Energy Supply Characteristics of a Combined Solar Cell and Diesel Engine System with a Prediction Algorithm for Solar Power Generation
The production of electricity from the solar cells continues to attract interest as a power source for distributed energy generation. It is important to be able to estimate solar cell power to optimize system energy management. This paper proposes a prediction algorithm based on a neural network (NN) to predict the electricity production from a solar cell. The operation plan for a combined solar cell and diesel engine generator system is examined using the NN prediction algorithm. Two systems are examined in this paper: one with and one without a power storage facility. Comparisons are presented of the results from the two systems with respect to the actual calculations of output power and the predicted electricity production from the solar cell. The exhaust heat from the engine is used to supply the heat demand. A back-up boiler is operated when the engine exhaust heat is insufficient to meet the heat demand. Electricity and heat are supplied to the demand side from the proposed systems, and no external sources are used. When the NN production-of-electricity prediction was introduced, the engine generator operating time was reduced by 12.5% in December and 16.7% for March and September. Moreover, an operation plan for the combined system exhaust heat is proposed, and the heat output characteristics of the back-up boiler are characterized.
- Journal of Power and Energy Systems
Journal of Power and Energy Systems 4(1), 27-38, 2010