http://www.cs.unibo.it/~montesi/CBD/Articoli/SurvyBigData2.pdf

Data-intensive applications, challenges, techniques and technologies: A survey on Big Data

https://repository.tudelft.nl/islandora/object/uuid%3Ae373683e-ac75-4100-97d9-1b0d7edb6d77/datastream/OBJ/download

Design and control of hybrid power and propulsion systems for smart ships: A review of developments

Reference and command governors for systems with constraints

Hybrid ac/dc micro-grid is a new concept decoupling dc sources with dc loads and ac sources with ac loads, while power is exchanged between both sides using a bidirectional converter/inverter. This necessitates a supervisory control system to split power between its different resources, which has sparked attention on the development of power management systems (PMSs). In this paper, a robust optimal PMS (ROPMS) is developed for a hybrid ac/dc micro-grid, where the power flow in the micro-grid is supervised based on solving an optimization problem. Satisfying demanded power with maximum utilization of renewable resources, minimum usage of fuel-based generator, extending batteries lifetime, and limited utilization of the main power converter between the ac and dc micro-grids are important factors that are considered in this approach. Uncertainties in the resources output power and generation forecast errors, along with static and dynamic constraints of the resources, are taken into account. Furthermore, since uncertainties in the resources output power may result in fluctuations in the dc bus voltage, a two-level controller is used to regulate charge/discharge power of the battery banks. Effectiveness of the proposed supervisory system is evaluated through extensive simulation runs based on dynamical models of the power resources.

Robust Optimal Power Management System for a Hybrid AC/DC Micro-Grid

Towards felicitous decision making

All-electric ships (AES), enabled by integrated power systems (IPS), have been pursued for both commercial and military applications to meet the increasing ship-board power demand and environmental sustainability initiatives. They necessitate real-time power management (PM) for dynamic reconfiguration to support system critical operations in the event of dynamic load change or IPS component failures. The nonlinear, large scale trajectory optimization problem associated with IPS, along with the non-analytical nature of IPS model, makes many existing methods inadequate in meeting the real-time requirements. In this paper, we develop a methodology that exploits time scale separation, a characteristic associated with IPS dynamics, to achieve real-time optimization. In parallel, a dynamic model of the IPS with gas turbine and fuel cell as power plants is developed that captures the relevant dynamics but is simple enough for real-time optimization. The tradeoffs between the computational efficiency and optimization accuracy are analyzed. The optimization results for IPS PM on a real-time simulator are reported, which illustrate the real-time feasibility of the proposed optimization strategy.

/pdf/real-time-power-management-of-integrated-power-systems-in-aenvk9md8j.pdf

Real-Time Power Management of Integrated Power Systems in All Electric Ships Leveraging Multi Time Scale Property

This paper presents the development of a PC-cluster based real-time simulator for all electric ship (AES) integrated power system (IPS) analysis and optimization. The system is established at the University of Michigan with the financial support from the U.S. Office of Naval Research (ONR). It is aimed to address the multi-disciplinary issues associated with the all-electric ship, such as optimal power management and dynamic system reconfiguration. In parallel with hardware construction, a modularized IPS model which includes the power generation module, the reconfigurable zonal electrical distribution system module, the ship propulsion module and the ship dynamic module is developed and integrated. Simulation GUIs have also been developed to provide a user friendly engineering environment where data acquisition and parameter tuning can be performed effectively. Both the system development efforts and preliminary simulation results for different shipboard operating scenarios are reported.

A PC-Cluster Based Real-Time Simulator for All-Electric Ship Integrated Power Systems Analysis and Optimization

A reference governor-based hierarchical control for failure mode power management of hybrid power systems for all-electric ships

Both new and existing naval vessels of all sizes face ever-increasing power supply requirements to support advanced mission loads including high power sensors, weapons, and launchers. Adding additional conventional generators to support these loads is infeasible given size and weight constraints and given the pulsed nature of those new loads. Instead, an optimization-based Power Management Controller (PMC) is used to dynamically control power system sources and loads in real time in order to serve system needs with a minimal amount of power supply equipment. In this paper, a Model Predictive Control (MPC) approach is used to dynamically coordinate sources and loads based on future demand. A cost function is used to prioritize various ship goals and objectives, and constraints are added to reflect hardware limitations. A Constrained Nonlinear MPC algorithm is then used to minimize the cost over a finite future horizon and generate control commands in real-time. The PMC is demonstrated to successfully control and improve system performance on a hardware test bed for ship power system research.

https://www.usna.edu/Users/ee/opila/files/Ship_PMC_ESTS2015.pdf

Shipboard power management using constrained nonlinear model predictive control

This paper deals with the optimal control of hybrid power systems (HPS) for all electric ships (AES) targeting military applications to support critical missions such as weapon or aircraft launches. The optimal control of HPS manages the power flow from the energy storage device and power sources to ensure mission effectiveness, namely, meet the pulse power demands as quickly and as efficiently as possible. The real-time control is a key requirement due to the on-demand nature of the problem. This requirement, along with the nonlinear and large scale HPS dynamics, long look-ahead horizon, safety constraints and load disturbances, makes the control problem challenging. In this paper we leverage the dynamic properties of HPS and propose a hierarchical control strategy for the power management of the HPS. The key merit of the proposed approach is that both the long term optimal power demand planning and short term disturbance rejection can be solved in real-time without computational delay. A case study using the HPS model illustrates the real-time computational efficiency and mission effectiveness of the proposed method.

Gayathri Seenumani

Papers

Real-Time Power Management of Integrated Power Systems in All Electric Ships Leveraging Multi Time Scale Property

A PC-Cluster Based Real-Time Simulator for All-Electric Ship Integrated Power Systems Analysis and Optimization

A reference governor-based hierarchical control for failure mode power management of hybrid power systems for all-electric ships

Shipboard power management using constrained nonlinear model predictive control

A hierarchical optimal control strategy for power management of hybrid power systems in all electric ships applications