Improving Short-Term Electricity Price Forecasting Using Day-Ahead LMP with ARIMA Models

Short-term electricity price forecasting has become important for demand side management and power generation scheduling. Especially as the electricity market becomes more competitive, a more accurate price prediction than the day-ahead locational marginal price (DALMP) published by the independent system operator (ISO) will benefit participants in the market by increasing profit or improving load demand scheduling. Hence, the main idea of this paper is to use autoregressive integrated moving average (ARIMA) models to obtain a better LMP prediction than the DALMP by utilizing the published DALMP, historical real-time LMP (RTLMP) and other useful information. First, a set of seasonal ARIMA (SARIMA) models utilizing the DALMP and historical RTLMP are developed and compared with autoregressive moving average (ARMA) models that use the differences between DALMP and RTLMP on their forecasting capability. A generalized autoregressive conditional heteroskedasticity (GARCH) model is implemented to further improve the forecasting by accounting for the price volatility. The models are trained and evaluated using real market data in the Midcontinent Independent System Operator (MISO) region. The evaluation results indicate that the ARMAX-GARCH model, where an exogenous time series indicates weekend days, improves the short-term electricity price prediction accuracy and outperforms the other proposed ARIMA modelsComment: IEEE PES 2017 General Meeting, Chicago, I

An MAS Based Energy Management System for a Stand-Alone Microgrid at High Altitude

A multi-agent system based energy management system (EMS) is proposed in this paper for implementing a PV-small hydro hybrid microgrid (MG) at high altitude. Based on local information, the distributed generation (DG) sources in the MG are controlled via the EMS to achieve efficient and stable system operation. Virtual bidding is used to quickly establish the scheduling of system operation and capacity reserve. In addition, real-time power dispatches are carried out through model predictive control to balance load demand and power generation in the MG. The dynamic model and the energy management strategy of the MG have been simulated on a RTDS–PXI joint real-time simulation platform. The simulation results show that the proposed energy management and control strategy can optimally dispatch the DG sources in the MG to achieve economic and secure operations of the whole system

A Review of Active Management for Distribution Networks: Current Status and Future Development Trends

Driven by smart distribution technologies, by the widespread use of distributed generation sources, and by the injection of new loads, such as electric vehicles, distribution networks are evolving from passive to active. The integration of distributed generation, including renewable distributed generation changes the power flow of a distribution network from unidirectional to bi-directional. The adoption of electric vehicles makes the management of distribution networks even more challenging. As such, an active network management has to be fulfilled by taking advantage of the emerging techniques of control, monitoring, protection, and communication to assist distribution network operators in an optimal manner. This article presents a short review of recent advancements and identifies emerging technologies and future development trends to support active management of distribution networks

A New Transfer Impedance Based System Equivalent Model for Voltage Stability Analysis

This paper presents a new transfer impedance based system equivalent model (TISEM) for voltage stability analysis. The TISEM can be used not only to identify the weakest nodes (buses) and system voltage stability, but also to calculate the amount of real and reactive power transferred from the generator nodes to the vulnerable node causing voltage instability. As a result, a full-scale view of voltage stability of the whole system can be presented in front of system operators. This useful information can help operators take proper actions to avoid voltage collapse. The feasibility and effectiveness of the TISEM are further validated in three test systems

Research Progress and Prospect Analysis of the Application of Flax Lignans

ABSTRACTLignan is one of the important components in flaxseed and has been paid increasing attention owing to its special therapeutic effects on many diseases. Herein, we retrieved the recently published studies on flaxseed lignan through the Web of Science to give a comprehensive understanding of the research advances of flaxseed lignan. Results showed that flaxseed lignan has been extensively applied to many industries, such as food, medicine, and cosmetics. Flaxseed lignan has great potential in the pharmaceuticals industry, many studies have proven its performance on antioxidant, anti-tumor, anti-cardiovascular disease, prevention of osteoporosis and diabetes. However, the depths of the research need to be enhanced and the mechanisms of lignan in curing each disease should be further clarified. Flaxseed lignan presents good performance in anti-skin sagging, maintains skin elasticity and radiance, and significantly delays the aging process. In addition, flaxseed lignan has been used in functional foods and dietary supplements in the food industry. Therefore, as a multiuse material, flaxseed lignan will play important roles in the product and development and utilization of food, medicine, and cosmetic and, accordingly, its source plant——flax, will also receive more attention in the future

Exploring the relationship between different types of reference group influence and young consumers' health tourism intention

Despite the many achievements in health tourism, relatively few studies conducted on the health tourism consumption decisions of young consumers. This study primarily investigates how different types of reference group influence affect young consumers' health tourism intentions. Based on the theoretical framework of Stimuli-Organism-Response (SOR), a mediation model including perceived value was constructed and structural equation modeling was used to analyze the relationship between the types of reference group influence, perceived value, and health tourism intention. The results showed that both informational influence and utilitarian influence in the reference group influence have a positive impact on health tourism intention. Of these, informational influence is greater. Secondly, perceived value also has a positive effect on consumers' health tourism intention and plays a mediating role between the reference group influence and the health tourism intention. The findings contribute to our understanding of the impact of different types of reference group influence on health tourism intentions and enrich the application of SOR theory. The findings have implications for promoting healthy tourism consumption among young consumers

PCA-Based Denoising Algorithm for Outdoor Lidar Point Cloud Data

Due to the complexity of surrounding environments, lidar point cloud data (PCD) are often degraded by plane noise. In order to eliminate noise, this paper proposes a filtering scheme based on the grid principal component analysis (PCA) technique and the ground splicing method. The 3D PCD is first projected onto a desired 2D plane, within which the ground and wall data are well separated from the PCD via a prescribed index based on the statistics of points in all 2D mesh grids. Then, a KD-tree is constructed for the ground data, and rough segmentation in an unsupervised method is conducted to obtain the true ground data by using the normal vector as a distinctive feature. To improve the performance of noise removal, we propose an elaborate K nearest neighbor (KNN)-based segmentation method via an optimization strategy. Finally, the denoised data of the wall and ground are spliced for further 3D reconstruction. The experimental results show that the proposed method is efficient at noise removal and is superior to several traditional methods in terms of both denoising performance and run speed