Optimization of the Garzan Hydropower System operations

Abstract

Through the rapid development of the watersheds in Turkey with projects developed by incorporated companies, a problem has arisen of how to operate a cascade reservoir system composed of state-and private sector-owned reservoirs in terms of the volume and timing of water releases to meet downstream water demands. This study presents a catchment-based optimization model based on inflow forecast with frequent updating for the integrated operation of hydropower plants under various sales methods. The model is formulated in terms of nonlinear programming (NLP) on a monthly basis for a 1-year period to assess the production strategies of the system reservoirs for that year. This model provides the basic constraints on the reservoir volume for daily and hourly optimization procedures. Forecasted flows are generated using seasonal autoregressive integrated moving average (ARIMA) models based on historical flow values. The proposed model is tested on the Garzan Hydropower System using historical, mean, and forecasted flow values. The results show that the integrated operation plan and improvement in the accuracy of inflow forecasts yield economic benefits as a consequence of optimal reservoir operation.