Electricity demand and price forecasting model for sustainable smart grid using comprehensive long short term memory

Dynamic Hybrid Model for Short-Term Electricity Price Forecasting

Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing ...

Forecasting Electricity Price Using Seasonal ARIMA model and Implementing RTP Based Tariff in Smart Grid

-A Smart Grid has a two-way digital communication system and it encourages customers to actively participate in different types of Demand Response (DR) programs. In the Smart Grid market, both the supplier and broker agent earn profit while distributing the electrical energy. They have to balance the supply and demand during the distribution of energy. They also participate in energy trading to...

Short-term electricity demand forecasting using double seasonal exponential smoothing

This paper considers univariate online electricity demand forecasting for lead times from a half-hour-ahead to a day-ahead. A time series of demand recorded at half-hourly intervals contains more than one seasonal pattern. A within-day seasonal cycle is apparent from the similarity of the demand profile from one day to the next, and a within-week seasonal cycle is evident when one compares the ...

Long Term Electricity Demand Forecasting with Multi-agent-Based Model

Australia's long-term electricity demand forecasting using deep neural networks

Accurate prediction of long-term electricity demand has a significant role in demand side management and electricity network planning and operation. Demand over-estimation results in over-investment in network assets, driving up the electricity prices, while demand underestimation may lead to under-investment resulting in unreliable and insecure electricity. In this manuscript, we apply deep ne...