Narrow body and wide body aircraft are responsible for more than 75% of aviation greenhouse gas (GHG) emission and aviation, itself, was responsible for about 2.5% of all GHG emissions in the United States in 2018. This situation becomes worse when considering a 4-5% annual growth in air travel. Electrified aircraft is clearly a promising solution to combat the GHG challenge; thus, the trend is to eliminate all but electrical forms of energy in aircraft power distribution systems. However, electrification adds tremendously to the complexity of aircraft electric power systems (EPS), which is dramatically changing in our journey from conventional aircraft to more electric aircraft (MEA) and all electric aircraft (AEA). In this article, we provide an in-depth discussion on MEA/AEA EPS: electric propulsion, distributed propulsion systems (DPS), EPS voltage levels, power supplies, and EPS architectures are discussed. Publications on power flow (PF) analysis and management of EPS are reviewed, and an initial schematic of a potential aircraft EPS with electric propulsion is proposed. In this regard, we also briefly review the components required for MEA/AEA EPS, including power electronics (PE) converters, electric machines, electrochemical energy units, circuit breakers (CBs), and wiring harness. A comprehensive review of each of the components mentioned above or other topics except for those related to steady state power flow in MEA/AEA EPS is out of this article's scope and should be found somewhere else. At the close of the paper, some challenges in the path towards AEA are presented. Unless the discussed challenges are satisfactorily addressed and solved, arriving at an AEA that can properly operate over commercial missions will not be possible.

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Electric Power Systems in More and All Electric Aircraft: A Review

Microgrids (MGs) have emerged as a viable solution for consumers consisting of Distributed Energy Resources (DERs) and local loads within a smaller zone that can operate either in an autonomous or grid tide mode. The DERs usually utilize Renewable Energy Resources (RERs), which have the advantages of meeting enhanced power demand, mitigating the pollutants of the environment, natural source of energy, needs minimal maintenance and cheap. Although MG integration provides several benefits, it faces many challenges and issues in its control and management, which can be effectively dealt with incorporating Energy Storage System (ESS) technologies into MGs. The addition of ESS to MGs has acquired increased attention as ESS can store energy during off-peak hours and deliver when required during peak hours. However, despite so many benefits, the ESS faces numerous issues in its integration, such as control, protection, state of charge (SoC), state of discharge (SoD), safety, life span, capacity, reliability and cost. So, to enhance the application of ESS in MG, the above issues need to be dealt with seriously. This research paper highlights the integration of ESS for MG application with a comprehensive review of issues, control methods, challenges, solutions, application, and overall management prospects. Further, the future trends and real time applications are also elucidated, which remarkably contributes to developing a cost effective and robust ESS architecture having a longer life span for renewable MGs application. Thus, an overview of this survey article's projected insights contributes to developing a techno-economic and effective integration of ESS with an extended life cycle for green MG employment. 

Review of energy storage system technologies integration to microgrid: Types, control strategies, issues, and future prospects

Microgrids need control and management at different levels to allow the inclusion of renewable energy sources. In this paper, a comprehensive literature review is presented to analyse the latest trends in research and development referring to the applications of predictive control in microgrids. As a result of this review, it was found that the application of predictive control techniques on microgrids is performed for the three control levels and with adaptations of the models in order to include uncertainties to improve their performance and dynamics response. In addition, to ensure system stability, but also, at higher control levels, coordinated operation among the microgrid’s components and synchronised and optimised operation with utility grids and electric power markets. Predictive control appears as a very promising control scheme with several advantages for microgrid applications of different control levels.

https://www.mdpi.com/1996-1073/13/10/2454/pdf

Predictive Control for Microgrid Applications: A Review Study

Clean and renewable energy is developing to realize the sustainable utilization of energy and the harmonious development of the economy and society. Microgrids are a key technique for applying clean and renewable energy. The operation optimization of microgrids has become an important research field. This paper reviews the developments in the operation optimization of microgrids. We first summarize the system structure and provide a typical system structure, which includes an energy generation system, an energy distribution system, an energy storage system and energy end users. Then, we summarize the optimization framework for microgrid operation, which contains the optimization objective, decision variables and constraints. Next, we systematically review the optimization algorithms for microgrid operations, of which genetic algorithms and simulated annealing algorithms are the most commonly used. Lastly, a literature bibliometric analysis is provided; the results show that the operation optimization of microgrids has received increasing attention in recent years, and developing countries have shown more interest in this field than developed countries have. Finally, we highlight future research challenges for the optimization of the operation of microgrids.

https://www.mdpi.com/1996-1073/14/10/2842/pdf

A Review of Optimization of Microgrid Operation

Renewable generation and energy storage systems are technologies which evoke the future energy paradigm. While these technologies have reached their technological maturity, the way they are integrated and operated in the future smart grids still presents several challenges. Microgrids appear as a key technology to pave the path towards the integration and optimized operation in smart grids. However, the optimization of microgrids considered as a set of subsystems introduces a high degree of complexity in the associated control problem. Model Predictive Control (MPC) is a control methodology which has been satisfactorily applied to solve complex control problems in the industry and also currently it is widely researched and adopted in the research community. This paper reviews the application of MPC to microgrids from the point of view of their main functionalities, describing the design methodology and the main current advances. Finally, challenges and future perspectives of MPC and its applications in microgrids are described and summarized.

Model Predictive Control for Microgrid Functionalities: Review and Future Challenges

Microgrids appear as the key part of the future power systems that include distributed generators, renewable energy, and energy storage. In this paper a decentralized power sharing control scheme that includes droop control with virtual impedances with PI controllers for the voltage and current is proposed for an islanded AC microgrid with two voltage source inverters in parallel that share a residential load. To avoid circulating currents and unbalanced power sharing due to line impedance differences in the microgrid, virtual impedances are added. The proposed control scheme is implemented in MAT-LAB/Simulink to prove the proper operation under inductive behavior and mismatches in the line impedances of the microgrid system.

https://nottingham-repository.worktribe.com/preview/4795441/Power%20Sharing%20Control%20of%20Islanded%20AC%20Microgrid.pdf

Power Sharing Control of Islanded AC Microgrid Considering Droop Control and Virtual Impedance

This article proposes a 27-level asymmetric cascade H-bridge multilevel topology for photovoltaic applications, which considers a predictive control strategy that allows minimization of the commutations of the converter. This proposal ensures a highly sinusoidal and stable photovoltaic injection when there are solar irradiance disturbances, generating a low distortion in the current waveform and low switching losses. To validate the performance of the control and the proposed topology, the dynamic model of the alternating current (AC) and direct current (DC) side system is first obtained, which is checked by computational simulations. Subsequently, the implementation of a master–slave control is carried out, focused on the control of DC voltage and AC current. The proposal is simulated, and the total harmonic distortion (THD) is obtained in the voltage and current waveforms. Undesired commutations, typical of the predictive control, are eliminated in the AC voltage waveform, and a proper DC voltage tracking is achieved for the high-power cell. In order to demonstrate the performance of the proposed control strategy, a low-power proof-of-concept prototype is implemented, in which the energy is injected to the grid, under the event of solar irradiance disturbances (with DC control).Then, the undesired switching in the main cell is eliminated, generating THDs in the voltage and current signal of 7.76% and 2.65%, respectively.

Improved Predictive Control for an Asymmetric Multilevel Converter for Photovoltaic Energy

The high increase of renewable energy sources and the increment of distributed generation in the electrical grid has made them complex and of variable parameters, causing potential stability problems to the PI controllers. In this document, a control strategy for power injection to the electrical system from photovoltaic plants through a voltage source inverter two-level-type (VSI-2L) converter is proposed. The algorithm combines a current-based maximum power point-tracking (Current-Based MPPT) with model predictive control (MPC) strategy, allowing avoidance of the use of PI controllers and lowering of the dependence of high-capacitive value condensers. The sections of this paper describe the parts of the system, control algorithms, and simulated and experimental results that allow observation of the behavior of the proposed strategy.

https://www.mdpi.com/2071-1050/13/6/3037/pdf

Predictive Control with Current-Based Maximum Power Point-Tracking for On-Grid Photovoltaic Applications

In this paper a new multilevel inverter topology is proposed for a three-phase grid-connected photovoltaic (PV) system. The proposed symmetric multilevel inverter generates seven-levels with reduced number of power switches than conventional symmetric multilevel inverters. The PV panels are connected to charge three equal capacitor voltages in each phase with appropriate PI controller. The maximum power point tracking method is extracted form PV panels by controlling of the voltage, power and current. Finally, in order to performance evaluation proposed seven-levels multilevel inverter, the proposed topology is simulated and the variation of capacitor voltages, the output voltage of inverter and grid injected current are presented.

Ariel Villalon

Papers

Predictive Control for Microgrid Applications: A Review Study

Power Sharing Control of Islanded AC Microgrid Considering Droop Control and Virtual Impedance

Improved Predictive Control for an Asymmetric Multilevel Converter for Photovoltaic Energy

Predictive Control with Current-Based Maximum Power Point-Tracking for On-Grid Photovoltaic Applications

New Reduced Switched Multilevel Inverter for Three-Phase Grid-Connected PV System, Performance Evaluation