Long-term optimal coordination of hydro-wind-thermal energy generation using stochastic dynamic programming

ABSTRACT

Clean alternative energy and a greater focus on climate change aim to increase the integration of Renewable Energy Sources (RES) into power system networks. As a relatively inexpensive renewable energy, wind energy is integrated into the electrical network to reduce its operating costs. A long-term optimal scheduling model for hydro-wind-thermal in a hybrid generation system is established to find the minimum cost trajectory of energy generation at each period under various constraints. Based on the proposed model and different types of power plants, the original complex problem decomposed into hydro-wind-thermal subproblems. The stochastic Dynamic programming technique (SDP) is employed to solve the complete optimization. In this research, the SDP technique is preferred. This technique handles multistage decision processes by splitting problems down into sequential stages. Because it can incorporate nonlinear and stochastic features into a dynamic programming problem, it has been successful in this hybrid system. A penalty factor was added to the model to reduce outflow variations. As can be seen from the results, outflows are very high during peak demand periods and very low during high inflows. Furthermore, the cost decreases as demand increases, from 40,082.26 $/$\mathit{GWh}$ in May when demand is 10,275 $\mathit{Gwh}$ to 16,536.32 $/$\mathit{GWh}$ in January when demand is 17,503 $\mathit{Gwh}$.

KEYWORDS:

• Long-term coordination
• hybrid hydro-wind thermal energy
• SDP techniques
• stochastic

Disclosure statement

No potential conflict of interest was reported by the author(s).