Automotive Inductive Position Sensor

Inductive angular position sensors (IAPS) are widely used for high accuracy and low cost angular position sensing in harsh automotive environments, such as suspension height sensor and throttle body position sensor. These sensors ensure high resolution and long lifetime due to their contactless sensing mode and their simple structure. Furthermore, they are suitable for wider application areas. For instance, they can be miniaturized to fit into a compact packaging space, or be adopted to measure the relative angle of multiple rotating targets for the purposes of torque sensing. In this work, a detailed SIMULINK model of an IAPS is first proposed in order to study and characterize the sensor performance. The model is validated by finite element analysis and circuit simulation, which provides a powerful design tool for sensor performance analysis. The sensor error introduced by geometry imperfection is thoroughly investigated for two-phase and three-phase configurations, and a corresponding correction method to improve the accuracy is proposed. A design optimization method based on the response surface methodology is also developed and used in the sensor development. Three types of sensors are developed to demonstrate the inductive sensor technology. The first type is the miniaturized inductive sensor. To compensate for the weak signal strength and the reduced quality (Q) factor due to the scaling down effect, a resonant rotor is developed for this type of sensor. This sensor is fabricated by using the electrodeposition technique. The prototype shows an 8mm diameter sensor can function well at 1.5mm air gap. The second type is a steering torque sensor, which is designed to detect the relative torsional angle of a rotating torsional shaft. It demonstrates the mutual coupling of multiple inductive sensors. By selecting a proper layout and compensation algorithm, the torque sensor can achieve 0.1 degree accuracy. The third type is a passive inductive sensor, which is designed to reduce power consumption and electromagnetic emissions. The realization and excellent performance of these three types of sensors have shown the robustness of the inductive sensor technology and its potential applications. The research conducted in this dissertation is expected to improve understanding of the performance analysis of IAPS and provide useful guidelines for the design and performance optimization of inductive sensors

AC Current Controller with Error-Free Feedback Acquisition System

In this paper, we introduce an improved ac current controller with robustness against the noise in the feedback path. This three-phase current controller is suited for inverter supplied ac machines and grid-connected power converters. Conventional solutions make use of symmetric pulse-width modulation (PWM) techniques with feedback sampling in the middle of the voltage pulses. Single-sample-based feedback acquisition gets affected by the noise and parasitic phenomena. We perform a thorough analytical and experimental study on feedback errors with conventional sampling, and we consider the impact of the lockout time, motor cables, winding capacitance, and anti-aliasing filters. In order to suppress a significant spectral content in the area of low-order harmonics, we apply an improved acquisition technique, which uses a period-average and removes any PWM noise from the feedback signals. Both anti-aliasing filter and proposed period-average filter introduce delays, which impair the control-loop performance. The conventional current controller is then extended to suppress the effects of the delays. Parameter setting procedure is devised to achieve both the bandwidth and the robustness against the parameter changes. Analytical and experimental studies prove that the proposed feedback acquisition technique improves the robustness in the presence of variable delays and switching transients. Experimental tests show that the extended current controller with period-average feedback acquisition reaches the same bandwidth and robustness as the state-of-the-art controller

Differential Flatness-Based Performance Enhancement of a Vector Controlled VSC with an LCL-Filter for Weak Grids

In this paper, a novel single-loop flatness-based controller (FBC) is proposed to control the grid-side current in a shunt converter connected to a weak grid through an LCL-filter. After its mathematical description, the paper reports controller implementation and some performance comparisons with two distinct implementations of the widely diffused vector current control approach, during balanced and unbalanced grid voltages, and weak grid conditions. Obtained results highlight higher tracking capability and better dynamic response of the proposed FBC. Moreover, because of its reduced negative conductance region, unstable behaviors that can be observed in weak grids appear significantly improved due to a reduced influence of the phase-locked loop system

Real-time Forecasting and Control for Oscillating Wave Energy Devices

Ocean wave energy represents a signicant resource of renewable energy and can make an important contribution to the development of a more sustainable solution in support of the contemporary society, which is becoming more and more energy intensive. A perspective is given on the benefits that wave energy can introduce, in terms of variability of the power supply, when combined with oshore wind. Despite its potential, however, the technology for the generation of electricity from ocean waves is not mature yet. In order to raise the economic performance of Wave energy converters (WECs), still far from being competitive, a large scope exists for the improvement of their capacity factor through more intelligent control systems. Most control solutions proposed in the literature, for the enhancement of the power absorption of WECs, are not implemented in practise because they require future knowledge of the wave elevation or wave excitation force. The non-causality of the unconstrained optimal conditions, termed complex-conjugate control, for the maximum wave energy absorption of WECs consisting of oscillating systems, is analysed. A link between fundamental properties of the radiation of the floating body and the prediction horizon required for an effective implementation of complex-conjugate control is identified. An extensive investigation of the problem of wave elevation and wave excitation force forecasting is then presented. The prediction is treated as a purely stochastic problem, where future values of the wave elevation or wave excitation force are estimated from past measurements at the device location only. The correlation of ocean waves, in fact, allows the achievement of accurate predictions for 1 or 2 wave periods into the future, with linear Autoregressive (AR) models. A relationship between predictability of the excitation force and excitation properties of the floating body is also identified. Finally, a controller for an oscillating wave energy device is developed. Based on the assumption that the excitation force is a narrow-banded harmonic process, the controller is effectively tuned through a single parameter of immediate physical meaning, for performance and motion constraint handling. The non-causality is removed by the parametrisation, the only input of the controller being an on-line estimate of the frequency and amplitude of the excitation force. Simulations in (synthetic and real) irregular waves demonstrate that the solution allows the achievement of levels of power capture that are very close to non-causal complex-conjugate control, in the unconstrained case, and Model predictive control (MPC), in the constrained case. In addition, the hierarchical structure of the proposed controller allows the treatment of the issue of robustness to model uncertainties in quite a straightforward and effective way

Control Strategies for Machining with Industrial Robots

This thesis presents methods for improving machining with industrial robots using control, with focus on increasing positioning accuracy and controlling feed rate. The strong process forces arising during high-speed machining operations, combined with the limited stiffness of industrial robots, have hampered the usage of industrial robots in high-end machining tasks. However, since such manipulators may offer flexible and cost-effective machining solutions compared to conventional machine tools, it is of interest to increase the achievable accuracy using industrial robots. In this thesis, several different methods to increase the machining accuracy are presented. Modeling and control of a piezo-actuated high-dynamic compensation mechanism for usage together with an industrial robot during a machining operation, such as milling in aluminium, is considered. Position control results from experiments are provided, as well as an experimental verification of the benefit of utilizing the online compensation scheme. It is shown that the milling surface accuracy achieved with the proposed compensation mechanism is increased by up to three times compared to the uncompensated case. Because of the limited workspace and the higher bandwidth of the compensator compared to the robot, a mid-ranging approach for control of the relative position between the robot and the compensator is proposed. An adaptive, model-based solution is presented, which is verified through simulations as well as experiments, where a close correspondence with the simulations was achieved. Comparing the IAE from experiments using the proposed controller to previously established methods, a performance increase of up to 56 % is obtained. Additionally, two different approaches to increasing the accuracy of the machining task are also presented in this thesis. The first method is based on identifying a stiffness model of the robot, and using online force measurements in order to modify the position of the robot to compensate for position deflections. The second approach uses online measurements from an optical tracking system to suppress position deviations. In milling experiments performed in aluminium, the absolute accuracy was increased by up to a factor of approximately 6 and 9, for the two approaches, respectively. Robotic machining is often performed using position feedback with a conservative feed rate, to avoid excessive process forces. By controlling the applied force, realized by adjusting the feed rate of the workpiece, precise control over the material removal can be exercised. This will in turn lead to maximization of the time-efficiency of the machining task, since the maximum amount of material can be removed per time unit. This thesis presents an adaptive force controller, based on a derived model of the machining process and an identified model of the Cartesian dynamics of the robot. The controller is evaluated in both simulation and an experimental setup

Control techniques for ocean energy applications.

Control systems, despite often being `invisibly' incorporated within products, devices and vehicles, are ubiquitous. They are prevalent within the automotive and aerospace industries and form part of the vanguard of technologies in in- creasing performance, improving fuel economy and increasing safety. One of the most appealing aspects of incorporating control technology in many systems is that the addition of extra control functionality can usually be achieved merely through the addition of extra software code though, in many cases, additional sensors and actuators may be required. This relatively simple implementation modality masks both the capability of control systems and the high level of engineering underpinning the devel- opment of a suitable control algorithm. For example, many high-performance model-based control design methods require an accurate mathematical model of the system to be controlled and a significant number of man-hours can be absorbed in modelling. Nevertheless, there is usually a good case to be made for the incorporation of control technology to improve the performance (both technical and economic), reliability and safety of a system. In this chapter, we will examine the role that control engineering can play in making ocean energy technology more competitive

Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids

[EN] Microgrids have emerged as a solution to address new challenges in power systems with the integration of distributed energy resources (DER). Inverter-based microgrids (IBMG) need to implement proper control systems to avoid stability and reliability issues. Thus, several researchers have introduced multi-objective control strategies for distributed generation on IBMG. This paper presents a review of the different approaches that have been proposed by several authors of multi-objective control. This work describes the main features of the inverter as a key component of microgrids. Details related to accomplishing efficient generation from a control systems' view have been observed. This study addresses the potential of multi-objective control to overcome conflicting objectives with balanced results. Finally, this paper shows future trends in control objectives and discussion of the different multi-objective approaches.Gonzales-Zurita, Ó.; Clairand, J.; Peñalvo-López, E.; Escrivá-Escrivá, G. (2020). Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids. Energies. 13(13):1-29. https://doi.org/10.3390/en13133483S1291313Ross, M., Abbey, C., Bouffard, F., & Joos, G. (2015). Multiobjective Optimization Dispatch for Microgrids With a High Penetration of Renewable Generation. IEEE Transactions on Sustainable Energy, 6(4), 1306-1314. doi:10.1109/tste.2015.2428676Murty, V. V. S. N., & Kumar, A. (2020). Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems. Protection and Control of Modern Power Systems, 5(1). doi:10.1186/s41601-019-0147-zKatircioğlu, S., Abasiz, T., Sezer, S., & Katırcıoglu, S. (2019). Volatility of the alternative energy input prices and spillover effects: a VAR [MA]-MGARCH in BEKK approach for the Turkish economy. Environmental Science and Pollution Research, 26(11), 10738-10745. doi:10.1007/s11356-019-04531-5Olivares, D. E., Mehrizi-Sani, A., Etemadi, A. H., Canizares, C. A., Iravani, R., Kazerani, M., … Hatziargyriou, N. D. (2014). Trends in Microgrid Control. IEEE Transactions on Smart Grid, 5(4), 1905-1919. doi:10.1109/tsg.2013.2295514Akinyele, D., Belikov, J., & Levron, Y. (2018). Challenges of Microgrids in Remote Communities: A STEEP Model Application. Energies, 11(2), 432. doi:10.3390/en11020432Benamar, A., Travaillé, P., Clairand, J.-M., & Escrivá-Escrivá, G. (2020). Non-Linear Control of a DC Microgrid for Electric Vehicle Charging Stations. International Journal on Advanced Science, Engineering and Information Technology, 10(2), 593. doi:10.18517/ijaseit.10.2.10815Lakshmi, M., & Hemamalini, S. (2018). Nonisolated High Gain DC–DC Converter for DC Microgrids. IEEE Transactions on Industrial Electronics, 65(2), 1205-1212. doi:10.1109/tie.2017.2733463Yin, C., Wu, H., Locment, F., & Sechilariu, M. (2017). Energy management of DC microgrid based on photovoltaic combined with diesel generator and supercapacitor. Energy Conversion and Management, 132, 14-27. doi:10.1016/j.enconman.2016.11.018Chen, D., Xu, Y., & Huang, A. Q. (2017). Integration of DC Microgrids as Virtual Synchronous Machines Into the AC Grid. IEEE Transactions on Industrial Electronics, 64(9), 7455-7466. doi:10.1109/tie.2017.2674621Abhinav, S., Schizas, I. D., Ferrese, F., & Davoudi, A. (2017). Optimization-Based AC Microgrid Synchronization. IEEE Transactions on Industrial Informatics, 13(5), 2339-2349. doi:10.1109/tii.2017.2702623Liu, Z., Su, M., Sun, Y., Li, L., Han, H., Zhang, X., & Zheng, M. (2019). Optimal criterion and global/sub-optimal control schemes of decentralized economical dispatch for AC microgrid. International Journal of Electrical Power & Energy Systems, 104, 38-42. doi:10.1016/j.ijepes.2018.06.045Khatibzadeh, A., Besmi, M., Mahabadi, A., & Reza Haghifam, M. (2017). Multi-Agent-Based Controller for Voltage Enhancement in AC/DC Hybrid Microgrid Using Energy Storages. Energies, 10(2), 169. doi:10.3390/en10020169Asghar, F., Talha, M., & Kim, S. (2017). Robust Frequency and Voltage Stability Control Strategy for Standalone AC/DC Hybrid Microgrid. Energies, 10(6), 760. doi:10.3390/en10060760Lotfi, H., & Khodaei, A. (2017). Hybrid AC/DC microgrid planning. Energy, 118, 37-46. doi:10.1016/j.energy.2016.12.015Kerdphol, T., Rahman, F., & Mitani, Y. (2018). Virtual Inertia Control Application to Enhance Frequency Stability of Interconnected Power Systems with High Renewable Energy Penetration. Energies, 11(4), 981. doi:10.3390/en11040981Rodrigues, Y. R., Zambroni de Souza, A. C., & Ribeiro, P. F. (2018). An inclusive methodology for Plug-in electrical vehicle operation with G2V and V2G in smart microgrid environments. International Journal of Electrical Power & Energy Systems, 102, 312-323. doi:10.1016/j.ijepes.2018.04.037Ghosh, S., & Chattopadhyay, S. (2020). Three-Loop-Based Universal Control Architecture for Decentralized Operation of Multiple Inverters in an Autonomous Grid-Interactive Microgrid. IEEE Transactions on Industry Applications, 56(2), 1966-1979. doi:10.1109/tia.2020.2964746Mohapatra, S. R., & Agarwal, V. (2020). Model Predictive Control for Flexible Reduction of Active Power Oscillation in Grid-Tied Multilevel Inverters Under Unbalanced and Distorted Microgrid Conditions. IEEE Transactions on Industry Applications, 56(2), 1107-1115. doi:10.1109/tia.2019.2957480Ziouani, I., Boukhetala, D., Darcherif, A.-M., Amghar, B., & El Abbassi, I. (2018). Hierarchical control for flexible microgrid based on three-phase voltage source inverters operated in parallel. International Journal of Electrical Power & Energy Systems, 95, 188-201. doi:10.1016/j.ijepes.2017.08.027Golshannavaz, S., & Mortezapour, V. (2018). A generalized droop control approach for islanded DC microgrids hosting parallel-connected DERs. Sustainable Cities and Society, 36, 237-245. doi:10.1016/j.scs.2017.09.038Safa, A., Madjid Berkouk, E. L., Messlem, Y., & Gouichiche, A. (2018). A robust control algorithm for a multifunctional grid tied inverter to enhance the power quality of a microgrid under unbalanced conditions. International Journal of Electrical Power & Energy Systems, 100, 253-264. doi:10.1016/j.ijepes.2018.02.042Andishgar, M. H., Gholipour, E., & Hooshmand, R. (2017). An overview of control approaches of inverter-based microgrids in islanding mode of operation. Renewable and Sustainable Energy Reviews, 80, 1043-1060. doi:10.1016/j.rser.2017.05.267Li, Z., Zang, C., Zeng, P., Yu, H., Li, S., & Bian, J. (2017). Control of a Grid-Forming Inverter Based on Sliding-Mode and Mixed ${H_2}/{H_\infty }$ Control. IEEE Transactions on Industrial Electronics, 64(5), 3862-3872. doi:10.1109/tie.2016.2636798Hossain, M. A., Pota, H. R., Squartini, S., & Abdou, A. F. (2019). Modified PSO algorithm for real-time energy management in grid-connected microgrids. Renewable Energy, 136, 746-757. doi:10.1016/j.renene.2019.01.005Shokoohi, S., Golshannavaz, S., Khezri, R., & Bevrani, H. (2018). Intelligent secondary control in smart microgrids: an on-line approach for islanded operations. Optimization and Engineering, 19(4), 917-936. doi:10.1007/s11081-018-9382-9Safari, A., Babaei, F., & Farrokhifar, M. (2019). A load frequency control using a PSO-based ANN for micro-grids in the presence of electric vehicles. International Journal of Ambient Energy, 42(6), 688-700. doi:10.1080/01430750.2018.1563811Miveh, M. R., Rahmat, M. F., Ghadimi, A. A., & Mustafa, M. W. (2016). Control techniques for three-phase four-leg voltage source inverters in autonomous microgrids: A review. Renewable and Sustainable Energy Reviews, 54, 1592-1610. doi:10.1016/j.rser.2015.10.079Rokrok, E., Shafie-khah, M., & Catalão, J. P. S. (2018). Review of primary voltage and frequency control methods for inverter-based islanded microgrids with distributed generation. Renewable and Sustainable Energy Reviews, 82, 3225-3235. doi:10.1016/j.rser.2017.10.022Bouzid, A. M., Guerrero, J. M., Cheriti, A., Bouhamida, M., Sicard, P., & Benghanem, M. (2015). A survey on control of electric power distributed generation systems for microgrid applications. Renewable and Sustainable Energy Reviews, 44, 751-766. doi:10.1016/j.rser.2015.01.016Vásquez, V., Ortega, L. M., Romero, D., Ortega, R., Carranza, O., & Rodríguez, J. J. (2017). Comparison of methods for controllers design of single phase inverter operating in island mode in a microgrid: Review. Renewable and Sustainable Energy Reviews, 76, 256-267. doi:10.1016/j.rser.2017.03.060Shen, X., Wang, H., Li, J., Su, Q., & Gao, L. (2019). Distributed Secondary Voltage Control of Islanded Microgrids Based on RBF-Neural-Network Sliding-Mode Technique. IEEE Access, 7, 65616-65623. doi:10.1109/access.2019.2915509Arbab-Zavar, B., Palacios-Garcia, E., Vasquez, J., & Guerrero, J. (2019). Smart Inverters for Microgrid Applications: A Review. Energies, 12(5), 840. doi:10.3390/en12050840Bullich-Massagué, E., Díaz-González, F., Aragüés-Peñalba, M., Girbau-Llistuella, F., Olivella-Rosell, P., & Sumper, A. (2018). Microgrid clustering architectures. Applied Energy, 212, 340-361. doi:10.1016/j.apenergy.2017.12.048Kerdphol, T., Rahman, F., Mitani, Y., Hongesombut, K., & Küfeoğlu, S. (2017). Virtual Inertia Control-Based Model Predictive Control for Microgrid Frequency Stabilization Considering High Renewable Energy Integration. Sustainability, 9(5), 773. doi:10.3390/su9050773Hajiakbari Fini, M., & Hamedani Golshan, M. E. (2018). Determining optimal virtual inertia and frequency control parameters to preserve the frequency stability in islanded microgrids with high penetration of renewables. Electric Power Systems Research, 154, 13-22. doi:10.1016/j.epsr.2017.08.007Jung, J., & Villaran, M. (2017). Optimal planning and design of hybrid renewable energy systems for microgrids. Renewable and Sustainable Energy Reviews, 75, 180-191. doi:10.1016/j.rser.2016.10.061Baharizadeh, M., Karshenas, H. R., & Guerrero, J. M. (2018). An improved power control strategy for hybrid AC-DC microgrids. International Journal of Electrical Power & Energy Systems, 95, 364-373. doi:10.1016/j.ijepes.2017.08.036Serban, I., & Ion, C. P. (2017). Microgrid control based on a grid-forming inverter operating as virtual synchronous generator with enhanced dynamic response capability. International Journal of Electrical Power & Energy Systems, 89, 94-105. doi:10.1016/j.ijepes.2017.01.009Tavakoli, M., Shokridehaki, F., Marzband, M., Godina, R., & Pouresmaeil, E. (2018). A two stage hierarchical control approach for the optimal energy management in commercial building microgrids based on local wind power and PEVs. Sustainable Cities and Society, 41, 332-340. doi:10.1016/j.scs.2018.05.035Cagnano, A., De Tuglie, E., & Cicognani, L. (2017). Prince — Electrical Energy Systems Lab. Electric Power Systems Research, 148, 10-17. doi:10.1016/j.epsr.2017.03.011Zhang, H., Meng, W., Qi, J., Wang, X., & Zheng, W. X. (2019). Distributed Load Sharing Under False Data Injection Attack in an Inverter-Based Microgrid. IEEE Transactions on Industrial Electronics, 66(2), 1543-1551. doi:10.1109/tie.2018.2793241Yang, L., Hu, Z., Xie, S., Kong, S., & Lin, W. (2019). Adjustable virtual inertia control of supercapacitors in PV-based AC microgrid cluster. Electric Power Systems Research, 173, 71-85. doi:10.1016/j.epsr.2019.04.011Rahman, F. S., Kerdphol, T., Watanabe, M., & Mitani, Y. (2019). Optimization of virtual inertia considering system frequency protection scheme. Electric Power Systems Research, 170, 294-302. doi:10.1016/j.epsr.2019.01.025Farrokhabadi, M., Canizares, C. A., Simpson-Porco, J. W., Nasr, E., Fan, L., Mendoza-Araya, P. A., … Reilly, J. (2020). Microgrid Stability Definitions, Analysis, and Examples. IEEE Transactions on Power Systems, 35(1), 13-29. doi:10.1109/tpwrs.2019.2925703Yoldaş, Y., Önen, A., Muyeen, S. M., Vasilakos, A. V., & Alan, İ. (2017). Enhancing smart grid with microgrids: Challenges and opportunities. Renewable and Sustainable Energy Reviews, 72, 205-214. doi:10.1016/j.rser.2017.01.064Rajesh, K. S., Dash, S. S., Rajagopal, R., & Sridhar, R. (2017). A review on control of ac microgrid. Renewable and Sustainable Energy Reviews, 71, 814-819. doi:10.1016/j.rser.2016.12.106Marzal, S., Salas, R., González-Medina, R., Garcerá, G., & Figueres, E. (2018). Current challenges and future trends in the field of communication architectures for microgrids. Renewable and Sustainable Energy Reviews, 82, 3610-3622. doi:10.1016/j.rser.2017.10.101Singh, A., & Suhag, S. (2018). Trends in Islanded Microgrid Frequency Regulation – A Review. Smart Science, 7(2), 91-115. doi:10.1080/23080477.2018.1540380Hou, X., Sun, Y., Lu, J., Zhang, X., Koh, L. H., Su, M., & Guerrero, J. M. (2018). Distributed Hierarchical Control of AC Microgrid Operating in Grid-Connected, Islanded and Their Transition Modes. IEEE Access, 6, 77388-77401. doi:10.1109/access.2018.2882678SHI, R., ZHANG, X., HU, C., XU, H., GU, J., & CAO, W. (2017). Self-tuning virtual synchronous generator control for improving frequency stability in autonomous photovoltaic-diesel microgrids. Journal of Modern Power Systems and Clean Energy, 6(3), 482-494. doi:10.1007/s40565-017-0347-3Toub, M., Bijaieh, M. M., Weaver, W. W., III, R. D. R., Maaroufi, M., & Aniba, G. (2019). Droop Control in DQ Coordinates for Fixed Frequency Inverter-Based AC Microgrids. Electronics, 8(10), 1168. doi:10.3390/electronics8101168Shuai, Z., Fang, J., Ning, F., & Shen, Z. J. (2018). Hierarchical structure and bus voltage control of DC microgrid. Renewable and Sustainable Energy Reviews, 82, 3670-3682. doi:10.1016/j.rser.2017.10.096Agundis-Tinajero, G., Segundo-Ramírez, J., Visairo-Cruz, N., Savaghebi, M., Guerrero, J. M., & Barocio, E. (2019). Power flow modeling of islanded AC microgrids with hierarchical control. International Journal of Electrical Power & Energy Systems, 105, 28-36. doi:10.1016/j.ijepes.2018.08.002Ali, A., Li, W., Hussain, R., He, X., Williams, B., & Memon, A. (2017). Overview of Current Microgrid Policies, Incentives and Barriers in the European Union, United States and China. Sustainability, 9(7), 1146. doi:10.3390/su9071146Cui, Y., Geng, Z., Zhu, Q., & Han, Y. (2017). Review: Multi-objective optimization methods and application in energy saving. Energy, 125, 681-704. doi:10.1016/j.energy.2017.02.174Yazdi, F., & Hosseinian, S. H. (2019). A novel «Smart Branch» for power quality improvement in microgrids. International Journal of Electrical Power & Energy Systems, 110, 161-170. doi:10.1016/j.ijepes.2019.02.026Bassey, O., Butler-Purry, K. L., & Chen, B. (2020). Dynamic Modeling of Sequential Service Restoration in Islanded Single Master Microgrids. IEEE Transactions on Power Systems, 35(1), 202-214. doi:10.1109/tpwrs.2019.2929268Chang, E.-C. (2018). Study and Application of Intelligent Sliding Mode Control for Voltage Source Inverters. Energies, 11(10), 2544. doi:10.3390/en11102544Das, D., Gurrala, G., & Shenoy, U. J. (2018). Linear Quadratic Regulator-Based Bumpless Transfer in Microgrids. IEEE Transactions on Smart Grid, 9(1), 416-425. doi:10.1109/tsg.2016.2580159Nguyen, H. K., Khodaei, A., & Han, Z. (2018). Incentive Mechanism Design for Integrated Microgrids in Peak Ramp Minimization Problem. IEEE Transactions on Smart Grid, 9(6), 5774-5785. doi:10.1109/tsg.2017.2696903Xiao, Z., Guerrero, J. M., Shuang, J., Sera, D., Schaltz, E., & Vásquez, J. C. (2018). Flat tie-line power scheduling control of grid-connected hybrid microgrids. Applied Energy, 210, 786-799. doi:10.1016/j.apenergy.2017.07.066Baghaee, H. R., Mirsalim, M., Gharehpetian, G. B., & Talebi, H. A. (2018). A Decentralized Robust Mixed $H_{{2}}/ H_{{{\infty }}}$ Voltage Control Scheme to Improve Small/Large-Signal Stability and FRT Capability of Islanded Multi-DER Microgrid Considering Load Disturbances. IEEE Systems Journal, 12(3), 2610-2621. doi:10.1109/jsyst.2017.2716351Panda, S. K., & Ghosh, A. (2020). A Computational Analysis of Interfacing Converters with Advanced Control Methodologies for Microgrid Application. Technology and Economics of Smart Grids and Sustainable Energy, 5(1). doi:10.1007/s40866-020-0077-xZhang, L., Chen, K., Lyu, L., & Cai, G. (2019). Research on the Operation Control Strategy of a Low-Voltage Direct Current Microgrid Based on a Disturbance Observer and Neural Network Adaptive Control Algorithm. Energies, 12(6), 1162. doi:10.3390/en12061162Zhu, K., Sun, P., Zhou, L., Du, X., & Luo, Q. (2020). Frequency-Division Virtual Impedance Shaping Control Method for Grid-Connected Inverters in a Weak and Distorted Grid. IEEE Transactions on Power Electronics, 35(8), 8116-8129. doi:10.1109/tpel.2019.2963345Samavati, E., & Mohammadi, H. R. (2019). Simultaneous voltage and current harmonics compensation in islanded/grid-connected microgrids using virtual impedance concept. Sustainable Energy, Grids and Networks, 20, 100258. doi:10.1016/j.segan.2019.100258Shi, K., Ye, H., Song, W., & Zhou, G. (2018). Virtual Inertia Control Strategy in Microgrid Based on Virtual Synchronous Generator Technology. IEEE Access, 6, 27949-27957. doi:10.1109/access.2018.2839737Fathi, A., Shafiee, Q., & Bevrani, H. (2018). Robust Frequency Control of Microgrids Using an Extended Virtual Synchronous Generator. IEEE Transactions on Power Systems, 33(6), 6289-6297. doi:10.1109/tpwrs.2018.2850880Amoateng, D. O., Al Hosani, M., Elmoursi, M. S., Turitsyn, K., & Kirtley, J. L. (2018). Adaptive Voltage and Frequency Control of Islanded Multi-Microgrids. IEEE Transactions on Power Systems, 33(4), 4454-4465. doi:10.1109/tpwrs.2017.2780986Sopinka, A., & Pitt, L. (2013). British Columbia Electricity Supply Gap Strategy: A Redefinition of Self-Sufficiency. The Electricity Journal, 26(3), 81-88. doi:10.1016/j.tej.2013.03.003Baghaee, H. R., Mirsalim, M., Gharehpetian, G. B., & Talebi, H. A. (2018). Decentralized Sliding Mode Control of WG/PV/FC Microgrids Under Unbalanced and Nonlinear Load Conditions for On- and Off-Grid Modes. IEEE Systems Journal, 12(4), 3108-3119. doi:10.1109/jsyst.2017.2761792Gholami, S., Saha, S., & Aldeen, M. (2018). Robust multiobjective control method for power sharing among distributed energy resources in islanded microgrids with unbalanced and nonlinear loads. International Journal of Electrical Power & Energy Systems, 94, 321-338. doi:10.1016/j.ijepes.2017.07.012Mousazadeh Mousavi, S. Y., Jalilian, A., Savaghebi, M., & Guerrero, J. M. (2018). Autonomous Control of Current- and Voltage-Controlled DG Interface Inverters for Reactive Power Sharing and Harmonics Compensation in Islanded Microgrids. IEEE Transactions on Power Electronics, 33(11), 9375-9386. doi:10.1109/tpel.2018.2792780Fani, B., Zandi, F., & Karami-Horestani, A. (2018). An enhanced decentralized reactive power sharing strategy for inverter-based microgrid. International Journal of Electrical Power & Energy Systems, 98, 531-542. doi:10.1016/j.ijepes.2017.12.023Khayat, Y., Naderi, M., Shafiee, Q., Batmani, Y., Fathi, M., Guerrero, J. M., & Bevrani, H. (2019). Decentralized Optimal Frequency Control in Autonomous Microgrids. IEEE Transactions on Power Systems, 34(3), 2345-2353. doi:10.1109/tpwrs.2018.2889671Arcos-Aviles, D., Pascual, J., Marroyo, L., Sanchis, P., & Guinjoan, F. (2018). Fuzzy Logic-Based Energy Management System Design for Residential Grid-Connected Microgrids. IEEE Transactions on Smart Grid, 9(2), 530-543. doi:10.1109/tsg.2016.2555245Alyazidi, N. M., Mahmoud, M. S., & Abouheaf, M. I. (2018). Adaptive critics based cooperative control scheme for islanded Microgrids. Neurocomputing, 272, 532-541. doi:10.1016/j.neucom.2017.07.027Buduma, P., & Panda, G. (2018). Robust nested loop control scheme for LCL‐filtered inverter‐based DG unit in grid‐connected and islanded modes. IET Renewable Power Generation, 12(11), 1269-1285. doi:10.1049/iet-rpg.2017.0803Batiyah, S., Sharma, R., Abdelwahed, S., & Zohrabi, N. (2020). An MPC-based power management of standalone DC microgrid with energy storage. International Journal of Electrical Power & Energy Systems, 120, 105949. doi:10.1016/j.ijepes.2020.105949Baghaee, H. R., Mirsalim, M., Gharehpetan, G. B., & Talebi, H. A. (2018). Nonlinear Load Sharing and Voltage Compensation of Microgrids Based on Harmonic Power-Flow Calculations Using Radial Basis Function Neural Networks. IEEE Systems Journal, 12(3), 2749-2759. doi:10.1109/jsyst.2016.2645165Benhalima, S., Miloud, R., & Chandra, A. (2018). Real-Time Implementation of Robust Control Strategies Based on Sliding Mode Control for Standalone Microgrids Supplying Non-Linear Loads. Energies, 11(10), 2590. doi:10.3390/en11102590California Carbon Market Watch: A Comprehensive Analysis of the Golden State’s Cap-and-Trade Program, Year One—2012–2013. 2014https://www.issuelab.org/resource/california-carbon-market-watch-a-comprehensive-analysis-of-the-golden-state-s-cap-and-trade-program-year-one-2012-2013.htmlExploring the Best Possible Trade-Off between Competing Objectives: Identifying the Pareto Fronthttps://pythonhealthcare.org/2018/09/27/93-exploring-the-best-possible-trade-off-between-competing-objectives-identifying-the-pTeekaraman, Y., Kuppusamy, R., & Nikolovski, S. (2019). Solution for Voltage and Frequency Regulation in Standalone Microgrid using Hybrid Multiobjective Symbiotic Organism Search Algorithm. Energies, 12(14), 2812. doi:10.3390/en12142812Zeng, Z., Li, H., Tang, S., Yang, H., & Zhao, R. (2016). Multi‐objective control of multi‐functional grid‐connected inverter for renewable energy integration and power quality service. IET Power Electronics, 9(4), 761-770. doi:10.1049/iet-pel.2015.0317Wu, Y., Guerrero, J. M., Vasquez, J. C., & Wu, Y. (2019). Bumpless Optimal Control over Multi-Objective Microgrids with Mode-Dependent Controllers. Energies, 12(19), 3619. doi:10.3390/en12193619Sedighizadeh, M., Esmaili, M., & Eisapour-Moarref, A. (2017). Voltage and frequency r