scholarly journals Weather forecasting error in solar energy forecasting

2017 ◽  
Vol 11 (10) ◽  
pp. 1274-1280 ◽  
Author(s):  
Hossein Sangrody ◽  
Morteza Sarailoo ◽  
Ning Zhou ◽  
Nhu Tran ◽  
Mahdi Motalleb ◽  
...  
Keyword(s):  
Solar Energy ◽  
Weather Forecasting ◽  
Energy Forecasting ◽  
Forecasting Error

scholarly journals An Optimization-Based Supervisory Control and Coordination Approach for Solar-Load Balancing in Building Energy Management

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1215
Author(s):  
James Allen ◽  
Ari Halberstadt ◽  
John Powers ◽  
Nael H. El-Farra
Keyword(s):  
Solar Energy ◽  
Energy Use ◽  
Weather Forecasting ◽  
Energy Generation ◽  
Building Energy ◽  
Objective Functions ◽  
Forecasting Accuracy ◽  
Electricity Cost ◽  
The Impact ◽  
Building Loads

This work considers the problem of reducing the cost of electricity to a grid-connected commercial building that integrates on-site solar energy generation, while at the same time reducing the impact of the building loads on the grid. This is achieved through local management of the building’s energy generation-load balance in an effort to increase the feasibility of wide-scale deployment and integration of solar power generation into commercial buildings. To realize this goal, a simulated building model that accounts for on-site solar energy generation, battery storage, electrical vehicle (EV) charging, controllable lighting, and air conditioning is considered, and a supervisory model predictive control (MPC) system is developed to coordinate the building’s generation, loads and storage systems. The main aim of this optimization-based approach is to find a reasonable solution that minimizes the economic cost to the electricity user, while at the same time reducing the impact of the building loads on the grid. To assess this goal, three objective functions are selected, including the peak building load, the net building energy use, and a weighted sum of both the peak load and net energy use. Based on these objective functions, three MPC systems are implemented on the simulated building under scenarios with varying degrees of weather forecasting accuracy. The peak demand, energy cost, and electricity cost are compared for various forecast scenarios for each MPC system formulation, and evaluated in relation to a rules-based control scheme. The MPC systems tested the rules-based scheme based on simulations of a month-long electricity consumption. The performance differences between the individual MPC system formulations are discussed in the context of weather forecasting accuracy, operational costs, and how these impact the potential of on-site solar generation and potential wide-spread solar penetration.

scholarly journals An ANFIS‐based model for solar energy forecasting and its smart grid application

2019 ◽  
Vol 1 (5) ◽  
Author(s):  
Gulnar Perveen ◽  
Mohammad Rizwan ◽  
Nidhi Goel
Keyword(s):  
Solar Energy ◽  
Smart Grid ◽  
Energy Forecasting ◽  
Grid Application

scholarly journals The Use of Gridded Model Output Statistics (GMOS) in Energy Forecasting of a Solar Car

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1984
Author(s):  
Christiaan Oosthuizen ◽  
Barend Van Wyk ◽  
Yskandar Hamam ◽  
Dawood Desai ◽  
Yasser Alayli
Keyword(s):  
Weather Forecasting ◽  
Forecast Error ◽  
Weather Prediction ◽  
Weather Conditions ◽  
Model Output ◽  
Energy Forecasting ◽  
Weather Forecasts ◽  
Improved Performance ◽  
Model Output Statistics ◽  
Auxiliary Services

For many years, primary weather forecasting services (Global Forecast System (GFS) and the European Centre for Medium-Range Weather Forecasts (ECMWF)) have been made available to the public through global Numerical Weather Prediction (NWP) models estimating a multitude of general weather variables in a variety of resolutions. Secondary services such as weather experts Meteomatics AG use data and improve the forecasts through various methods. They tailor for the specific needs of customers in the wind and solar power generation sector as well as data scientists, analysts, and meteorologists in all areas of business. These auxiliary services have improved performance and provide reliable data. However, this work extended these auxiliary services to so-called tertiary services in which the weather forecasts were further conditioned for the very niche application environment of mobile solar technology in solar car energy management. The Gridded Model Output Statistics (GMOS) Global Horizontal Irradiance (GHI) model developed in this work utilizes historical data from various ground station locations in South Africa to reduce the mean forecast error of the GHI component. An average Root Mean Square Error (RMSE) improvement of 11.28% was shown across all locations and weather conditions. It was also shown how the incorporation of the GMOS model could have increased the accuracy in regard to the State of Charge (SoC) energy simulation of a solar car during the Sasol Solar Challenge 2018 and the possible range benefits thereof.

A current perspective on the accuracy of incoming solar energy forecasting

2019 ◽  
Vol 70 ◽  
pp. 119-144 ◽  
Author(s):  
Robert Blaga ◽  
Andreea Sabadus ◽  
Nicoleta Stefu ◽  
Ciprian Dughir ◽  
Marius Paulescu ◽  
...  
Keyword(s):  
Solar Energy ◽  
Energy Forecasting ◽  
Current Perspective ◽  
A Current
Sign in / Sign up

Export Citation Format

Share Document