The largest two-shaft gas turbine in the United States has been operated in combined cycle service at the Oklahoma Gas and Electric Company Horseshoe Lake Station since May 1963. The same design unit has been operated in peaking and stand-by service at Public Service Electric and Gas (Essex, N. J.) station since December 1963. The 0.G & E. unit has a NEMA rating of 25 Mw base load. The PSEG uni...

Homes, buildings and industrial facilities together represent nearly 100 % of the load on the electric grid. Beyond load, these facilities comprise a significant amount of electricity generation and thermal storage. These customer-owned load, storage and generation resources must be made responsive to needs of the electric grid in order to enable the Smart Grid. At issue is the best way to acco...

Abstract— In this paper, a new model is proposed for optimal planning of daily charging and power delivering from/to the power system considering time schedule of trips for electric vehicles. In this model, trips are categorized in job, shopping, educational, and pleasure and possible times to charge/injection are considered based on type of trip and limitations of charging stations. In the opt...

Estimation of Productivity in Korean Electric Power Plants: A Semiparametric Smooth Coefficient Model This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to mode...

This paper presents a short-term electric load forecasting method based on Autoregressive Tree Algorithm and Rough Set Theory. Firstly, Rough Set Theory was used to reduce the testing properties of Autoregressive Tree. It can optimize the Autoregressive Tree Algorithm. Then, Autoregressive Tree Model of Short-term electric load forecasting is set up. Using Rough Set Theory, the attributes will ...

On one hand, an all-electric ship may take over and support operator tasks in order to improve the operational effectiveness and efficiency on board of a ship. At the other hand, information processing demands seem to increase substantially for the operators in such a ship. Recently, a Cognitive Task Load analysis method was developed for the design of operator tasks and computer support, aimin...

This paper proposes a novel neural model to the problem of short-term load forecasting. The neural model is made up of two self-organizing map nets | one on top of the other. It has been successfully applied to domains in which the context information given by former events plays a primary role. The model was trained and assessed on load data extracted from a Brazilian electric utility. It was ...

Kernel-based methods, such as support vector regression (SVR), have demonstrated satisfactory performance in short-term load forecasting (STLF) application. However, the good performance of kernel-based method depends on the selection of an appropriate kernel function that fits the learning target, unsuitable kernel function or hyper-parameters setting may lead to significantly poor performance...

This paper reports on work the Consortium for Electric Reliability Technology Solutions (CERTS) has been pursuing to hasten the arrival of meaningful load participation in competitive electricity markets. The activities include: experimental economic analysis of the effect of price responsive load in reducing market prices and price volatility; assessments of emerging demand response programs a...

This paper focuses on the optimal intraday scheduling of a distribution system that includes renewable energy (RE) generation, energy storage systems (ESSs), and thermostatically controlled loads (TCLs). This system also provides time-of-use pricing to customers. Unlike previous studies, this study attempts to examine how to optimize the allocation of electric energy and to improve the equilibr...