Optimal Load and Energy Management of Aircraft Microgrids Using Multi-Objective Model Predictive Control

Abstract

Safety issues related to the electrification of more electric aircraft (MEA) need to be addressed because of the increasing complexity of aircraft electrical power systems and the growing number of safety-critical sub-systems that need to be powered. Managing the energy storage systems and the flexibility in the load-side plays an important role in preserving the system’s safety when facing an energy shortage. This paper presents a system-level centralized operation management strategy based on model predictive control (MPC) for MEA to schedule battery systems and exploit flexibility in the demand-side while satisfying time-varying operational requirements. The proposed online control strategy aims to maintain energy storage (ES) and prolong the battery life cycle, while minimizing load shedding, with fewer switching activities to improve devices lifetime and to avoid unnecessary transients. Using a mixed-integer linear programming (MILP) formulation, different objective functions are proposed to realize the control targets, with soft constraints improving the feasibility of the model. In addition, an evaluation framework is proposed to analyze the effects of various objective functions and the prediction horizon on system performance, which provides the designers and users of MEA and other complex systems with new insights into operation management problem formulation.

Sustainable Aviation Electrification: A Comprehensive Review of Electric Propulsion System Architectures, Energy Management, and Control

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Multi-Objective Cooperative Control for a Ship-Towing System in Congested Water Traffic Environments

“…Research works in [34] propose a dynamic weight adjusting strategy for the control objectives of trajectory tracking and driver's commands matching to address the conflict between the driver and the automation. In [35], scholars replace the hard constraints with soft constraints for the battery state of charge for the aircraft microgrids to improve the feasibility of the solution of the mixed-integer linear programming (MILP)based MPC algorithm. Authors in [36] propose a dynamic weight tuning strategy according to the inter-vehicular states to optimize the responsiveness of collision avoidance during the transitional maneuver for improving the feasibility.…”

Robust self‐adaptive fuzzy controller for load‐frequency control of islanded airport microgrids considering electric aircraft energy storage and demand response

“…However, some technical issues, such as the low energy density of batteries and energy supply through traditional fossil resources due to high energy demand, have made the work difficult. Moreover, to provide power and create a balance between “supply and demand” in the airport energy system, traditional methods, such as increasing the capacity of the upstream power grid due to high investment costs, land and resource limitations, distance from the main grid, and long construction cycle, cannot be feasible [5]. Because such power generation expansion plans with the additional transmission and distribution capacity ultimately lead to higher electricity consumption costs in airports, increased transmission losses, and pollution [6].…”