In a truly smart grid, system load would be known in advance with a high degree of confidence. Currently, this goal of “smart forecasting” is far from being realized. In the Pacific Gas and Electric (PG&E) aggregation area managed by the California Independent System Operator (ISO), the root mean squared day-ahead forecast error was about 3.8 percent of mean actual load over the period 1 April ...

Gas demand possesses dual property of growing and seasonal fluctuation simultaneously, it makes gas demand variation possess complex nonlinear character. From previous studies know single model for nonlinear problem can’t get good results but accurately gas forecast were essential part of an efficient gas system planning and operation. In recent years, lots of scholar put forward combination mo...

Prediction of residential natural gas consumption in 20 next years was performed in this paper. Artificial neural network (ANN) was used to predict the natural gas in the Kerman, the biggest province in the Iran. The Kerman is included with ten important cities where gas consumption was estimated in each city. The minimum temperature in each year, population growth rate and number of each year ...

the main purpose of the present research is to determine the relationship between the management earnings forecast errors and conservatism level and then surveying about the effects of forecast difficulty, and external financing on this relationship. regarding this, the financial information related to 147 stock firms, available during the period of study (2003-2015) were collected and analyzed...

this research presents a mathematical model for the optimal allocation of oil and gas to different sectors in iran using operations research techniques. sectors are residential, commercial, transportation, industries, agriculture, exports, injection to oil reservoirs and power plants as a secondary energy producer. optimal allocation of energy resources to end-users from 2011 to 2021 has been d...

of a thesis at the University of Miami. Any prediction based on numerical model contains uncertainty. The Deepwater Horizon oil spill forecast is a challenge due to the difficulty in measuring key parameters and the complexity in predicting the oil fate. Monte-Carlo (MC) sampling are applied to quantify the forecast uncertainties in an integral oil plume model simulating the Deepwater Horizon o...

[1] Knowledge of trace gas fluxes at the land surface is essential for understanding the impact of human activities on the composition and radiative balance of the atmosphere. An ability to derive fluxes at the regional scale (on the order of 10–10 km), at the scale of ecosystems and political borders, is crucial for policy and management responses. Lagrangian (‘‘air mass-following’’) aircraft ...