Hydro-Québec is a vertically integrated utility that produces, transmits and distributes most of the electricity in the province of Québec. The power grid it operates has a particular architecture created by important hydroelectric dams located far North and an extensive 735kV transmission grid that allow the generation to reach the majority of the load that is located thousand of kilometers away in the southern region of Quebec. The specificity of the grid has forced Hydro-Quebec to develop important measures to monitor the stability of the grid. Thoses stability limits are derived from multiple stability phenomena like angular stability, frequency stability or voltage stability. Those phenomena are highly non-linear but have to be taking into account when doing generation planning and operation. Since generation planning and operation algorithms normally use mixed integer linear programming formulation, Hydro-Quebec had to develop novel approach to model stability limits into its tools for planning and operating the generation. RALPH software is a tool specifically developped to solve the unit-commitment problem under hydraulic and transient stability constraints.

This work addresses the Optimal Transmission Switching (OTS) problem in electricity networks, which aims to find an optimal power grid topology that minimizes system operation costs while satisfying physical and operational constraints. Existing methods typically convert the OTS problem into a Mixed-Integer Linear Program (MILP) using big-M constants. However, the computational performance of these approaches relies significantly on the tightness of these big-Ms. In this work, we propose an iterative tightening strategy to strengthen the big-Ms by efficiently solving a series of bounding problems that account for the economics of the OTS objective function through an upper-bound on the generating cost. We also discuss how the performance of the proposed tightening strategy is enhanced if reduced line capacities are considered. Using the 118-bus test system we demonstrate that the proposed methodology outperforms existing approaches, offering tighter bounds and significantly reducing the computational burden of the OTS problem.

Hydro Quebec distribution network faces many planning and operational challenges that can be addressed using operational research. The focus is to adequately prioritize the network reinforcements and to improve the system reliability, i.e., reduce the interruption frequency and duration. In Hydro Quebec research center, we try to address these objectives through the innovation project SCÉNARIO. We are studying the some of the common distribution system optimization problems, including:
- Controlled recharge of electrical vehicles
- Residential heating control through aggregator
- Staggered client reconnection after an outage
- Reliability-based positioning of feeder sectionalizers
- Optimal micro-grid control
- Distribution network capacity expansion
One of the particularities that Hydro Quebec network has compared to other utilities is the winter Cold Load Pick-up (CLPU). Due to the large and growing prevalence of electric heating and a significant projected EV load, the CLPU has become the most important criterion for the distribution system planning. Therefore, all the above-mentioned optimization problems must be casted considering the CLPU and the associated customer load models.

Hydro-Québec (HQ), one of the world’s largest hydropower producers, generates electricity to supply the Québec market and sells its excess output on wholesale markets. At HQ a variety of tools and methods have been implemented to jointly analyze operational scheduling and contract management. Stochastic Dual Dynamic Programming (SDDP) is one of the algorithmic solutions used to determine the operating policies of our extensive energy infrastructure. These operational policies encompass among others the evaluation of load factor contracts, commonly known as flexible contracts. In these agreements, terms regarding price, energy, and maximum power are predefined, yet usage remains adaptable. For instance, contracts such as CHPE (Champlain Hudson Power Express) and NECEC (New England Clean Energy Connect) are integrated into the SDDP framework represented as state variable. These contracts impose restrictions on both annual energy volume and instant power output. This decision support system allows as to better evaluate our risk associated to inflow uncertainty.