Design of Robust Higher Order Sliding Mode Control for Microgrids

Cucuzzella, Michele; Incremona, Gian Paolo; Ferrara, Antonella

doi:10.1109/jetcas.2015.2450411

Cited by 89 publications

(61 citation statements)

References 52 publications

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“…However, to highlight the superiority of the proposed control scheme, the robust higher-order sliding mode (RHOSM) control method in literature [26] and the PI method were also executed on the microgrid system. The second-order sliding mode control parameters were designed as U i,max = 4.8 × 10 7 and α α i = 0.9 for the grid-connected mode and the third-order sliding mode control parameters were chosen as 15 , α r q = 5.0 × 10 15 for the islanding mode.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…To the authors' knowledge, other adaptive versions of an HOSM control scheme for microgrid operation for both grid-connected and islanding modes does not currently exist. However, to highlight the superiority of the proposed control scheme, the robust higher-order sliding mode (RHOSM) control method in literature [26] and the PI method were also executed on the microgrid system. The second-order sliding mode control parameters were designed as Figure 3.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…A single-line diagram of a master-slave microgrid with nDGus [26,29] is shortly shown in Figure 1. Each microsource is a generally renewable energy type and is represented by a DC voltage source, which is connected with the main grid via VSI, RL filter, and PCC.…”

Section: Microgrid Modelingmentioning

confidence: 99%

“…I Td and I Tq can track the reference values by designing a first-order sliding mode control law for Formulas (26) and (27). However, the control chattering is severe, which is harmful to VSI operation and has a strong impact on the lifetime of a power electronic device.…”

Section: Adaptive Second-order Sliding Mode Control For Grid-connectementioning

confidence: 99%

“…However, the system only had asymptotic stability. Finite time stability for islanding operation was achieved based a third-order sliding mode control scheme in [26]. However, the microgrid model (controlled object) was treated as a black box in this method, which led to conservative parameter choice.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Higher-Order Sliding Mode Control for Islanding and Grid-Connected Operation of a Microgrid

Han

Cui

2018

Energies

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Grid-connected and islanding operations of a microgrid are often influenced by system uncertainties, such as load parameter variations and unmodeled dynamics. This paper proposes a novel adaptive higher-order sliding mode (AHOSM) control strategy to enhance system robustness and handle an unknown uncertainty upper bounds problem. Firstly, microgrid models with uncertainties are established under islanding and grid-connected modes. Then, adaptive third-order sliding mode and adaptive second-order sliding mode control schemes are respectively designed for the two modes. Microgrid models' descriptions are divided into nominal part and uncertain part, and higher-order sliding mode (HOSM) control problems are transformed into finite time stability problems. Again, a scheduled law is proposed to increase or decrease sliding mode control gain adaptively. Real higher-order sliding modes are established, and finite time stability is proven based on the Lyapunov method. In order to achieve smooth mode transformation, an islanding mode detection algorithm is also adopted. The proposed control strategy accomplishes voltage control and current control of islanding mode and grid-connected mode. Control voltages are continuous, and uncertainty upper bounds are not required. Furthermore, adjustable control gain can further whittle control chattering. Simulation experiments verify the validity and robustness of the proposed control scheme.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Microgrid Modelingmentioning

confidence: 99%

Section: Adaptive Second-order Sliding Mode Control For Grid-connectementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adaptive Higher-Order Sliding Mode Control for Islanding and Grid-Connected Operation of a Microgrid

Han

Cui

2018

Energies

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Lypunov theory combined with small signal linearization for regulated operation of a hybridDC/ACmicrogrid

Souraki

Radmehr

Rezanejad

2020

Int Trans Electr Energ Syst

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Summary This paper proposes a new control strategy for enforcing a AC‐DC hybrid microgrid to attain stable responses in both steady state and dynamic operating conditions. The proposed controller is designed based on combining direct Lyapunov method and small signal linearization (SSL). The dynamic parts of converter control functions are achieved through providing the global asymptotical stability of the hybrid microgrid by using its total saved energy function. Then, the steady‐state components of the controller, unlike other existing Lyapunov‐based methods, are obtained according to SSL‐based mathematical terms as the main novelty of this paper. This novelty simultaneously provides several contributions within the proposed control technique structure as (a) the direct control of the PCC voltage frequency and DC‐link voltage errors, (b) the enhanced decoupling feature for DC/AC converter current, and (c) the direct control of the input voltage error for bidirectional DC/DC converter. Finally, comparative simulation results in MATLAB/Simulink software are presented to verify the superiority of proposed controller combined with SSL under AC and DC load variations, discharging/charging of storage unit, different grid power factors and AC loads shared among grid side and DC sources.

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Power sharing adaptive control strategy for a microgrid with multiple storage and renewable energy sources

Sedaghati

Shakarami

2018

Adaptive Control & Signal

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SummaryWith the rapid growth of single‐phase renewable energy source units within three‐phase microgrids, the accuracy of the power sharing per phase among distributed generation (DG) units is necessary. This paper proposes an adaptive power control strategy based on new sliding mode control for islanding operation of a microgrid with multiple three‐phase and single‐phase DGs. The studied microgrid consists of two three‐phase photovoltaic (PV) arrays and three single‐phase DG units, which include PV, fuel cell, and battery systems. In order to control the three‐phase DGs properly, an observer is used to estimate the uncertain system parameters. Then, according to the estimated values, a controller is adapted to the new system conditions. In this control strategy, one of the three‐phase PV arrays is responsible for adjusting the voltage and frequency, and the other is responsible for controlling the load current to manage the power of three‐phase inverters. To control the single‐phase DGs, their power and voltage references are assigned based on the corresponding phase of the three‐phase DGs responsible for power and voltage control. Subsequently, the power and voltage control operation is performed in a per‐unit system. The proposed control strategy is strongly stable against variation of conditions, disturbances, and microgrid parameter uncertainties, and it regulates the active and reactive powers injected by DGs. The feasibility of the proposed control strategy is validated using simulation studies on a multibus islanded microgrid with balanced and unbalanced loading conditions via MATLAB/Simulink software. The results indicate that the proposed approach is able to provide faster response and lower steady‐state error compared with the conventional proportional integral controller.

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Design of Robust Higher Order Sliding Mode Control for Microgrids

Cited by 89 publications

References 52 publications

Adaptive Higher-Order Sliding Mode Control for Islanding and Grid-Connected Operation of a Microgrid

Adaptive Higher-Order Sliding Mode Control for Islanding and Grid-Connected Operation of a Microgrid

Lypunov theory combined with small signal linearization for regulated operation of a hybridDC/ACmicrogrid

Power sharing adaptive control strategy for a microgrid with multiple storage and renewable energy sources

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