Optimal design of controllers and harmonic compensators for three-level cascaded control in stationary reference frame for grid-supporting inverters-based AC microgrid

Ebrahim, Mohamed A.; Aziz, Beshoy Abdou; Nashed, Maged N. F.; Osman, Fawzy A.

doi:10.1016/j.egyr.2021.11.248

Cited by 20 publications

(3 citation statements)

References 35 publications

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“…A hybrid optimization system refers to a combination of different optimization algorithms or techniques such as p-metaheuristic, s-metaheuristic, machine learning, and mathematical programming that are integrated to improve algorithm efficiency, reduce search time, provide better quality solutions, improve effectiveness, provide accuracy, and solve complex optimization problems [42][43][44][45][46][47][48][49][50] . Exploration and exploitation are typically the two different phases of the process in metaheuristic optimization.…”

Section: Proposed Hybrid Optimization Systemmentioning

confidence: 99%

Hybrid cheetah particle swarm optimization based optimal hierarchical control of multiple microgrids

Mohamed,

Mahmoud,

Saied

et al. 2024

Sci Rep

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The emergence of microgrids arises from the growing integration of Renewable Energy Resources (RES) and Energy Storage Systems (ESSs) into Distribution Networks (DNs). Effective integration, coordination, and control of Multiple Microgrids (MMGs) whereas navigating the complexities of energy transition within this context poses a significant challenge. The dynamic operation of MMGs is a challenge faced by the traditional distributed hierarchical control techniques. The application of Artificial Intelligence (AI) techniques is a promising way to improve the control and dynamic operation of MMGs in future smart DNs. In this paper, an innovative hybrid optimization technique that originates from Cheetah Optimization (CHO) and Particle Swarm Optimization (PSO) techniques is proposed, known as HYCHOPSO. Extensive benchmark testing validates HYCHOPSO’s superiority over CHO and PSO in terms of convergence performance. The objective for this hybridization stems from the complementary strengths of CHO and PSO. CHO demonstrates rapid convergence in local search spaces, while PSO excels in global exploration. By combining these techniques, the aim is to leverage their respective advantages and enhance the algorithm's overall performance in addressing complex optimization problems. The contribution of this paper offering a unique approach to addressing optimization challenges in microgrid systems. Through a comprehensive comparative study, HYCHOPSO is evaluated against various metaheuristic optimization approaches, demonstrating superior performance, particularly in optimizing the design parameters of Proportional-Integral (PI) controllers for hierarchical control systems within microgrids. This contribution expands the repertoire of available optimization methodologies and offers practical solutions to critical challenges in microgrid optimization, enhancing the efficiency, reliability, and sustainability of microgrid operations. HYCHOPSO achieves its optimal score within fewer than 50 iterations, unlike CHO, GWO, PSO, Hybrid-GWO-PSO, and SSIA-PSO, which stabilize after around 200 iterations. Across various benchmark functions, HYCHOPSO consistently demonstrates the lowest mean values, attains scores closer to the optimal values of the benchmark functions, underscoring its robust convergence capabilities.the proposed HYCHOPSO algorithm, paired with a PI controller for distributed hierarchical control, minimizes errors and enhances system reliability during dynamic MMG operations. Using HYCHOPSO framework, an accurate power sharing, voltage/frequency stability, seamless grid-to-island transition, and smooth resynchronization are achieved. This enhances the real application's reliability, flexibility, scalability and robustness.

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Section: Proposed Hybrid Optimization Systemmentioning

confidence: 99%

Hybrid cheetah particle swarm optimization based optimal hierarchical control of multiple microgrids

Mohamed,

Mahmoud,

Saied

et al. 2024

Sci Rep

Self Cite

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“…The main core of the developed control structure for the suggested energy management system is a PI regulator. In the presented research, the Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Absolute Error (ITAE), and Integral Time Square Error (ITSE) are chosen as performance indices to accomplish the tuning process [39][40][41][42][43][44]. The most significant results with the number of iterations (itr), objective function (Obj.…”

Section: Harris Hawks Optimization-based Energy Management Schemementioning

confidence: 99%

Optimal Energy Management Solutions Using Artificial Intelligence Techniques for Photovoltaic Empowered Water Desalination Plants Under Cost Function Uncertainties

et al. 2022

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Two modern methods of the energy management system (EMS) based on a modified cost function are addressed in this paper. Fuzzy logic (FL) and Harris Hawks Optimization (HHO) is implemented to achieve the optimal performance of seawater desalination plants (SWDP) within the minimum feed-in tariff (FiT). The technical difficulties involved in the variation of energy price from one time to another and the system parameters uncertainties. For example, the price of energy is higher at the peak time and the price is lower at normal times. Also, the peak time can change from one day to another day. The proposed management system can deal with these variations and uncertainty cases. The suggested EMS is achieved through a bidirectional electrical energy interchange approach (π-EEIA). The main concept behind the proposed π-EEIA is how and when to inject the excess generated energy of renewable energy into the utility grid or charge the battery depending on the minimum dynamic cost criterion and vice versa. To accomplish this study a 700 m 3 /day SWDP located in Egypt fed on solar energy and a utility network has been constructed and analyzed. The system includes SWDP fed from a photovoltaic (PV) array as well as the utility grid in addition to a battery energy storage system (BESS). The main objective of this study is the management and coordination between the energy exchange process from the solar energy, the utility network, and BESS to provide sufficient electrical energy for SWDP within the minimum FiT. The system is constructed and validated using the MATLAB/SIMULINK TM software package. The proposed FL and HHO-based EMSs are investigated in the presence of the system uncertainties such as the change in the energy (excess or shortage) as well as the change in the energy price in the utility network (high or low) with (normal or peak) time. The attained results demonstrate that the proposed FL and HHO-based EMSs provide high dynamic performance and accurate coordination between various energy resources and BESS. The results show that FL-based EMS achieves a profit of 10.28 $ but the HHO-based EMS achieves a profit of 10.11 $ in the same period.

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“…Regardless of the method used to limit the current, all of them aim to limit the total current, without discriminating between the different current components of this current. With this regard, the limitation of the AHF capability in case of VSC overload has been previously explored in current controllers for active power filters: saturation approaches [37], [38], virtual impedance techniques [39] and optimization algorithms [40]. However, the limitation of the AHF capability in case of VSC overcurrent with direct harmonic voltage tracking remains unexplored.…”

Section: Introductionmentioning

confidence: 99%

Active Harmonic Filtering With Selective Overcurrent Limitation for Grid-Forming VSCs: Stability Analysis and Experimental Validation

Matas-Díaz,

Barragán-Villarejo,

Maza-Ortega

et al. 2024

IEEE Trans. on Ind. Applicat.

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The high penetration of renewable energy sources (RES) interfaced with power electronics together with new nonlinear loads pose new challenges in the grid operation. In fact, power systems with reduced inertia and high harmonic distortion will be common in a near future. Recently, the grid-forming operation of voltage source converters (VSCs) has emerged to address these challenges, mimicking the contribution of synchronous generators to the system inertia. In addition, these grid-connected VSCs can be used at the same time for reducing the harmonic distortion by applying active filtering techniques. However, these harmonic compensation algorithms can generate VSC overloading. This paper proposes a method for dynamically adjusting the individual virtual impedance of the filtered harmonics to prevent the power converter overcurrent. For this purpose, the value of each harmonic virtual impedance is modified according to a priority which can be set by the final user according to the established power quality standard. The paper includes a theoretical stability analysis of the controller and experimental results to validate the proposed algorithm.

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Optimal design of controllers and harmonic compensators for three-level cascaded control in stationary reference frame for grid-supporting inverters-based AC microgrid

Cited by 20 publications

References 35 publications

Hybrid cheetah particle swarm optimization based optimal hierarchical control of multiple microgrids

Hybrid cheetah particle swarm optimization based optimal hierarchical control of multiple microgrids

Optimal Energy Management Solutions Using Artificial Intelligence Techniques for Photovoltaic Empowered Water Desalination Plants Under Cost Function Uncertainties

Active Harmonic Filtering With Selective Overcurrent Limitation for Grid-Forming VSCs: Stability Analysis and Experimental Validation

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