Stochastic short-term hydropower planning with inflow scenario trees

Abstract

This paper presents an optimization approach to solve the short-term hydropower unit commitment and loading problem with uncertain inflows. A scenario tree is built based on a forecasted fan of inflows, which in turn comes from the weather forecast and the historical weather realizations. The tree-building approach seeks to minimize the nested distance between the stochastic process of historical inflow data and the multistage stochastic process represented in the scenario tree. A two-phase multistage stochastic model is used to solve the problem. One of the main features of the modeling of the problem is that the effect of varying water head on production is carefully heeded. The proposed approach is tested on a 31 day rolling horizon with daily forecasted inflows for three power plants situated in the province of Quebec, Canada, that belong to the company Rio Tinto.

Scenario-Tree Modeling for Stochastic Short-Term Hydropower Operations Planning

“…The loading problem maximizes the energy production in the first stage and expected energy production in the future, subject to water balance constraints and hydropower production functions selection. The entire model is presented in Section 4.2 of (Séguin et al, 2015).…”

“…Without presenting the mathematical modeling of the problem, as it is not the scope of the present research, the contents of this model is explained for the reader to understand its outcome. In more recent work, the authors have also considered stochastic inflows in the reservoirs (Séguin et al, 2015). A scenario tree is used to represent the uncertain inflows and therefore, the sstul model is solved for each scenario tree node.…”

“…As the scenario tree generation method (Séguin et al, 2015) used in this paper requires input parameters, this work studies if there is an energy production gain when the scenario tree parameters are optimized in an optic of maximizing the energy production throughout the rolling-horizon. The rolling-horizon scheme, consisting of scenario tree generation and short-term hydropower optimization is embedded within a blackbox optimization model.…”

“…Deterministic models (Santo and Costa, 2016) in which there are no uncertainties, as well as stochastic short-term hydropower models (Belsnes et al, 2016) have recently been proposed. In this paper, uncertain inflows are considered, based on the authors previous work (Séguin et al, 2015).…”

Detailed long‐term hydro‐thermal scheduling for expansion planning in the Nordic power system

“…This process can be resembled in rolling horizon simulator scheme, as demonstrated by the authors in [23,24], combining short-term decisions and medium-term strategy computation in sequence. This type of scheme, which is often linked to the framework of model predictive control, was proposed for the LTHTS problem in [25][26][27].…”