To exploit the massive solar energy available in the region, photovoltaic plants have been built in the mountain areas in Southwest China, coexisting with many small cascaded run-of-the-river hydropower plants, interconnected by short-distance transmission lines. Network constraints inside these systems are often negligible. However, due to the volatile nature of solar power and the weak connection to the external power grid, without proper coordination, solar power curtailment and water spillage are inevitable. To address this issue, this paper proposes an ultra-short-term stochastic generation control method for cascaded hydropower to mitigate solar power volatility. Two technical challenges are specifically addressed: to tackle the time-varying stochastic volatility of solar power, the Ito process model is introduced; to characterize the spatial-temporal hydraulic coupling of the cascaded hydropower plants and river operation constraints, a state-space dynamic river model derived from shallow water equations is included. Followingly, a stochastic control (SC) approach for hydropower generation based on stochastic programming is proposed, where hydropower generation commands are parameterized as affine functions of measured solar power, enabling quick response to solar power volatility. Simulation of a real-life cascaded hydro-solar system and a modified system verifies the proposed control method.

Large-scale green hydrogen production system combining wind farms and electrolysis systems is an important way to low-carbon energy system. The flexible and fast ramping capability of the electrolysis system provides the possibility for a wind-electrolysis joint system (WEJS) to provide secondary frequency regulation (SFR) to reduce the production cost of green hydrogen. To increase the biddable capacity and improve the full load hours, this paper proposes a cooperative power allocation strategy for wind turbines and electrolyzers responding to the down and up AGC signals respectively. Furthermore, this paper proposes a more accurate method for estimating the daily hydrogen production due to response to the up ramping of automatic generation control (AGC) signals to ensure that the joint system meets the hydrogen production contract when providing SFR. Based on the above two points, this paper proposes a multi-timescale control framework and robust bidding optimization for a WEJS participating in energy and regulation markets. Case studies demonstrate that the relative error of daily hydrogen production can be controlled at 3.37%. The full load hours of the electrolysis systems can be increased by 50.21% compared with only participation in the energy market.

Power system static voltage stability region boundary (SVSRB) is a complicated hypersurface in parameter space. Due to inequality constraints such as generator reactive power limits, different critical points on the SVSRB may be related to different groups of active constraints and can be associated with different types of loadability limit, which makes it difficult to approximate the whole SVSRB at once or assemble many local approximations of the SVSRB. To overcome the difficulty, this paper proposes an approach for globally approximating the whole SVSRB considering generator reactive power limits at one go. First, a parametric optimization model incorporating all inequality constraints is formulated to describe the SVSRB, where the optimal solutions are the critical points on the SVSRB. The optimality condition, i.e., parametric Karush-Kuhn-Tucker conditions (KKT conditions), is also derived. Then, by applying the Galerkin method to the parametric KKT conditions in an interior-point-method-like manner, the whole SVSRB is approximated and represented using a single polynomial expression. Case studies in a 10-bus system and IEEE 300-bus system verify the effectiveness and accuracy of the proposed method.