Simulation of strongly injection-locked semiconductor ring lasers

To overcome the limited modulation bandwidth of directly modulated semiconductors, a novel scheme for modulation bandwidth enhancement and tailoring is presented. This scheme involves a single-frequency master laser monolithically integrated with strongly injection-locked whistle-geometry semiconductor ring lasers. Improved high-speed performance of the novel scheme is confirmed through numerical modeling, showing greatly enhanced resonance frequency of up to ~160 GHz. Approaches to further improve the modulation response of strongly injection-locked ring lasers, including cascaded injection-locking and Q-modulated injection-locking are also presented

Stability Constrained Optimization in High IBR-Penetrated Power Systems-Part I: Constraint Development and Unification

Maintaining power system stability is becoming more and more challenging due to the ever-increasing inverter-interfaced renewable penetration in power systems. To ensure system stability during system operation and to provide appropriate incentives in the future market-based stability maintenance framework, it is essential to develop a comprehensive set of power system stability constraints which can be incorporated into system operation, market design and planning problems. In this paper, different system stability issues, including synchronization, voltage and frequency stability, are investigated and the corresponding stability conditions are analytically formulated as system operation constraints. A unified framework is further proposed to represent the stability constraints in a general form and enables effective reformulation of the impedance-based stability metrics. All the constraints are converted into linear or Second-Order-Cone (SOC) form, which can be readily implemented in any optimisation-based applications, such as system scheduling, planning and market design, thus providing significant value for multiple system stability enhancement and studies

Optimal Design of Neural Network Structure for Power System Frequency Security Constraints

Recently, frequency security is challenged by high uncertainty and low inertia in power system with high penetration of Renewable Energy Sources (RES). In the context of Unit Commitment (UC) problems, frequency security constraints represented by neural networks have been developed and embedded into the optimization problem to represent complicated frequency dynamics. However, there are two major disadvantages related to this technique: the risk of overconfident prediction and poor computational efficiency. To handle these disadvantages, novel methodologies are proposed to optimally design the neural network structure, including the use of asymmetric loss function during the training stage and scientifically selecting neural network size and topology. The effectiveness of the proposed methodologies are validated by case study which reveals the improvement of conservativeness and mitigation of computation performance issues