Grid power fluctuation reduction by fuzzy control based energy management system in residential microgrids

Islam, Mojaharul; Yang, Fang; Ekanayek, Chandima; Ամին, Մոհամմադ

doi:10.1002/etep.2758

Cited by 18 publications

(16 citation statements)

References 25 publications

(37 reference statements)

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“…Figure 8 shows the FL EPC performance, during the simulation, where the variation of P Bat , wich has numbers favorable for the SOC and remains within the limits of 50% and 100%. However this did not show a significant change, in addition, the peaks of power are −4kW and 2kW ; on the other hand, P Grid has peaks of power between −5kW and 5kW indicating a balance between the power injected and the power rectified [49], [50], [54].…”

Section: Numerical Resultsmentioning

confidence: 88%

“…Nowadays, three popular Fuzzy Logic strategies (FL) used as PMS are the Fuzzy Logic Control based on Net Power Trend (FLC NPT) [49], the Fuzzy Logic Control based on Energy Rate of Charge (FLC ERC) [50], and the Fuzzy Logic Control based on Grid Fluctuation (FLC GF) [54]. In the FLC NPT, the diffuse controller considers the tendency of the power flow in the MG to minimize the power exchange with the main grid; while extending the life of the storage unit against the charging and discharging cycles.…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Logic Power Management Strategy for a Residential DC-Microgrid

et al. 2020

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Power management strategies (PMS) are applied to keep a balance, between different energy sources (i.e. solar, wind, geothermal, hydro), storage units (i.e. fuel cell, batteries, fly wheel) and loads. Up to date, there has been reported several advance techniques to solve this task, for instance: Fuzzy Logic, Deep Learning, Droop Control, Bayesian Networks, among others. Nevertheless, some of those PMS are over simplified and others are too complex to be programmed in devices with limited resources. To solve these issues, this paper proposes a PMS based on Fuzzy Logic, which keeps a balance between those two goals. Characteristics of the proposed PMS are a small number of rules; fulfillment of the demanded power at every time; reducing use of the storage unit; and keeping a balance between the different sources, storage unit and loads. The proposed PMS is numerically evaluated by using SIMULINK-MATLAB®, in a 10kW residential DC Microgrid (MG), and validated by using a Hardware in the Loop platform (NI myRio-1900 and Typhoon HIL402). A comparison with three popular advance techniques demonstrates the feasibility of the proposed PMS.

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Section: Numerical Resultsmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Power Management Strategy for a Residential DC-Microgrid

et al. 2020

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“…A short‐term tie‐line fluctuation was analyzed in Reference 23, and a fuzzy logic controller was designed in a dynamic EMS to control the battery in a grid‐connected residential MG. However, the result showed that the method reduces tie‐line fluctuation but is unable to maintain constant tie‐line control.…”

Section: Introductionmentioning

confidence: 99%

Dynamic control of grid‐connected microgrids for tie‐line smoothing

Islam

Yang

Ամին

2020

Int Trans Electr Energ Syst

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Summary This paper presents an interlink inverter control method for providing a constant tie‐line smoothing service in a grid‐connected residential microgrid (MG) to mitigate the fluctuating nature of renewable power generation and load demand. A grid power controller is designed for an MG to keep a constant grid power on typical days of the year by maintaining the charging/discharging of the battery. To achieve this objective, the MG controller sends the reference to the interlink inverter controller based on load dynamics, average PV generation and battery capacity. Moreover, a state‐space model is developed from the dynamic model of the MG system, and an eigenvalue‐based stability analysis is performed for different system parameters. The proposed control method is verified through extensive case studies by using real irradiance and typical residential customer load data in Queensland, Australia. In addition, a comparison with a dynamic energy management‐based method that aims to achieve the same objective is presented to demonstrate the performance of the proposed control method. Results show that the proposed method provides a constant tie‐line power for a grid‐connected residential MG for typical days of the year.

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“…In addition, a generic-based controller with flexible power flow capability has been proposed for hybrid microgrid in Eajal et al, 39 paying attention to the droop controllability of the distributed resources and bidirectional power flow in the interlinking converters. Several combined adaptive fault-tolerant control algorithms in Vargas-Martinez et al, 43 a hierarchical control included adaptive droop method and a new hybrid firefly optimized P-Q and V-f controller coordination in Satapathy et al 44 and a fuzzy control based on energy management system in Islam et al, 45 have been proposed to control various structures of a microgrid system. Designing the robustness, partial feedback linearization in Mahmud et al 41 and a feed-forward control strategy with internal model robust feedback control in Wang et al 42 has verified the importance of considering the nonlinearity features of microgrid dynamic models.…”

mentioning

confidence: 99%

“…Designing the robustness, partial feedback linearization in Mahmud et al 41 and a feed-forward control strategy with internal model robust feedback control in Wang et al 42 has verified the importance of considering the nonlinearity features of microgrid dynamic models. Several combined adaptive fault-tolerant control algorithms in Vargas-Martinez et al, 43 a hierarchical control included adaptive droop method and a new hybrid firefly optimized P-Q and V-f controller coordination in Satapathy et al 44 and a fuzzy control based on energy management system in Islam et al, 45 have been proposed to control various structures of a microgrid system.…”

mentioning

confidence: 99%

Distributed energy storage system‐based nonlinear control strategy for hybrid microgrid power management included wind/PV units in grid‐connected operation

Holari

Taher

Mehrasa

2019

Int Trans Electr Energ Syst

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Summary In this paper, a control strategy based on a combination of Lyapunov theory and input‐output feedback linearization (IOFL) has been proposed to provide stable operation for a hybrid DC/AC microgrid under unbalanced generations of the AC units. The DC link of the considered hybrid microgrid was supplied through photovoltaic (PV)‐based buck and lithium battery‐based (LB‐based) bidirectional DC/DC converters. A DC/AC converter was connected to the DC link and set to provide the required active and reactive power for reaching the desired waveforms for the point of common coupling (PCC) voltages. To accurately control the aforementioned converters, the mathematical equations were first achieved and then the proposed IOFL was designed to obtain the control inputs. To enhance the IOFL performance, several control loops regarding DC link voltage variations were considered for all converters. The main contribution of the proposed IOFL is that the control input of the LB‐based bidirectional DC/DC converter consists of both control inputs of the DC link‐connected inverter. As another contribution of this paper, total energy due to the control inputs' errors was completely investigated through the Lyapunov theory, leading to effective dynamic parts for the control inputs. In addition, the DC and AC power sharing was comprehensively evaluated based on both AC and DC specifications. For further analysis, the effects of angular frequency variations on the inverter control inputs were presented. Simulation results through MATLAB/SIMULINK software verified the accuracy and ability of the proposed control strategy.

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Grid power fluctuation reduction by fuzzy control based energy management system in residential microgrids

Cited by 18 publications

References 25 publications

Fuzzy Logic Power Management Strategy for a Residential DC-Microgrid

Fuzzy Logic Power Management Strategy for a Residential DC-Microgrid

Dynamic control of grid‐connected microgrids for tie‐line smoothing

Distributed energy storage system‐based nonlinear control strategy for hybrid microgrid power management included wind/PV units in grid‐connected operation

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