Title :
Small hydropower plants operations optimization in the market conditions
Author :
Coban, Hasan H. ; Varfolomejeva, Renata ; Sauhats, Antans ; Umbrasko, Inga
Author_Institution :
Inst. of Power Eng., Riga Tech. Univ., Riga, Latvia
Abstract :
This paper intends to give an overview and identifies best practice designs for European feed-in tariffs targeted to support renewable generation. Furthermore, it introduces and compares feed-in premium designs of different European countries. The main purpose of this work is to develop optimal short-term planning models for price taker hydropower producer working in the existing regimes. Those models have to deal with the high level of uncertainty which is the water power introduces into the power system. We intend to provide guidance in decision-making aimed at maximizing the profit. A detailed analysis is made of a simpler reservoir configuration, which indicates that even though the problem is nonlinear, a bang-bang type of control is optimal, where the power stations are operated at maximum rates of flow. Some simple relationships between price and timing of decisions are calculated directly. A numerical algorithm is also developed. The task of a small HPP operation regime is solved for the maximum income within the cases of the known variation of prices at the market. An optimization tool known as generalized reduced gradient method for nonlinear optimization tasks is used to plan hydropower production under uncertainties.
Keywords :
decision making; hydroelectric power stations; optimisation; power generation planning; power markets; European feed-in tariffs; bang-bang control; generalized reduced gradient method; hydropower production; market conditions; nonlinear optimization; optimal short-term planning models; power stations; power system; renewable generation; reservoir configuration; small hydropower plants operations optimization; water power; Electricity; Hydroelectric power generation; Optimization; Renewable energy sources; Reservoirs; games theory; hydropower generation; income maximization; market conditions;
Conference_Titel :
Information, Electronic and Electrical Engineering (AIEEE), 2014 IEEE 2nd Workshop on Advances in
Conference_Location :
Vilnius
DOI :
10.1109/AIEEE.2014.7020328