No abstract

Abstract-The magnetic equivalent circuit (MEC) technique is a powerful analysis and design tool that combines relative accuracy with moderate computational effort. In this paper, a nodal-based MEC formulation and a mesh-based MEC formulation of a magnetic system are compared. The Newton-Raphson algorithm is used to solve the algebraic system, and to draw conclusions about the computational efficiency of the two formulations under linear and nonlinear operation. Although the two formulations exhibit similar performance under linear operating conditions, the performance of the mesh-based model is significantly better than that of the nodal-based model under nonlinear operation.

Shipboard integrated power systems, the key enablers of ship electrification, call for effective power management control (PMC) to achieve optimal and reliable operation in dynamic environments under hardware limitations and operational constraints. The design of PMC can be treated naturally in a model predictive control (MPC) framework, where a cost function is minimized over a prediction horizon subject to constraints. The real-time implementation of MPC-based PMC, however, is challenging due to computational complexity of the numerical optimization. In this paper, an MPC-based PMC for a shipboard power system is developed and its real-time implementation is investigated. To meet the requirements for real-time computation, an integrated perturbation analysis and sequential quadratic programming (IPA-SQP) algorithm is applied to solve a constrained MPC optimization problem. Several operational scenarios are considered to evaluate the performance of the proposed PMC solution. Simulations and experiments show that real-time optimization, constraint enforcement, and fast load following can be achieved with the IPA-SQP algorithm. Different performance attributes and their tradeoffs can be coordinated through proper tuning of the design parameters.Index Terms-Integrated perturbation analysis and sequential quadratic programming (IPA-SQP), integrated power system (IPS), model predictive control (MPC), power management control (PMC), real-time optimization.

No abstract

No abstract