Inga Umbraško

Algorithm of smart control system operation of small hydropower plant

The small-scale hydro power plant (SHPP) operating regime optimization is considered from the point of view of increasing the income during its whole day work. The optimization problem of SHPP solution using dynamic programming and generalized reduced gradient method is made. In addition to the input data of SHPP Nord Pool Spot market price changing graph for the considered period is used. The SHPP optimization was made to increase efficiency of its operation by optimal water usage distribution. The obtained results demonstrate the advantages of the generalized reduced gradient method in comparison with dynamic programming for the optimization of SHPP regime by the income amount.

Modeling of the generating company behavior in energy and reserve market

In the market conditions generating companies put more attention to the question of energy and reserve distribution or purchasing. Each generating company tries to reduce its costs of energy production for increasing its profit from participation in the market. Thus, the question of energy and reserve distribution between generating stations and purchased amount is one of the key aspects of generating company behavior. In article the algorithm of generating company costs minimization, considering spot market and bilateral trading, is proposed. As criteria of optimization task cost minimization function is used. As variables in the model are used: energy, reserve, participation of the power plant in the market (both for reserve providing and for energy production). The algorithm operability was approved on example.

The small hydropower plant operating regime optimization by the income maximization

The problem of regime management of small-scale hydro power plant (SHPP) is considered from the point of view of getting the maximum income during the 24 hours. Statement of the problem and its solution using a non-linear programming solver is made. In addition to the input data of SHPP Nord Pool Spot market price changing graph for the considered period is used. The SHPP operating options are compared under various conditions of water resources amount. The obtained results demonstrate the feasibility of the use of common opportunities of SHPP control system intellectualization for the optimization of their regime by the income amount.

Biogas power plant operation considering limited biofuel resources

The problem of operational planning of a biogas combined heat and power (CHP) plant under conditions of limited biofuel resources is analyzed in this paper. The power plant operation mode depends on the biomass amount and its delivery. Consideration of parameters with high dispersion, such as the ambient temperature, thermal energy consumption and energy price, makes the problem solution much more complicated and requires new algorithms and software tools. This paper proposes an algorithm of stochastic optimization to estimate the maximum value of income by taking into account the random nature of variables. When the biomass resource is limited, the need of its optimal distribution for all the time periods considered becomes of top importance. In this paper, a case study is conducted on a realistic biogas CHP plant that demonstrates the feasibility of our stochastic optimization algorithm. It is concluded that the proposed algorithm can increase the efficiency of the biogas power plant operations under conditions of limited resources. The main distinction of this paper is that a biogas CHP plant optimization model is considered from the point of view of income maximization under market conditions taking into account the limited biomass resources.

Small hydropower plants operations optimization in the market conditions

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.

Hydropower Plant Regime Management According to the Market Conditions

The dimensions and significance of the modern systems prove the necessity to change principles of the systems management. In order to decrease carbon dioxide (CO2) emissions, fight climate change, not adhere to fuel resources and increase energy security while decreasing its dependences on foreign countries, many country governments took actions to exploit its domestic resources and raise the renewable energies in the electricity production, that is why renewable energy is a key issue in today’s world and may continue to play a globally essential role in the future. Turkey has a large renewable energy potential it is still on a development process and has relevant natural hydropower potential, which is about 1.1 % of the worldwide and 13.75 % of the European potential. 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 huge level of uncertainty which is the water power introduces into the power system. Hydropower stations (20 MW or less) operation effectiveness under the conditions of market relations is defined by means of income value that is determined during the calculation period. This income can be obtained in the regime providing as large as possible HPP electric energy production with particular water consumption within a considered period. The value of these incomes can be calculated in accordance with pre-set market prices for electric energy within the calculated period. This paper addresses optimization techniques, model applications, and operational issues. Our goal was devoted to the problem of small HPP control regimes optimization. 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. The developed forecasting and optimization technics are established on optimization of the Cobanli HPP in Turkey considering hydropower production and flood control. Optimization of powerhouse regimes operation rules provides optimal solutions that have a larger hydropower potential compared to the present regulations. It’s concluded that real-time optimization in normal flow situations provide solutions that trades-off the immediate and the future value of hydropower production. We developed a model for hydropower plant scheduling under market and fixed electricity price and water inflow rates for to achieve greatest economic benefit.