This paper proposes a distributed coordinated voltage control scheme for distribution networks with distributed generation (DG) and on-load tap changer (OLTC). In this scheme, static synchronous ...compensators (STATCOMs), DG units and OLTC are coordinated to regulate voltages of all buses to be close to the nominal value in the distribution network, mitigate voltage fluctuations, and minimize the number of operations of OLTC while considering different temporal characteristics of voltage regulation devices. The optimization problem of coordinating DG units and STATCOMs is decomposed by the gradient projection (GP) method. The local controller optimizes the reactive power outputs of DGs and STATCOMs according to local voltage and reactive power measurements, and still achieves the optimal coordination of DG units and STATCOMS in a decentralized manner without a central controller or communication between local controllers. The OLTC control scheme is designed to correct the long-term voltage deviations based on model predictive control (MPC) while minimizing the number of operations. The local controllers send the calculated reactive power references of DG and STATCOMs to the OLTC controller, which achieves distributed coordinated voltage control and mitigates the computation burden. A distribution network with two 20 kV feeders and 8 DG units was used to validate the control performance of the proposed coordinated voltage control scheme.
This study focuses on the equitable loss allocation method for radial distribution networks integrated with distributed generators (DGs). As the traditional Shapley value method may cause a ...combinational explosion problem, the authors propose a sampling method for estimating the actual Shapley value. They use a stratified sampling method (SSM) to reduce the number of samples of Shapley value method with the subject to the overall equilibrium constraint. To determine the number of samples drawn from each stratum, they use the Neyman optimum allocation to minimise the variance of the sample mean. A reinforcement learning algorithm is introduced to estimate the standard deviations of the strata needed for the optimal stratified sampling. The proposed method is applied to a modified 17-bus distribution network and an actual distribution network in Zhejiang Province, People's Republic of China. The simulation results show that the proposed method can not only resolve the combinational explosion problem of Shapley value method but retain its desirable characteristics. The proposed method can dramatically reduce computational time by implementing a SSM. Therefore, the efficiency and superiority of the proposed method with regards to loss allocation are verified for radial distribution networks that include DGs.
Input-series-output-parallel (ISOP) isolated bidirectional direct current (dc)/dc converter (IBdc) becomes a preferred scheme connecting high-voltage and low-voltage bus in dc distribution network. ...Input-voltage-sharing (IVS) among modules is essential to realize the stable operation of ISOP system. Nowadays, with large-scale access of distributed energy sources and loads in dc grids, the fluctuations in bus voltage and connected load become frequent and great, deteriorating the IVS performance and stable operation of ISOP structure IBdc. To solve this issue, a triple-close-loop IVS strategy is proposed in this article. Compared with the conventional IVS strategy with constant input impedance, the proposed IVS strategy reshapes input impedance to be a full-order model containing high-order components and sensitive to fluctuation of output voltage, and IVS control based on reshaped impedance improves dynamics feature, maintains ideal output power, and avoids false protection and potential instability for ISOP structure IBdc under frequent and large fluctuation. Experimental results verify the correctness and effectiveness of the analysis and proposed strategy, providing a feasible, efficient, and practical control scheme for ISOP system in dc distribution network.
Fast-acting reactive power support from distributed generations (DGs) is a promising approach for tackling rapid voltage fluctuations in distribution networks. However, the voltage regulation range ...via reactive power of DGs alone is narrow especially in distribution networks with high resistance-reactance ratio. In this paper, a randomized algorithm is proposed to improve the voltage profile in distribution networks via coordinated regulation of the active and reactive power of DGs. To this end, first the variables of the proposed quadratically constrained quadratic programming problem on voltage control are partitioned into disjoint subsets, each of which corresponds to a unique low-dimensional subproblem. Second, these subsets are updated serially in a randomized manner via solving their corresponding subproblems, which overcomes the requirement for system-wide coordination among participating agents and guarantees an optimal solution. Compared with the existing algorithms, the proposed algorithm is resilient to network reconfigurations and achieves a wider voltage regulation range. The effectiveness and convergence performance of the proposed algorithm is validated by the case studies.
With the increasing penetration of renewable energy (RE), the operations of distribution network are threatened and some issues may appear, i.e., large voltage deviation, deterioration of statistic ...voltage stability, high power loss, etc. In turn, RE accommodation would be significantly impacted. Therefore, we propose a many-objective distribution network reconfiguration (MDNR) model, with the consideration of RE curtailment, voltage deviation, power loss, statistic voltage stability, and generation cost. This aims to assess the trade-off among these objectives for better operations of distribution networks. As the proposed model is a non-convex, non-linear, many-objective optimization problem, it is difficult to be solved. We further propose a deep reinforcement learning (DRL) assisted multi-objective bacterial foraging optimization (DRL-MBFO) algorithm. This algorithm combines the advantages of DRL and MBFO, and is targeted to find the Pareto front of proposed MDNR model with better searching efficiency. Finally, we conduct case study on the modified IEEE 33-bus, 69-bus, and 118-bus power distribution systems, and results verify the effectiveness of the MDNR model and outperformance of the proposed DRL-MBFO.
Integration of rooftop photovoltaic (PV) systems in a three-phase four-wire distribution network cause voltage-violations namely voltage-rise and voltage unbalance. This study investigates the ...factors that affect both the voltage-rise and voltage unbalance in low voltage distribution network integrated with the rooftop PV systems. The concerning factors are classified into active factors such as; loads active powers, PV active powers, and bus reactive powers, and passive factors such as; numbers of feeder buses and neutral-grounded resistances. The study also determines the factors conditions at which the highest values of both voltage-rise and voltage unbalance occurred. Moreover, the most and least significant effects of individual factors on both voltage-rise and voltage unbalance are studied. The studied system is simulated and implemented in MATLAB software environment and the feeder loads are modelled based on Back–Forward Sweep method. The simulation results identify that the conditions of the worst voltage-rise and voltage unbalance cases depend on the collective influence of the studied factors.
The highly penetrated distributed generators (DGs) aggravate the voltage violations in active distribution networks (ADNs). The coordination of various regulation devices such as on-load tap changers ...(OLTCs) and DG inverters can effectively address the voltage issues. Considering the problems of inaccurate network parameters and rapid DG fluctuation in practical operation, multi-source data can be utilized to establish the data-driven control model. In this paper, a data-driven voltage control method with the coordination of OLTC and DG inverters on multiple time-scales is proposed without relying on the accurate physical model. First, based on the multi-source data, a data-driven voltage control model is established. Multiple regulation devices such as OLTC and DG are coordinated on multiple time-scales to maintain voltages within the desired range. Then, a critical measurement selection method is proposed to guarantee the voltage control performance under the partial measurements in practical ADNs. Finally, the proposed method is validated on the modified IEEE 33-node and IEEE 123-node test cases. Case studies illustrate the effectiveness of the proposed method, as well as the adaptability to DG uncertainties.
This article provides a unique benchmark to integrate and systematically evaluate advanced functionalities of microgrid and downstream device controllers. The article describes Banshee, a real-life ...power distribution network. It also details a real-time controller hardware-in-the-loop (HIL) prototyping platform to test the responses of the controllers and verify decision-making algorithms. The benchmark aims to address power industry needs for a common basis to integrate and evaluate controllers for the overall microgrid, distributed energy resources (DERs), and protective devices. The test platform will accelerate microgrid deployment, enable standard compliance verification, and further develop and test controllers' functionalities. These contributions will facilitate safe and economical demonstrations of the state-of-the-possible while verifying minimal impact to existing electrical infrastructure. All aspects of the benchmark and platform development including models, configuration files, and documentation are publicly available via the electric power HIL controls collaborative (EPHCC).
In the traditional dc distribution networks with both a low-voltage dc (LVdc) and a medium-voltage dc (MVdc) bus, dc units, such as photovoltaics solar, storage devices, and dc loads, are connected ...to the LVdc bus through LVdc converters, such as dc/dc boost converters and bidirectional buck-boost dc/dc converters. In this approach, no galvanic isolation is provided and two power conversion stages are needed between the dc units and the MVdc grid, hence leading to a high number of converters and higher costs. To address these shortcomings, this article proposes a novel multiport dc solid-state transformer (MDCSST) to interface these dc units directly to the MVdc bus. Multiple modules are connected in series on the medium-voltage side to the MVdc bus, whereas dc units are independently connected on the low-voltage side of the MDCSST. Compared with a traditional dc distribution network, the proposed scheme connects dc units to the MVdc bus without an extra converter or an LVdc bus, therefore, saving cost and reducing the number of converters. In addition, dc units are galvanically isolated by high-frequency transformers. The main challenge of the MDCSST is to resolve the voltage-imbalance problem on the MVdc side, which is caused by the dc units' power differences. An LC branch is used to balance the voltages among the modules and to transfer their differential powers. Simulations and experiments were carried out to validate the proposed approach and verify the theoretical analysis.
Distribution networks are evolving into active meshed networks with bidirectional power flow as the penetration of distributed generation (DG) sources is increasing. This necessitates the use of ...directional relaying schemes in these emerging active distribution networks. However, conventional directional overcurrent (OC) protection will not be adequate to protect these networks against the stochastic nature of renewable DGs and the changing network architectures. Hence, this study proposes an adaptive directional OC relay algorithm that determines optimal protection settings according to varying fault currents and paths induced by the DGs in active meshed distribution networks. The proposed algorithm consists of a two-phase approach that deduces: (i) optimal floating current settings through a fuzzy decision-making module, and (ii) optimal floating time settings through an optimisation algorithm. Extensive case studies are implemented on the modified power distribution networks of IEEE 14-bus and IEEE 30-bus by varying the type, location, and size of DGs. The results validate the ability of the proposed protection scheme to capture the uncertainties of the DGs and determine optimal protection settings, while ensuring minimal operating time.
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