A Novel Cooperative Control Technique for Hybrid AC/DC Smart Microgrid Converters

Jasim, Ali M.; Jasim, Basil H.; Bureš, Vladimír; Mikulecký, Peter

doi:10.1109/access.2023.3234011

Cited by 17 publications

(6 citation statements)

References 52 publications

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“…Te main inverter is controlled by discrete PR controllers, as illustrated in Figure 4, for both the selected control techniques in gridconnected or island mode of operation. Te authors of [34,41] presented the modeling of the PR controller, which is introduced as follows.…”

Section: Dc/ac Inverter Control Methodmentioning

confidence: 99%

“…Inevitably, energy injection or reduction is needed to maintain grid power balance because the power produced by wind and solar renewables is intermittently greater or less than demand [32]. Numerous coordination control techniques based on PI, hysteresis, PR controllers, and deadbeat controllers can be adopted to interface power inverters with the power system [5][6][7][33][34][35]. While the PR control method is often employed to rectify the sine signals harmonics and minimize steady-state error, PI regulators provide greater error and are consistent with the parameter-adjusting issue [33].…”

Section: Introductionmentioning

confidence: 99%

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Coordinated Control and Load Shifting-Based Demand Management of a Smart Microgrid Adopting Energy Internet

Jasim,

Alhasnawi

et al. 2023

International Transactions on Electrical Energy Systems

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High renewable energy penetration worsens systems instability. Balancing consumption energy and generation output energy reduces this instability. This paper introduces coordination control to coordinate the flow of electricity between MG buses and to stabilize the system under variable load, generation conditions. The adopted MG regulates the bidirectional DC/AC main converter using digital proportional resonant controllers in a synchronous reference frame. A maximum power point tracker-based boost DC/DC converter enables the wind turbine and solar photovoltaic to harvest maximum power. Traditional methods such as perturb and observe and incremental conductance maximum power trackers cannot solve nonlinearity and inaccurate responses. This work provides a hybrid maximum power tracker strategy to modify the responses of standard maximum power point techniques based on particle swarm optimization-trained adaptive neuro-fuzzy inference system (ANFIS-PSO) to achieve quick and maximum solar power with minimal oscillation tracking. Concerning the management system, this paper adopts a recent meta-heuristic algorithms-based DSM program to modify consumers’ electricity use by shifting the load appliances to off-peak demand periods. The adopted algorithms for DSM are sparrow search algorithm (SSA), binary orientation search algorithm (BSOA), and cockroach algorithm (CA). Finally, based on energy Internet technology, ThingSpeak cloud-based MATLAB is adopted to gather and display real-time data streams and generate graphical analyses. The simulation results reveal that the recommended coordinating control produces quick grid frequency responsiveness and zero steady-state errors. The optimal demand management program minimizes peak energy consumption from 5.2 kWh to 4.6 kWh. All DSM methods cost 439.1 $ per month, compared to 484.4 $ for the nonscheduling load profile.

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Section: Dc/ac Inverter Control Methodmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Coordinated Control and Load Shifting-Based Demand Management of a Smart Microgrid Adopting Energy Internet

Jasim,

Alhasnawi

et al. 2023

International Transactions on Electrical Energy Systems

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“…Te voltage and current controllers use generalized integrators (GI) to eliminate steady-state error. Te transfer function of the PR controller is described by the following equation [43,44].…”

Section: Proposed Primary Controlmentioning

confidence: 99%

Consensus-Based Intelligent Distributed Secondary Control for Multiagent Islanded Microgrid

Jasim

Aymen

et al. 2023

International Transactions on Electrical Energy Systems

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Isolated microgrids (MGs) face challenges in performance stability and active/reactive power sharing as a result of frequency/voltage deviations and mismatched line impedance issues. In this paper, a consensus-based multiagent system (MAS) is proposed as a solution to restore voltage/frequency deviations and enable true power sharing. The invention of an Intelligent Distributed Secondary Control Scheme (IDSCS) can efficiently achieve hoped-for outcomes. The proposed IDSCS features estimation and compensation sublayers. For the estimation sublayer, discrete dynamic consensus algorithm-based state estimators are presented to collect average information of frequency, voltage, and reactive power. Each DG is viewed as an agent sharing information with its immediate neighbors through a sparse cyber communication network. In the compensation sublayer, online tuned proportional integral (PI) controllers using artificial neural networks (ANNs) are proposed as an intelligent voltage and frequency compensators. This combination uses the simplicity of the PI controller mathematical formula and ANN’s ability to deal with parameter variations and nonlinearity. Due to the global nature of the frequency parameter, the active power-sharing compensator is unnecessary. For compensating reactive power deviations, ANNs-based reactive power controllers are proposed. Furthermore, at the primary control level, the proposed strategy employs discrete-time proportional resonant (PR) controllers in a stationary reference frame, eliminating the need for any α β / d q or d q / α β transformations. Distributed implementation of the proposed method guarantees system scalability without MG topology or demand pattern expertise. The control scheme was validated using hypothetical MAS in MATLAB Simulink platform. The simulation findings indicate the proposed MG system can effectively distribute power among the DGs while maintaining voltage and frequency stable.

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“…In order to minimize the ripple of the peak current (∆I) and ensure that the capacitor does not resonate with the inductor, it is important to select an inductor with a high value. Equation (40) describes the relationship between the inductor value and the ripple of the peak current. Additionally, the value of the capacitor should be chosen to minimize the ripple voltage (∆V C ).…”

Section: Mg Subsystemmentioning

confidence: 99%

Energy Internet-Based Load Shifting in Smart Microgrids: An Experimental Study

Jasim

Mohseni

et al. 2023

Energies

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This study investigated a grid-connected smart microgrid (MG) system integrating solar photovoltaic (PV) panels and a battery energy storage system (BESS) as distributed energy resources (DERs) to locally serve residential loads. The load-shifting demand-side management (DSM) technique was employed to effectively manage the load appliances. The proposed load-shifting algorithm relies on minimum price incentives to allow customers to allocate their load appliances economically during minimum price periods. The algorithm considers the waiting times and minimum tariff periods for appliances, calculates precise operating durations for each appliance, and prioritizes powering the appliances from the MG first, followed by the main grid. The system comprises two non-shiftable and three shiftable loads. When the MG power is insufficient to activate all shiftable loads, the system transfers the remaining unsupplied shiftable appliances to periods with low-priced energy. The Energy Internet concept is adopted to manage energy and monitor usage when a customer is unable to check the accuracy of their energy meter by supervising the system’s features on-site. The proposed comprehensive system enables load management, continuous monitoring, customer awareness, and energy cost saving. Six cases were studied, both numerically and experimentally, with varying MG power generation and load pre-scheduling periods, with and without DSM application. In all adopted cases, the implemented system save energy costs by at least 50%.

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A Novel Cooperative Control Technique for Hybrid AC/DC Smart Microgrid Converters

Cited by 17 publications

References 52 publications

Coordinated Control and Load Shifting-Based Demand Management of a Smart Microgrid Adopting Energy Internet

Coordinated Control and Load Shifting-Based Demand Management of a Smart Microgrid Adopting Energy Internet

Consensus-Based Intelligent Distributed Secondary Control for Multiagent Islanded Microgrid

Energy Internet-Based Load Shifting in Smart Microgrids: An Experimental Study

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