scholarly journals Economic Management Based on Hybrid MPC for Microgrids: A Brazilian Energy Market Solution

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3508 ◽  
Author(s):  
Eduardo Conte ◽  
Paulo R. C. Mendes ◽  
Julio E. Normey-Rico
Keyword(s):  
Predictive Control ◽  
Mixed Integer ◽  
Energy Market ◽  
High Fidelity ◽  
Management Problem ◽  
Economic Management ◽  
Central Controller ◽  
Energy Compensation ◽  
And Performance

This paper proposes a microgrid central controller (MGCC) solution to the energy management problem of a renewable energy-based microgrid (MG). This MG is a case study from the Brazilian energy market context and, thus, has some operational particularities and rules to be obeyed. The MGCC development was based on a hybrid model predictive control (HMPC) strategy using the mixed logical dynamic (MLD) approach to deal with logical constraints within the HMPC structure, which results in a mixed integer programming (MIP) problem. The development of the solution is done through economic and dynamic modeling of the MG components; furthermore, it also takes into account the energy compensation rules of the Brazilian energy market and the white energy tariff. These conditions are specified through a set of MLD constraints. The effectiveness and performance of the proposed solution are evaluated through high-fidelity numerical simulation.

The Role of Model Fidelity in Model Predictive Control Based Hazard Avoidance in Unmanned Ground Vehicles Using LIDAR Sensors

2013 ◽  
Author(s):  
Jiechao Liu ◽  
Paramsothy Jayakumar ◽  
James L. Overholt ◽  
Jeffrey L. Stein ◽  
Tulga Ersal
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Vehicle Dynamics ◽  
High Fidelity ◽  
Unmanned Ground Vehicles ◽  
Ground Vehicles ◽  
Model Fidelity ◽  
Hazard Avoidance ◽  
The Impact

Unmanned ground vehicles (UGVs) are gaining importance and finding increased utility in both military and commercial applications. Although earlier UGV platforms were typically exclusively small ground robots, recent efforts started targeting passenger vehicle and larger size platforms. Due to their size and speed, these platforms have significantly different dynamics than small robots, and therefore the existing hazard avoidance algorithms, which were developed for small robots, may not deliver the desired performance. The goal of this paper is to present the first steps towards a model predictive control (MPC) based hazard avoidance algorithm for large UGVs that accounts for the vehicle dynamics through high fidelity models and uses only local information about the environment as provided by the onboard sensors. Specifically, the paper presents the MPC formulation for hazard avoidance using a light detection and ranging (LIDAR) sensor and applies it to a case study to investigate the impact of model fidelity on the performance of the algorithm, where performance is measured mainly by the time to reach the target point. Towards this end, the case study compares a 2 degrees-of-freedom (DoF) vehicle dynamics representation to a 14 DoF representation as the model used in MPC. The results show that the 2 DoF model can perform comparable to the 14 DoF model if the safe steering range is established using the 14 DoF model rather than the 2 DoF model itself. The conclusion is that high fidelity models are needed to push autonomous vehicles to their limits to increase their performance, but simulating the high fidelity models online within the MPC may not be as critical as using them to establish the safe control input limits.

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

2021 ◽  
Vol 13 (24) ◽  
pp. 13907
Author(s):  
Xin Wang ◽  
Jason Atkin ◽  
Najmeh Bazmohammadi ◽  
Serhiy Bozhko ◽  
Josep M. Guerrero
Keyword(s):  
Energy Storage ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Evaluation Framework ◽  
Operation Management ◽  
System Level ◽  
Mixed Integer ◽  
Battery Life ◽  
Management Problem ◽  
Objective Functions

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.

scholarly journals Cooperative path-planning and tracking controller evaluation using vehicle models of varying complexities

2020 ◽  
pp. 095440622094546
Author(s):  
Husain Kanchwala ◽  
Icaro Bezerra Viana ◽  
Nabil Aouf
Keyword(s):  
Path Planning ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Mixed Integer ◽  
Distributed Model ◽  
Programming Approach ◽  
High Fidelity ◽  
Vehicle Model ◽  
Integer Quadratic Programming ◽  
Tracking Controller

This paper discusses cooperative path-planning and tracking controller for autonomous vehicles using a distributed model predictive control approach. Mixed-integer quadratic programming approach is used for optimal trajectory generation using a linear model predictive control for path-tracking. Cooperative behaviour is introduced by broadcasting the planned trajectories of two connected automated vehicles. The controller generates steering and torque inputs. The steering and drive motor actuator constraints are incorporated in the control law. Computational simulations are performed to evaluate the controller for vehicle models of varying complexities. A 12-degrees-of-freedom vehicle model is developed and is subsequently linearised to be used as the plant model for the linearised model predictive control-based tracking controller. The model behaviour is compared against the kinematic, bicycle and the sophisticated high-fidelity multi-body dynamics CarSim model of the vehicle. Vehicle trajectories used for tracking are longitudinal and lateral positions, velocities and yaw rate. A cooperative obstacle avoidance manoeuvre is performed at different speeds using a co-simulation between the controller model in Simulink and the high-fidelity vehicle model in CarSim. The simulation results demonstrate the effectiveness of the proposed method.

scholarly journals Turnback Capacity Assessment and Delay Management at a Rail Transit Terminal with Two-Tail Tracks

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Zhibin Jiang ◽  
Yuyan Tan ◽  
Feng Wang ◽  
Lei Bu
Keyword(s):  
Positive Impact ◽  
Mixed Integer ◽  
Design Parameters ◽  
Rail Transit ◽  
Capacity Evaluation ◽  
Buffer Time ◽  
Study Results ◽  
And Performance ◽  
Allocation Strategies

Terminal capacity and performance have become a major concern for rail transit agencies in China due to the ever increasing passenger demand. This paper develops a mixed integer programming (MIP) optimization model to estimate the turnback capacity and performance of a rail transit terminal with two-tail tracks. The capacity evaluation and delay propagation are described and assessed as anN-track integrated model with minimal time span and train delay. Operations and design parameters such as tail track allocation strategies, maximum layover time, headway pattern, buffer time distribution scheme, and primary delay are also considered in this model. The effectiveness of the model is tested by a case study with computation results drawn from one terminal station in Shanghai, China. The case study results show that unfixed platform time and flexible tail track allocation strategies can improve the capacity of turnback operation, and the strategy of allowing swapping of the tail tracks has a significantly positive impact on delay absorption.

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

2021 ◽  
Author(s):  
Xin Wang ◽  
Jason Atkin ◽  
Najmeh Bazmohammadi ◽  
Serhiy Bozhko ◽  
and Josep M. Guerrero
Keyword(s):  
Energy Storage ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Evaluation Framework ◽  
Operation Management ◽  
System Level ◽  
Mixed Integer ◽  
Battery Life ◽  
Management Problem ◽  
Objective Functions

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 robustness of the model. Besides, 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.

scholarly journals Power Plant Cooperation In District Heating Considering Open Electricity Market

2021 ◽  
Vol 58 (3) ◽  
pp. 66-81
Author(s):  
R. Oleksijs ◽  
A. Sauhats ◽  
B. Olekshii
Keyword(s):  
Electricity Market ◽  
Mixed Integer Linear Programming ◽  
District Heating ◽  
Heat Energy ◽  
Mixed Integer ◽  
Energy Market ◽  
Market Participants ◽  
Hourly Data ◽  
Total Profit

Abstract The paper analyses the possibilities to form a coalition of several heat energy providers in order to participate in the district heating market considering the open electricity market. Cooperation would allow the participants to better dispatch the existing energy sources and would ensure higher total profit for the participants. The objective function for such a cooperation is provided. To optimise the operation of the coalition, mixed integer linear programming is used, considering constraints of different heating energy market participants and the need to fulfil heating energy balance. If any additional profit is made, it is shared between coalition participants according to the Shapley value, which grants interest for market participants to form the coalition. Case study based on historical hourly data is provided and numerical results are presented in the paper.

Modelling and Simulation of High Fidelity CDU for Flight Simulator Based on Object-Oriented and Hardware-in-Loop Technique

2010 ◽  
Vol 108-111 ◽  
pp. 530-535
Author(s):  
Si Bin Zhu ◽  
Zheng Mao Ye ◽  
Gui Xian Li
Keyword(s):  
Object Oriented ◽  
Simulation Method ◽  
High Fidelity ◽  
Management Problem ◽  
Simulation Experiments ◽  
Simulation Fidelity ◽  
Loop Technique ◽  
And Performance ◽  
Hardware In Loop ◽  
Hardware Circuit

A high fidelity, reliable and extensible real-time CDU simulation system is built on the basis of self-made membrane keyboard and object-oriented simulation method in this paper to improve the visual feelings and simulation fidelity of CDU in flight management system research. Based on embedded PC104 CPU and 8255 programmable peripheral equipment interface card, the membrane keyboard hardware circuit and the keyboard code scanning program are designed. Accordingly, the confused logical problem of keystokes is solved and meanwhile, the emulation CDU keyboard is realized. And then, an extensible and reliable CDU pages system is constructed utilizing object-oriented simulation technique, inheritance and polymorphism mechanisms. Thus, the tiresome generation and management problem of pages system is tackled. Simulation experiments illustrate that routing data and performance parameters can be input and displayed realistically on the CDU system developed in this paper.

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