Microgrid with Numerical Weather Information

2014 ◽  
pp. 321-351
Keyword(s):  
Solar Cell ◽  
Diesel Engine ◽  
Energy Supply ◽  
Optimal Operation ◽  
Electricity Production ◽  
Prediction Algorithm ◽  
Numerical Weather ◽  
Weather Information ◽  
Operation Algorithm ◽  
Operation Results

This chapter consists of two sections, ‘Compound Microgrid Installation Operation Planning of a PEFC and Photovoltaics with Prediction of Electricity Production Using GA and Numerical Weather Information’ and ‘Energy Supply Characteristics of a Combined Solar Cell and Diesel Engine System with a Prediction Algorithm for Solar Power Generation’. The optimal operation algorithm of a photovoltaics compound microgrid is developed using numerical weather information (NWI) in the 1st section. The relation between the NWI error characteristics and the operation results of the system is clarified. The 2nd section proposes a prediction algorithm based on a neural network to predict the electricity production from a solar cell. The operation plan for a combined photovoltaics and diesel engine generator is examined using the NN prediction algorithm.

Fuel Reduction Effect of the Solar Cell and Diesel Engine Hybrid System with a Prediction Algorithm of Solar Power Generation

2011 ◽  
pp. 815-839
Author(s):  
Shin’ya Obara
Keyword(s):  
Solar Cell ◽  
Diesel Engine ◽  
Fuel Consumption ◽  
Hybrid System ◽  
Green Energy ◽  
Energy Utilization ◽  
Electricity Production ◽  
Weather Data ◽  
Prediction Algorithm ◽  
Reduction Effect

Green energy utilization technology is an effective means of reducing greenhouse gas emissions. We developed the production-of-electricity prediction algorithm (PAS) of the solar cell. In this algorithm, a layered neural network is made to learn based on past weather data and the operation plan of the hybrid system (proposed system) of a solar cell and a diesel engine generator was examined using this prediction algorithm. In addition, system operation without a electricity-storage facility, and the system with the engine generator operating at 25% or less of battery residual quantity was investigated, and the fuel consumption of each system was measured. Numerical simulation showed that the fuel consumption of the proposed system was modest compared with other operating methods. However, there was a significant difference in the prediction error of the electricity production of the solar cell and the actual value, and the proposed system was shown to be not always superior to others. Moreover, although there are errors in the predicted and actual values using PAS, there is no significant influence in the operation plan of the proposed system in almost all cases.

Fuel Reduction Effect of the Solar Cell and Diesel Engine Hybrid System with a Prediction Algorithm of Solar Power Generation

2010 ◽  
pp. 242-271
Author(s):  
Shin’ya Obara
Keyword(s):  
Solar Cell ◽  
Diesel Engine ◽  
Fuel Consumption ◽  
Hybrid System ◽  
Green Energy ◽  
Energy Utilization ◽  
Electricity Production ◽  
Weather Data ◽  
Prediction Algorithm ◽  
Reduction Effect

Green energy utilization technology is an effective means of reducing greenhouse gas emissions. We developed the production-of-electricity prediction algorithm (PAS) of the solar cell. In this algorithm, a layered neural network is made to learn based on past weather data and the operation plan of the hybrid system (proposed system) of a solar cell and a diesel engine generator was examined using this prediction algorithm. In addition, system operation without a electricity-storage facility, and the system with the engine generator operating at 25% or less of battery residual quantity was investigated, and the fuel consumption of each system was measured. Numerical simulation showed that the fuel consumption of the proposed system was modest compared with other operating methods. However, there was a significant difference in the prediction error of the electricity production of the solar cell and the actual value, and the proposed system was shown to be not always superior to others. Moreover, although there are errors in the predicted and actual values using PAS, there is no significant influence in the operation plan of the proposed system in almost all cases.

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