Research on a Novel AC/DC Hybrid Microgrid Based on Silicon Controlled Converters and Polarity Reversal Switches
Sensors
Abstract and Figures
In order to reduce the economic costs, enhance the efficiency, and improve the structural stability of microgrids, this paper proposes a novel AC/DC hybrid microgrid structure. This structure, based on Silicon Controlled Converters (SCCs) and Polarity Reversal Switches (PRSs), enables bidirectional power flow and provides a low-cost and straightforward control solution. This paper elaborates on the overall control strategy of the microgrid under different states of the PRS and introduces the control logic of the Current Reversible Chopper (CRC) circuit. For typical daily scenarios across the four seasons, where wind and photovoltaic (PV) power generation outputs and load demands vary, this study combines sampled data to investigate the coordinated configuration scheme of wind energy, PV energy, and energy storage within the microgrid, and analyzes the state changes in the PRS. Furthermore, this paper conducts simulation analysis of the microgrid under different states of the PRS and during the switching process of the PRS, verifying the feasibility of the proposed new structure. Finally, this paper compares the proposed structure with traditional microgrid structures in terms of economics, system efficiency, and structural stability, and analyzes the impact of this structure on the frequency, inertia, and multi-energy interaction of the system.
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Using hybrid energy storage systems, we propose a power mode partitioning control strategy for AC/DC microgrids that effectively mitigates frequency and voltage fluctuations. By incorporating composite virtual impedance, we categorize the state of charge (SOC) into five distinct operational modes. Supercapacitors, known for their dynamic response, are prioritized to counteract power fluctuations. We assign these operational modes to the AC and DC subnetworks based on real-time changes in frequency and voltage. When significant fluctuations occur, coordinated power transmission between the subnetworks and support from the energy storage system ensure that frequency and voltage remain within acceptable limits. Simulations conducted in MATLAB/Simulink confirmed that this control strategy stabilized power fluctuations and addressed the challenges of overcharging and overdischarging in storage batteries.
This paper puts forward a new practical voltage source converter (VSC) based AC-DC converter model suitable for conducting power flow assessment of multi-terminal VSC-based high-voltage direct current (VSC-MTDC) systems. The model uses an advanced method to handle the operational limits and control modes of VSCs into the power flow formulation. The new model is incorporated into a unified framework encompassing AC and DC power grids and is solved by using the Newton-Raphson method to enable quadratically convergent iterative solutions. The use of complementarity constraints, together with the Fischer-Burmeister function, is proposed to enable the seamless incorporation of operational control modes of VSC and automatic enforcement of any converter's operational limits that become violated during the iterative solution process. Thus, a dedicated process for checking limits is no longer required. Furthermore, all existing relationships between the VSC control laws and their operational limitsare considered directly during the solution of the power flow problem. The applicability of the new model is demonstrated with numerical examples using various multi-terminal AC-DC transmission networks, one of which is a utility-sized power system.
The increasing penetration of renewable energy resources (RESs) facilitates the carbon footprint reduction process yet reduces the power system inertia. As a result, the grid frequency and the rate of change of frequency (RoCoF) might probably go beyond the normal range, resulting in unexpected load shedding, generator tripping, and even frequency instability. To address this problem, grid-connected inverters are designed to participate infrequency regulation and provide the equivalent inertial support. Nevertheless, the inertia emulation effect is affected by the inverter synchronization dynamic and high RoCoF events may occur as the result of poor synchronization dynamics. In view of this limitation, a synthetic inertia control is developed in this paper considering the synchronization dynamics. The synthetic inertia principles and control design guideline are explicitly provided. Finally, hardware experimental results of a scaled-down power system prototype are provided to validate the effectiveness of the proposed approach.
This paper presents a 120MW capacity solar photovoltaic (PV) plant with a battery energy storage (BES). This plant has utilized high-power 72-pulse voltage source converters (VSCs), developed using six multi-winding transformers and twelve three-level neutral-point-clamped (NPC) converters. 72-pulse operation of the VSC is realized by suitably selecting the transformers phase-shifting and NPCs switching phase-displacement angles. The multi-MPPT approach is applied in the VSC to optimize energy generation from the solar PV array. This solar PV plant has utilized DC-coupled BES, which is distributed along with the solar PV array field in the plant area. The excess PV energy is stored in the BES locally and dispatched the same during nighttime when PV array is not generating using the same solar VSC and DC and AC electrical equipments. Thus, it offers a saving on investment cost. Additionally, the VSC is utilized to provide reactive power to the grid. A developed MATLAB model of the solar PV and BES plant is presented along with the OPAL-RT real-time implementation strategy, and steady-state, harmonics and dynamic responses are obtained.
Poor power sharing of hybrid ac/dc microgrid leads to the inefficient operation of distributed generators (DGs). Besides, the lack of inertia caused by droop and phase-locked loop-based current control brings negative effects to the system. In this article, we propose a distributed normalized power coordination (NPC) embedded with virtual synchronous generator for hybrid microgrid. The proposed NPC controller can achieve cross inertia support, accurate global power sharing, and frequency/voltage recovery among dispatchable DGs simultaneously. Furthermore, to suppress frequency and power oscillation, the index of inertia deviation is proposed to guide the inertia placement of hybrid MG based on Participation Factor analysis. Finally, the proposed strategy is validated by the simulation and hardware-in-loop tests compared to the conventional methods.
This paper presents a novel load-flow method for unbalanced islanded ac microgrids. The principles of this method are based on the modified augmented nodal analysis (MANA) formulation. It is shown that it can considerably improve the performance over conventional mismatch equation-based solvers for islanded microgrids, while being more generic and simpler to formulate. An unbalanced 25-bus ac microgrid is used to verify the validity and efficiency of the proposed MANA-based formulation. The results are compared against mismatch formulation to demonstrate better computational speed and reduced number of iterations.
Voltage Source Converter (VSC) for grid integration of renewable energies are prone to have small-signal stability issues when connected to weak AC grids. Such stability issues largely arise from the lack of VSC control adaptivity to the varying grid condition (e.g., grid impedance). To address this issue, this letter presents an adaptive multi-parameter tuning method using the Artificial Neural Network. Innovative aspect of the proposal lies in that it enables the VSC to simultaneously tune multiple controller parameters online, which brings about a
pole-tracking
-based stabilization control feature for the VSC. Experimental results demonstrate that the proposed method can effectively and adaptively stabilize the VSC when the grid impedance is varied.
Battery energy storage system (BESS) plays an important role in solving problems in which the intermittency has to be considered while operating distribution network (DN) penetrated with renewable energy. Aiming at this problem, this paper proposes a global centralized dispatch model that applies BESS technology to DN with renewable energy source (RES). The method proposed in this paper aims to minimize the power purchase cost considering network active loss cost as well as voltage deviation penalty cost. Later, second-order cone programming (SOCP) method as well as big M method are applied to make the problem tractable. Last, the method illustrated in this paper is applied and validated on a modified IEEE 33-bus benchmark system to verify the effectiveness of the proposed scheduling model.
This letter investigates a Branching Dueling Q-Network (BDQ) based online operation strategy for a microgrid with distributed battery energy storage systems (BESSs) operating under uncertainties. The developed deep reinforcement learning (DRL) based microgrid online optimization strategy can achieve a linear increase in the number of neural network outputs with the number of distributed BESSs, which overcomes the curse of dimensionality caused by the charge and discharge decisions of multiple BESSs. Numerical simulations validate the effectiveness of the proposed method.
In dc microgrid, energy storage system (ESS) plays a crucial role to provide short-or-long term and high-quality electric energy. The different control strategies for bidirectional dc-dc converter (BDC) of ESS in grid-tied and islanded modes pose challenges to the coordination control of the dc microgrid. This paper proposes an autonomous control scheme for the BDC in dc microgrid. The proposed control scheme is based on
droop control and unifies bus voltage regulation and power regulation in a single control structure. Thus, global smooth transition between various operation modes can be achieved without any control strategy changes, which avoids various mode switch detection mechanisms and improves system stability. Furthermore, the proposed control scheme is fully decentralized which reduces the reliance on communication, and enhances the reliability of the microgrid. On the other hand,
droop approach eliminates the negative effect of widespread constant power loads (CPLs) in dc microgrid. The stability of the proposed control method is illustrated, and the design guideline of some critical control gains is addressed. Finally, the effectiveness of the proposed control scheme is validated by the real-time hardware-in- loop (HIL) platform.