Continuously expanding deployments of distributed power-generation systems (DPGSs) are transforming the conventional centralized power grid into a mixed distributed electrical network. The modern power grid requires flexible energy utilization but presents challenges in the case of a high penetration degree of renewable energy, among which wind and solar photovoltaics are typical sources. The integration level of the DPGS into the grid plays a critical role in developing sustainable and resilient power systems, especially with highly intermittent renewable energy resources. To address the challenging issues and, more importantly, to leverage the energy generation, stringent demands from both utility operators and consumers have been imposed on the DPGS. Furthermore, as the core of energy conversion, numerous power electronic converters employing advanced control techniques have been developed for the DPGS to consolidate the integration. In light of the above, this paper reviews the power-conversion and control technologies used for DPGSs. The impacts of the DPGS on the distributed grid are also examined, and more importantly, strategies for enhancing the connection and protection of the DPGS are discussed.

/pdf/distributed-power-generation-systems-and-protection-3g8dq2p3up.pdf

Distributed Power-Generation Systems and Protection

Fault detection is essential in microgrid control and operation, as it enables the system to perform fast fault isolation and recovery. The adoption of inverter-interfaced distributed generation in microgrids makes traditional fault detection schemes inappropriate due to their dependence on significant fault currents. In this paper, we devise an intelligent fault detection scheme for microgrid based on wavelet transform and deep neural networks. The proposed scheme aims to provide fast fault type, phase, and location information for microgrid protection and service recovery. In the scheme, branch current measurements sampled by protective relays are pre-processed by discrete wavelet transform to extract statistical features. Then all available data is input into deep neural networks to develop fault information. Compared with previous work, the proposed scheme can provide significantly better fault type classification accuracy. Moreover, the scheme can also detect the locations of faults, which are unavailable in previous work. To evaluate the performance of the proposed fault detection scheme, we conduct a comprehensive evaluation study on the CERTS microgrid and IEEE 34-bus system. The simulation results demonstrate the efficacy of the proposed scheme in terms of detection accuracy, computation time, and robustness against measurement uncertainty.

Intelligent Fault Detection Scheme for Microgrids With Wavelet-Based Deep Neural Networks

A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network

This paper presents a data-mining-based intelligent differential protection scheme for the microgrid. The proposed scheme preprocesses the faulted current and voltage signals using discrete Fourier transform and estimates the most affected sensitive features at both ends of the respective feeder. Furthermore, differential features are computed from the corresponding features at both ends of the feeder and are used to build the decision tree-based data-mining model for registering the final relaying decision. The proposed scheme is extensively validated for fault situations in the standard IEC microgrid model with wide variations in operating parameters for radial and mesh topology in grid-connected and islanded modes of operation. The extensive test results indicate that the proposed intelligent differential relaying scheme can be highly reliable in providing an effective protection measure for safe and secured microgrid operation.

Data-Mining Model Based Intelligent Differential Microgrid Protection Scheme

Data analytics are now playing a more important role in the modern industrial systems. Driven by the development of information and communication technology, an information layer is now added to the conventional electricity transmission and distribution network for data collection, storage and analysis with the help of wide installation of smart meters and sensors. This paper introduces the big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as huge amount of data collection are firstly discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of the typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this paper. By dealing with huge amount of data from electricity network, meteorological information system, geographical information system etc., many benefits can be brought to the existing power system and improve the customer service as well as the social welfare in the era of big data. However, to advance the applications of the big data analytics in real smart grids, many issues such as techniques, awareness, synergies, etc., have to be overcome.

/pdf/big-data-analytics-in-smart-grids-a-review-4g4lfx70ug.pdf

Big data analytics in smart grids: a review

Distribution Automation can be used for service restoration and feeder reconfiguration, after isolation of faulty part when an abnormal situation occur in distribution system rapidly so that reliability improves, unserved energy loss and distribution system loss(I2R loss) reduces by optimal feeder configuration. As the cost of Global System for Mobile Communication (GSM) services reducing day by day and have advantage of already existed network over other standards like Zigbee, Bluetooth and Wi-Fi, is most reliable and efficient standard for communication in automation, offers easy implementation with low cost. This paper presents an efficient de sign for distribution automation system and its implementation in remote/automatic monitoring and controlling of the relays (circuit breaker) by means of GSM Short Message Service (SMS) service, automatic decision making and continuous monitoring of distribution system components in real time. The design is implemented on PSoC (Programmable System on Chip) and the GSM modem so that it can be used for a wide range of applications.

Distribution system automation based on GSM using Programmable System on Chip (PSOC)

The dynamic behavior of micro-grid imposes serious challenges to the design of the protection system. The fault current magnitude and direction changes significantly with variations in the operating conditions which may leads to failure of protection system and non-selective operation. To alleviate the problems, this paper proposes an effective relay coordination using Genetic Algorithm (GA) considering different topology and operating modes of the micro-grid. The proposed coordination enables the overcurrent relays to update their current setting according to the operating conditions to achieve the minimum possible operating times while maintaining the coordination criteria between the primary and backup relays. Extensive test results with both synchronous and inverter based DGs and operating conditions indicate the ability of the proposed relay coordination in devising an effective and reliable protection measure for microgrid.

Overcurrent relay coordination for micro-grid with different operating conditions

Penetration of distributed generations (DGs) enable microgrid to operate in different mode such as grid-connected and islanded mode with radial and mesh topology. The fault current magnitude and di...

Impact of Microgrid Operation on the Performance of Overcurrent Relay Coordination and Assessment of Differential Relay Coordination

A multiple features based passive islanding detection technique using S-transform and decision tree is proposed in this paper. It consider synchronous as well as inverter based distributed generations interfaced to micro-grid. The technique involves extraction of different statistical features of frequency contour obtain by performing S-transform with the current signal retrieved at target distributed generation location and builds the decision tree for islanding and non-islanding classification. Extensive simulations are carried out for wide variations in system loading and power mis-match during islanding, and a decision tree is built for effective islanding detection for both synchronous and inverter based distributed generations in microgrid. Performance of the proposed anti-islanding technique is compared with existing rate of change of frequency and rate of change of voltage relay. It provides improved performance at lower end power mis-match.

Multiple features based anti-islanding protection relay for distributed generations

Unevenly distributed loads at different phases may lead to stability issues and incur high losses in a low inertial microgrid with a rise in Voltage Unbalance (VU). Thus, a suitable control mechanism is mandatory for stable microgrid operation and mitigating VU under peak and off-peak loading conditions. This paper presents a hierarchical control mechanism that includes a primary Droop-based Positive-Negative Sequence Compensation (PNSC) approach and a secondary controlling technique implemented using Demand Side Management (DSM). Besides mitigating VU, DSM also performs effective energy management by manipulating Thermostatically Controlled Loads (TCLs) and Electric Vehicle Charging stations (EVCs), with specific emphasis on the Thermal Comfort (TC) of customers. The primary controller’s stability is also examined to test and validate its potential to mitigate VU during off-peak loading. Furthermore, a comprehensive analysis of the proposed hierarchical controller is performed with several dynamics taken into account. Moreover, the control technique is designed to mitigate generation and demand mismatch while adhering to IEC-61000-3-13. The effectiveness of the proposed control framework is tested using a modified IEEE-13 bus system in a MATLAB/ Simulink and Digsilent PowerFactory environment. Further the Hardware in Loop (HIL) is done in OPAL-RT to validate the real time performance of the system.

Susmita Kar

Papers

Distribution system automation based on GSM using Programmable System on Chip (PSOC)

Overcurrent relay coordination for micro-grid with different operating conditions

Impact of Microgrid Operation on the Performance of Overcurrent Relay Coordination and Assessment of Differential Relay Coordination

Multiple features based anti-islanding protection relay for distributed generations

Hierarchical Control for Voltage Unbalance Mitigation Considering Load Management in Stand-Alone Microgrid