With increasing wind power penetration, the inherent uncertainty of wind power poses significant challenges to dispatch decisions in power systems. To address this issue, this paper proposes a two-stage distributionally robust chance-constrained (TDRC) model for the unit commitment problem with wind power uncertainty. In this model, an ambiguity confidence set is developed to characterise wind power uncertainty with unknown probability distributions, and wind power curtailment and load shedding levels are modelled as chance constraints to balance wind power uncertainty and system security of dispatch decisions. A hybrid parallel solution (HPS) is proposed for efficient computation by integrating Benders decomposition (BD) and column-and-constraint generation (C&CG) methods. Case studies on the IEEE 24- and 118-bus systems demonstrate the rationality of the proposed approach, while experiments on a practical 126-bus system using the cyber-physical power system (CPPS) dispatch platform further validate the effectiveness and practical applicability of the proposed TDRC model.

False data injection (FDI) attacks can mislead the system operator to conduct incorrect dispatch decisions, causing cyber-induced physical line overloads. However, traditional false data is constructed either further from normal data and easy to detect, or not effective to overload multiple lines. To improve both attack stealth and overload impacts, this paper proposes a bilevel cyber-induced overloads (CIO) mechanism that can cause a predefined number of multi-line overloads considering post-attack economic dispatch, where the injected false data is minimised to improve the attack stealth. Within this mechanism, a detailed CIO attack model is formulated that explicitly incorporates the post-attack economic dispatch, enabling it to design more practical attack strategies. One advanced feature of this CIO attack model is the optimal selection of overloaded lines for the bilevel optimization of cyberattack resources and post-attack impacts in terms of line overloads, operation costs, and load loss. To solve the proposed model, it is converted into a single-level nonlinear model by a strong duality theory, and then CIO attacks are discretised to convert this model into a mixed-integer linear programming (MILP) problem. Case studies conducted on an IEEE 14-bus power system and an industrial 126-bus equivalent power system validate the superiority and effectiveness of our proposed approach.

This letter proposes an island-maximising attack mechanism to maximise the number of power islands in cyber-physical power systems (CPPS) by disrupting lines. Specifically, a single-level mixed-integer programming (MIP) model is developed with a graph-theoretic approach, which is able to divide CPPS into power islands, while intra-island line overloads are induced in a high-stealth manner with increasing load shedding and economic loss. Case studies conducted on modified IEEE 14-bus and practical 36-zone Great Britain systems validate the effectiveness of our proposed island-maximising approach.

This paper focuses on the trajectory planning problem in highly complex and irregular parking lot scenarios. We formulate this problem as an optimal control problem (OCP) according to the requirements of the task and propose a planner to solve it numerically. To ensure optimal planning results, the proposed planner consists of three procedures, which are responsible for generating the guiding route, constructing the collision-free tunnel, and optimizing the trajectory, respectively. Firstly, we use the generalized Voronoi graph (GVG) to build an equidistant roadmap and propose an improved adaptive A* algorithm (IAA*) to improve the time efficiency of the guiding route generation process. Secondly, we employ a coarse trajectory to guide a homotopic route and replace the intractably scaled collision-avoidance constraints with within-tunnel constraints, which are small-scale and independent of the environment’s complexity. Our tunnel construction method ensures the integrity of the free spaces, so that repeated construction is not necessary. Finally, in the process of trajectory optimization, we propose a lightweight OCP iterative solution framework to search for the optimal solution with high computational efficiency, in which the customized OCP with only box constraints is quickly solved in each iteration. Besides, the theoretical analysis, numerical simulations, and real-world experiments had been carried out to demonstrate the effectiveness and efficiency of the method.

EPSRC Supergen Energy Networks Hub (grant number: EP/S00078X/1): ‘GRid flexibility by Electrifying Energy Networks for Airport (GREEN Airport)’; UK Department for Transport Transport-Technology Research Innovation Grant (T-TRIG 2019): ‘Aircraft to Grid: Hybrid and Smart Charging for Electric Aircraft’.