A resilient self‐healing approach for active distribution networks considering dynamic microgrid formation

With increasing connection of distributed generations (DGs), the power flow in electric distribution network is no longer unidirectional and the network has become active distribution network. Thus, the connection of DGs in electric distribution networks has created a challenge for distribution network operators due to bidirectional power flow. One of the main technical challenges of an active distribution network is to maintain an acceptable voltage level in the system. This has initiated efforts in using various voltage control strategies to regulate the network voltage profile so that the voltage is maintained at its allowable voltage limits. A number of voltage control methods have been applied to solve voltage control problems associated with the connection of DGs in a distribution system. These voltage control strategies may be classified as decentralized or distributed and centralized or coordinated voltage control. From the literature, a number of coordinated voltage control strategies have been implemented to provide better and faster control to the system. This chapter presents an improved coordinated voltage control method in active electric distribution network by coordinating the three voltage control methods, namely, power factor control, on load tap changer control and generation curtailment control. These voltage control methods are coordinated using fuzzy logic by considering the load bus voltages and DG power as inputs and the voltage control actions as the outputs. The fuzzy logic if-then control rules which are generated to build the fuzzy logic control system are based on the simulations results as well as from the previous works. Results obtained using the fuzzy logic based coordinated voltage control has shown that the voltages are able to be kept within its permissible limits.

With the decentralization of the electricity market and the plea for a carbon-neutral ecosystem, more and more distributed generation (DG) has been incorporated in the power distribution grid, which is then known as active distribution network (ADN). The addition of DGs causes numerous control and protection confronts to the traditional distribution network. For instance, two-way power flow, small fault current, persistent fluctuation of generation and demand, and uncertainty of renewable energy sources (RESs). These problems are more challenging when the distribution network hosts many converter-coupled DGs. Hence, the traditional protection schemes and relaying methods are inadequate to protect ADNs against short-circuit faults and disturbances. We propose a robust communication-assisted fault protection technique for safely operating ADNs with high penetration of converter-coupled DGs. The proposed technique is realizable by employing digital relays available in the recent market and it aims to protect low-voltage (LV) ADNs. It also includes secondary protection that can be enabled when the communication facility or protection equipment fails to operate. In addition, this study provides the detail configuration of the digital relay that enables the devised protection technique. Several enhancements are derived, as alternative technique for the traditional overcurrent protection approach, to detect small fault current and high-impedance fault (HIF). A number of simulations are performed with the complete model of a real ADN, in Shenyang, China, employing the PSCAD software platform. Various cases, fault types and locations are considered for verifying the efficacy of the devised technique and the enabling digital relay. The obtained simulation findings verify the proposed protection technique is effective and reliable in protecting ADNs against various fault types that can occur at different locations.

The power grid is going through significant changes with the introduction of renewable energy sources and the incorporation of smart grid technologies. These rapid advancements necessitate new models and analyses to keep up with the various emergent phenomena they induce. A major prerequisite of such work is the acquisition of well-constructed and accurate network datasets for the power grid infrastructure. In this paper, we propose a robust, scalable framework to synthesize power distribution networks that resemble their physical counterparts for a given region. We use openly available information about interdependent road and building infrastructures to construct the networks. In contrast to prior work based on network statistics, we incorporate engineering and economic constraints to create the networks. Additionally, we provide a framework to create ensembles of power distribution networks to generate multiple possible instances of the network for a given region. The comprehensive dataset consists of nodes with attributes, such as geocoordinates; type of node (residence, transformer, or substation); and edges with attributes, such as geometry, type of line (feeder lines, primary or secondary), and line parameters. For validation, we provide detailed comparisons of the generated networks with actual distribution networks. The generated datasets represent realistic test systems (as compared with standard test cases published by Institute of Electrical and Electronics Engineers (IEEE)) that can be used by network scientists to analyze complex events in power grids and to perform detailed sensitivity and statistical analyses over ensembles of networks.

Significant increase of distributed generation (DG) presence and active distribution network (ADN) development cause changes in distribution network’s power quality (PQ), mostly in distorted system voltages and currents. This paper analyses harmonics generation from multiple DG types, such as solar and biogas power plants, and simulates harmonic interactions in ADN in order to identify potential PQ issues. Each harmonic source observed in this paper was modelled according to IEC 61000 with the model parameters provided by power quality measurements in the real system on several DG power plants and passive consumer nodes. A harmonic load flow is performed on a detailed ADN model for different presumed DG expansion scenarios that indicate the complexity of the DG impact on the AND’s PQ. Quantitative and qualitative graphical presentation for cumulative and the most significant ADN nodes is given and the assessment for the potential ADN development based on PQ indices is proposed.

The large-scale integration of distributed photovoltaics (PV) can cause reverse power flow due to an imbalance between load and PV generation, altering the voltage profile in traditional distribution networks. The uncertainties in PV output can also cause voltage violations in the distribution network. Conventional methods for assessing static stability in voltage within such systems utilize continuous power flow techniques to calculate the load margin index, which provides a measure of how stable the voltage is in the distribution network. Nevertheless, the frequent load margin calculations in such methods result in significant computational costs, rendering them impractical for networks with distributed generators (DGs). Conventional static voltage stability assessment methods typically use continuation power flow (CPF) to calculate load margins but face significant computational bottlenecks in active distribution networks with distributed generation. For instance, even with improved power flow algorithms, a 33-bus system requires 58 iterations and about 0.3–0.5 seconds per analysis; in large-scale systems with tens of thousands of buses, total evaluation time can exceed 10 minutes. This paper introduces the holomorphic embedding load flow method (HELM), which accommodates different bus types (PI, PQ, PV) in active distribution networks. Building on HELM, a voltage partial sensitivity method is proposed, providing a criterion for evaluating the voltage stability in distribution networks. The sensitivity-based stability criteria using holomorphic embedding functions consider various DG operating conditions without requiring maximum load margin computation. The efficient calculation of these indexes makes the approach ideal for managing voltage in systems that include distribution networks with DGs. Finally, these indexes are used to manage voltage in active distribution networks, and the effectiveness of the method is confirmed through comprehensive numerical examples.

In order to meet the high permeability and the access of large scale distributed generation, at present and in the future, active distribution network becomes the trend of smart grid research. This paper introduces the influence of distribution network voltage distribution and stability of distributed energy access based on active distribution network; The reactive power and voltage optimization control method of active power distribution network is summarized from the aspects of optimal voltage regulation measure, voltage regulation measure of power network equipment, reactive power optimal dispatch of power system, and so on. Analysis of the current status of the research, and summarized the existing active distribution network with a distributed power pickup distribution network reactive power and voltage control of the existence of some problems and the insufficiency still some problems that must be solved in the study of reactive power and voltage optimization control of active distribution network are pointed out.

With the access of distributed generators (DG), the power flow direction and structure of distribution networks have changed, and therefore many traditional fault location methods are no longer applicable. Single-phase grounding fault is a common fault in power distribution network, which may bring secondary fault and even blackout. Starting from the relationship between the wavelet eigenvalues of traveling waves and the fault section of distribution lines with DG, the optimal fault features were selected by dimension reduction of linear discriminant analysis (LDA), and then the Bayesian classification model based on kernel distribution was used to realize the new method of Single phase grounding fault location. The IEEE 33-bus model with DGs was constructed to test the faults in different sections of active distribution network, the locating accuracy of the optimal three-dimensional feature sample is 97.9%. The result shows the method can achieve accurate fault location.

With the increasing integration of distribution generations (DGs), active distribution networks (ADNs) need to address the new challenges in voltage control. Meanwhile, the traditional centralized method in reactive power optimization usually leads to a heavy computational burden for large-scale distribution networks. A distributed voltage control model with a novel network partitioning method is proposed in this study, where the capacity curve of DGs and the regulation of electrical storage systems (ESS) are specially addressed. According to the number of decision variables and the number of constraints in the optimization model, the computational complexity can be utilized in the network partitioning method with the power balance and the electrical distance to automatically partition a distribution network in an optimal manner. Taking the coordination between two boundary sub-areas into consideration, a distributed voltage control strategy is developed and solved by a distributed solution method based on Lagrangian dual relaxation. Finally, numerical studies based on two IEEE test systems and a practical 152-bus system are performed to verify the effectiveness of the proposed method.

The International Institute of Knowledge Innovation and Invention (IIKII) is an institute that promotes the exchange of innovations and inventions, and establishes a communication platform for international innovations and researches. In 2019, IIKII cooperated with the Institute of Electrical and Electronics Engineers (IEEE) Tainan Section Sensors Council to hold IEEE conferences such as IEEE ICIASE 2019, IEEE ECBIOS 2019, IEEE ICKII 2019, ICUSA-GAME 2019, and IEEE ECICE 2019. This Special Issue entitled “Selected Papers from IIKII 2019 conferences” aims to select excellent papers from IIKII 2019 conferences, including symmetry in physics, chemistry, biology, mathematics, and computer science, etc. It selected 21 excellent papers from 750 papers presented in IIKII 2019 conferences on the topic of symmetry. The main goals of this Special Issue are to encourage scientists to publish their experimental and theoretical results in as much detail as possible, and to discover new scientific knowledge relevant to the topic of symmetry.

This paper presents a feature comparison between the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) Release 8 and Institute of Electrical and Electronics Engineers (IEEE) 802.16m and preliminary system performance comparison. As Orthogonal Frequency Division Multiple Access (OFDMA) mobile broadband air interfaces, LTE and IEEE 802.16m are both International Mobile Telecommunications-Advanced (IMT-Advanced) technologies. LTE and IEEE 802.16m, which both make use of Multiple-Input Multiple-Output (MIMO) channels, have their own features and advantages. This paper compares some features between LTE and IEEE 802.16m in terms of frame structure, effective bandwidth, Hybrid Automatic Retransmission Request (HARQ) and Modulation and Coding Scheme (MCS), which is a valuable replenishment to the former work. The system simulation results show that LTE and IEEE 802.16m achieve similar performance although they are different communication evolution systems from different specification work groups.

Economic development relies on access to electrical energy, which is crucial for society’s growth. However, power shortages are challenging due to non-renewable energy depletion, unregulated use, and a lack of new energy sources. Ethiopia’s Debre Markos distribution network experiences over 800 h of power outages annually, causing financial losses and resource waste on diesel generators (DGs) for backup use. To tackle these concerns, the present study suggests a hybrid power generation system, which combines solar and biogas resources, and integrates Superconducting Magnetic Energy Storage (SMES) and Pumped Hydro Energy Storage (PHES) technologies into the system. The study also thoroughly analyzes the current and anticipated demand connected to the distribution network using a backward/forward sweep load flow analysis method. The results indicate that the total power loss has reached its absolute maximum, and the voltage profiles of the networks have dropped below the minimal numerical values recommended by the Institute of Electrical and Electronics Engineers (IEEE) standards (i.e., 0.95–1.025 p.u.). After reviewing the current distribution network’s operation, additional steps were taken to improve its effectiveness, using metaheuristic optimization techniques to account for various objective functions and constraints. In the results section, it is demonstrated that the whale optimization algorithm (WOA) outperforms other metaheuristic optimization techniques across three important objective functions: financial, reliability, and greenhouse gas (GHG) emissions. This comparison is based on the capability of the natural selection whale optimization algorithm (NSWOA) to achieve the best possible values for four significant metrics: Cost of Energy (COE), Net Present Cost (NPC), Loss of Power Supply Probability (LPSP), and GHG Emissions. The NSWOA achieved optimal values for these metrics, namely 0.0812 €/kWh, 3.0017 × 106 €, 0.00875, and 7.3679 × 106 kg reduced, respectively. This is attributable to their thorough economic, reliability, and environmental evaluation. Finally, the forward/backward sweep load flow analysis employed during the proposed system’s integration significantly reduced the impact of new energy resources on the distribution network. This was evident in the reduction of total power losses from 470.78 to 18.54 kW and voltage deviation from 6.95 to 0.35 p.u., as well as the voltage profile of the distribution system being swung between 1 and 1.0234 p.u., which now comply with the standards set by the IEEE. Besides, a comparison of the cost and GHG emission efficiency of the proposed hybrid system with existing (grid + DGs) and alternative (only DGs) scenarios was done. The findings showed that, among the scenarios examined, the proposed system is the most economical and produces the least amount of GHG emissions.

Summary A distribution network with distributed generation (DG) is usually called an active distribution network. The voltage quality in an active distribution network tends to degrade because of the bidirectional power flow in the network and the random output characteristic of DG. Existing voltage control methods cannot effectively address this issue. In this article, an improved differential evolution (DE) algorithm–based optimal series compensation voltage control method for an active distribution network is presented. It is assumed that the series compensating voltage is produced flexibly by modern power electronics equipment. The quantitative relationship connecting the node voltage deviation, network power loss and compensating voltage is analysed. The optimal control model, including the power loss and load node voltage, is constructed. Then an improved DE algorithm is proposed to solve the optimal model, which combines the standard DE approach with the simulated annealing and adaptive mutation operator method. The optimal control model can be solved effectively by the improved algorithm. A simulation model is developed based on the IEEE 33 standard distribution network with DG. Simulation results confirm the validity of the optimal control model and the advantages of the improved DE algorithm.

With recent development of technology and management in power market and equipment, more and more distributed generation (DG) is embedded in the distribution network. However the approach of connecting DG in most cases is based on a so-called ‘fit and forget’ policy and the capacity of DG is limited rigidly by distribution system operator to avoid the negative effects of high level penetration. New management technologies have been proposed to handle the integration of DGs in the distribution networks. In this review, the micro grid (MG) was treated as the local control method to coordinate DGs within a small area of distribution network. And the active distribution network (AND) was treated as the global control mechanism to actively manage DGs, MGs and other equipment. The operation framework of ADN was firstly introduced. Then based on the static and dynamic models of DGs and MGs, impacts of DGs and MGs on the ADN are surveyed from power quality, stability to the operation. Finally, the conclusion and suggestion is given in this paper.

The increased distributed generators (DGs) have exacerbated voltage violations in active distribution networks (ADNs). Local reactive power control of DG inverters can realize a fast response to frequent voltage fluctuations. However, commonly used model-based voltage control depends upon accurate network parameters and entire ADN data, which may cause the sensitive information leakage of ADN and DG behaviors in practical operation. In this article, a cloud-edge collaboration-based local voltage control strategy for DGs is proposed with privacy preservation. First, a local voltage control framework is established based on cloud-edge collaboration, in which a surrogate model is built based on the graph convolutional neural networks to estimate the ADN voltages. By transferring the surrogate model, the edge side can obtain the exact voltage estimation in the local curve tuning process without the authority of the whole ADN data, preserving the network parameters of ADN. Then, the interarea coordination based on federated learning is proposed to realize the parameter updating of DG control curves, which can achieve better voltage control performance. By updating surrogate submodels based on private data distributed across multiple edge devices, federated learning can effectively preserve DG behaviors. Finally, the effectiveness and adaptability of the proposed control strategy are validated using the modified IEEE 33-node system. The proposed local DG control strategy can effectively cope with voltage problems and enhance the adaptability to variations in practical operation states while considering privacy preservation.

The massive accessing of unbalance and nonlinear loads to a power distribution network may cause serious problems on power quality and result in additional power loss and safety risks. Distributed generation (DG) with a converter interface has a flexible adjusting ability and can provide certain unbalance and harmonic compensations to power distribution networks. In this paper, an optimal operation method of an active distribution network (ADN) involving the unbalance and harmonic compensation of a converter was proposed. First, the power regulating characteristics of DG were analyzed. Second, an optimization model was constructed to minimize ADN power loss, sum of harmonic voltage squares, and total unbalance of the negative sequence voltage, and multiple constraints, such as converters and network, were considered in the model. Third, the optimization model was transformed into a semidefinite programming model based on the characteristics of the nonconvex and nonlinear original model, thus assuring global convergence and decreasing difficulties in problem solving. Finally, the validity of the proposed algorithm was verified by using IEEE 33-node and 123-node test systems.