recently, with the introduction of DER (Distributed Energy Resources) such as wind, solar, energy storage systems, and electric vehicles, distribution systems have also started to produce and trade electricity. In order to cope with the changing system environment, countries around the world recognize that new functions for distribution system operation are needed, and application research based on AMI (Advanced Metering Infrastructure) is underway. However, it is still in the research stage and there is no specific functional design. In this paper, in line with the spread of AMI in Korea, four business use cases that can be implemented using AMI are defined. These are related to the distribution system and DER control, and the information exchange sequence was designed and represented as a Unified Modeling Language diagram. DSO (Distribution System Operator) can establish a foundation for improving distribution system operation and secure LV (Low Voltage) distribution system visibility through the implementation of this business use case.

Abstract

A data mining approach is proposed for evaluating the effects of battery production factors in cathode coating stage on both battery capacity and internal resistance for the first time. Specifically, an effective neural network model is built based on real data form designed experiments for obtaining reference cathode coating for coin cells. The purpose is to analyze and predict how the battery quality in both charge and discharge scenarios changes with respect to the key factors of coating including its weight and thickness. The results highlight the correlation between mentioned factors and battery quality indices, which could guide manufacturer to identify efficient ways for producing high-quality batteries.

Abstract

This study evaluates the cooling effect of latent heat storage (PCM) on integrated PV cells between two glass layers in a double-glazed ventilated building-integrated photovoltaic (BIPV) façade. Transient CFD simulations were performed to investigate the potential of thermal management. The varying parameters were: PCM thickness, PCM thermal conductivity, PCM latent heat storage capacity, BIPV glass thickness, and air velocity in the ventilated gap. A regression model with interactions was made for evaluating the relative impact of thermal management on overheating hours compared to a reference system without PCM. The results show the importance of enhancing the thermal conductivity of PCM, with the greatest impact in the initial enhancement and neglectable effect at higher values above roughly 1 W/mK.

Abstract

We propose a novel framework to address the problem of detecting anomalies in building electricity consumption profiles. Our method is based on two sequential steps, which combine machine learning clustering and regression methods. The first step separates weekly anomalous consumption profiles from
regular ones, for a selected timespan. This is achieved through an unsupervised machine learning clustering method applied on a representation of weekly profiles in a two-dimensional space. The results of the clustering method are used to train a regression model which predicts the future behavior of the time series. Any measured consumption which deviates from the predicted value of the regression model is flagged as anomalous, and this could potentially trigger an alarm in the system. Results are discussed and performances are compared with respect to a simple regression model. Possible applications of this method for real-time anomaly detection are briefly discussed.

Abstract

As a new geothermal heat utilization mode, the research and application of single well pumping system are in the initial stage, so it is necessary to establish the system feasibility evaluation standard. Based on the refraction law, an empirical correlation of the heat affected radius of the aquitard is established in this paper. It is found that the heat affected radius of the aquitard can be characterized by the flow parameters (flow rate, recharge temperature), geological parameters (permeability, porosity, thickness) and physical parameters (thermal diffusivity) of the pumping and recharging layer. It is found that the most sensitive factors of thermal performance are permeability, recharge temperature and circulation flow.

Abstract

Flow induced vibrations (FIVs) of four tandem circular cylinders with roughness strips are numerically studied in Reynolds number range of 30,000≤Re≤100,000. The power conversion and FIV responses are discussed. The VIV initial branch, VIV upper branch, VIV to galloping transition, and galloping are clearly observed for first cylinder. The amplitude ratio curves of third and fourth cylinders show an upward trend and the branches of FIV are not obvious. Both the converted power and conversion efficiency of four cylinders are higher than those of one, two and three cylinders when 62,049≤Re≤90,000. The maximum total converted power reaches to 103W when Re=100,000.

Abstract

Exhaust gas from bright heat treatment furnaces can be used as a fuel for fuel cells because it is rich in hydrogen. However, it contains carbon monoxide (CO); when a CO-containing gas is used as a fuel gas in a proton-exchange membrane fuel cell (PEMFC), cell performance decreases. Therefore, it is necessary to remove contaminants from hydrogen-rich exhaust gas. In this study, the effect of CO contaminants in hydrogen gas on the PEMFC stack performance was firstly evaluated. The experimental results showed a correlation between CO concentration and fuel cell stack performance, wherein performance degraded quickly because of CO poisoning. Furthermore, for improving the performance of the PEMFC stack using the CO-containing hydrogen gas, three methods were evaluated: molecular sieve adsorption, methanation reaction, and air bleeding. These methods were effective against CO poisoning and delayed performance deterioration. In particular, methanation refining was observed to be the most effective method for reducing CO poisoning.