Optimal siting and sizing of demand response in a transmission constrained system with high wind penetration

This paper describes algorithms that use demand-side management to address large-scale integration of wind power. In particular, demand response (DR) is used to manage wind power intermittency by shifting the time that electrical power system loads occur in response to real-time prices and wind availability. An economic dispatch with transmission, DR capacity and operational constraints is used to model the operation of a transmission constrained system with a high penetration of wind power. This optimization model is used to determine the optimal sizing and distribution of DR given a fixed budget for customer incentives and the installation of enabling technology. We demonstrate the effectiveness of the operational model based on a simple PJM 5-bus system and an IEEE 118-bus system. Simulation results show that transmission constraints have a greater effect on sizing of DR capacity than the location of wind power, which means that buses electrically close to congested lines tend to have higher incentives to deploy DR resources than other buses. The second part of the work examines optimal siting of technology that enables DR based on the frequency of DR based load changes, which are generally a function of the network location.     

The potential of energy flexibility of space heating and cooling in Portugal

This study assesses the potential of energy flexibility of space heating and cooling for a typical household under different geographical conditions in Portugal. The proposed approach modifies the demand through the optimization of the thermostat settings using a genetic algorithm to reduce either operational costs or interaction with the grid. The results show that the used energy flexibility indicator expresses the available potential and that flexibility depends on several factors, namely: i) thermal inertia of the archetypical household; ii) the time of use electricity tariffs; iii) users’ comfort boundaries; and iv) the geographical location of the houses.     

Demand response for home energy management system

The optimization of energy consumption, with consequent cost reduction, is one of the main challenges for the present and future smart grid. Demand response (DR) program is expected to be vital in home energy management system (HEMS) which aims to schedule the operation of appliances to save energy costs by considering customer convenience as well as characteristics of electric appliances. The DR program is a challenging optimization problem especially when the formulations are non-convex or NP-hard problems. In order to solve this challenging optimization problem efficiently, an effective heuristic approach is proposed to achieve a near optimal solution with low computational costs. Different from previously proposed methods in literatures which are not suitable to be run in embedded devices such as a smart meter. The proposed algorithm can be implemented in an embedded device which has severe limitations on memory size and computational power, and can get an optimal value in real-time. Numerical studies were carried out with the data simulating practical scenarios are provided to demonstrate the effectiveness of the proposed method.     

预测油气田产量的β模型

通过对油气田产量变化规律进行系统研究，推导建立了预测油气田产量的β模型。该模型不但可以预测油气田产量、累积产量随生产时间的变化，而且可以预测可采储量、最高年产量及其发生的时间。实例检验该模型是可信的。     

Validity of Three Measures of Communication for Predicting Relationship Adjustment and Stability Among a Sample of Young Couples.

The goal of this study was to examine whether data from 3 different measures of communication (i.e., self-report, quasi-observational, and observational) can predict relationship adjustment and stability 1 year later when used conjointly in a sample of 62 young couples. The 3 measures of communication were the Communication Skills Test-Revised (CST-R), the Communication Box (CB), and the Demand/Withdraw Pattern Questionnaire (DWPQ). Through hierarchical multiple regression analyses, results revealed that the CST-R and the DWPQ predict both genders' relationship adjustment 1 year later when used conjointly. Logistic regression analyses revealed that none of the measures of communication significantly predicted relationship stability. In conclusion, the combination of the CST-R and the DWPQ appears to be useful for longitudinally predicting relationship adjustment. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

我国石油开采与油井管生产概述

概略介绍了我国石油开采及其专用管材的需求情况以及油井管的生产规划和要求,对发展国内油井管特别是焊接油井管生产提出了建议。     

河口海岸水文信息处理系统

应用Visual Basic6.0应用程序、Microsoft Access数据库和FORTRAN语言开发的河口海岸水文信息处理系统，具有水文现场资料整编功能、利用分潮优化技术的潮汐调和分析及预报功能，且计算工作量相对较小，预报精度高。     

关于移动平均过程两系数的推导

对经济预测方法中两公式给出了证明，两公式的系数被显式推导出来，这两个公式是时间序列模型公式，广泛用于经济预测之中，但文献上很难找到推导过程，本文的证明是基本的，无需高深数学知识即可理解．     

A novel data-driven approach to support decision-making during production scale-up of assembly systems

In today's manufacturing settings, a sudden increase in the customer demand may enforce manufacturers to alter their manufacturing systems either by adding new resources or changing the layout within a restricted time frame. Without an appropriate strategy to handle this transition to higher volume, manufacturers risk losing their market competitiveness. The subjective experience-based ad-hoc procedures existing in the industrial domain are insufficient to support the transition to a higher volume, thereby necessitating a new approach where the scale-up can be realised in a timely, systematic manner. This research study aims to fulfill this gap by proposing a novel Data-Driven Scale-up Model, known as DDSM, that builds upon kinematic and Discrete-Event Simulation (DES) models. These models are further enhanced by historical production data and knowledge representation techniques. The DDSM approach identifies the near-optimal production system configurations that meet the new customer demand using an iterative design process across two distinct levels, namely the workstation and system levels. At the workstation level, a set of potential workstation configurations are identified by utilising the knowledge mapping between product, process, resource and resource attribute domains. Workstation design data of selected configurations are streamlined into a common data model that is accessed at the system level where DES software and a multi-objective Genetic Algorithm (GA) are used to support decision-making activities by identifying potential system configurations that provide optimum scale-up Key Performance Indicators (KPIs). For the optimisation study, two conflicting objectives: scale-up cost and production throughput are considered. The approach is employed in a battery module assembly pilot line that requires structural modifications to meet the surge in the demand of electric vehicle powertrains. The pilot line is located at the Warwick Manufacturing Group, University of Warwick, where the production data is captured to initiate and validate the workstation models. Conclusively, it is ascertained by experts that the approach is found useful to support the selection of suitable system configuration and design with significant savings in time, cost and effort.     

从吊裆裤看服装审美需求

裆部低垂、臀围剪裁宽松,松松垮垮的吊裆裤,成为时尚潮人钟爱的流行服饰。裆部松松紧紧,深深浅浅的外观变化,并不仅是几个数字的细微差别,它所反映的是现代人的审美意识和审美需求的变化。即使在这个数字化时代里,人们也无法用数字代替审美。只有充分思考和了解服装背后人的心理需求,这样我们才能掌握方向,设计出能够符合时代,满足消费者需求的服装。