To combat energy shortage, the multi-energy system has gained increasing interest in contemporary society. In order to fully utilize adjustable multi-energy resources on the demand side and reduce interactive compensation, this paper presents an integrated demand response (IDR) model in consideration of conventional load-shedding and novel resource-shifting, due to the fact that participants in IDR can use more abundant resources to reduce the consumption of energy. In the proposed IDR, cooling, heating, electricity, gas and so forth are considered, which takes the connection between compensation and load reductions into consideration. Furthermore, a bilevel optimal dispatch strategy is proposed to decrease the difficulty in coordinated control and interaction between lower-level factories and upper-level multi-energy operators in industrial parks. In this strategy, resources in both multi-energy operator and user sides are optimally controlled and scheduled to maximize the benefits under peak shifting constraint. In the normal operation mode, this strategy can maximize the benefits to users and multi-energy operators. Particularly in heavy load conditions, compared to the conventional electricity demand response, there are more types of adjustable resources, more flexibility, and lower interactive compensations in IDR. The results indicate that optimal operation for factories and multi-energy operators can be achieved under peak shifting constraint and the overall peak power value in industrial park is reduced.

To solve the configuration issue when using International Electrotechnical Commission (IEC) 61850 for distributed intelligence in Distribution Automation Systems (DAS), this paper proposes the configuration solution in terms of semantic models and processing methods. Firstly, the special requirements of the DAS configuration are analyzed, consisting of the system boundary of a configuration project, the topology configuration for distributed applications, and the automatic identification of the Intelligent Electronic Devices (IED). The new models of Process, Line, and other elements are then presented based on the System Configuration Language (SCL) to describe the distribution network topology. The planned contents are allocated into a new format of the Configured IED Description (CID) file to realize the distributed applications. A register service is designed, which fulfills the automatic identification of IEDs when they are remotely placed into a DAS. The service checks the configuration status in real-time and automates the whole configuration engineering process. The case study shows that the proposed solution allows an IED to detect the real-time topology and re-establish the data flow configuration with peer IEDs independently from the master station; thus the distributed applications can be performed more autonomously and efficiently.

With the increasing penetration rate of renewable energy generation, the uncertainty of renewable energy output in microgrid cluster (MGC) leads to significant fluctuations in transaction volume, which may lead to the risk of transaction default. This paper proposes a day-ahead two layer trading model for microgrid cluster based on price trading mechanism and Conditional value-at-risk (CVaR) theory. Firstly, the upper-layer establishes an objective to minimize the overall power fluctuation of the microgrid cluster using Demand response (DR) with a penalty mechanism. The microgrid cluster adopts an internal pricing mechanism and adjusts transaction prices based on internal supply-demand conditions to guide microgrids’ participation in intracluster trading, thereby encouraging the microgrid to use the flexible resources to reduce power fluctuation. Secondly, the lower-layer optimization establishes an optimization model with the objective of minimizing the comprehensive operating cost of the microgrid cluster. The model employs backward scenario reduction techniques to obtain multiple sets of typical scenarios for renewable energy generation, and the CVaR theory is introduced to quantify the potential risk of transaction default. Finally, the effectiveness of the proposed models is verified through case studies considering various application scenarios.

Distribution automation (DA) and Internet of Things (IoT) all need the topology information of power distribution network to support some applications, such as fault diagnosis, network reconfiguration and optimization. IEC 61850 is a general communication model and standard for information exchange between intelligent electronic devices (IEDs). However, it has no mechanism for feeder topology information exchange. This paper solves this problem by developing the corresponding information model. Firstly, a feeder model is established as a container of the equipment along a distribution line. Secondly, logical models, such as terminal and connection nodes, are added to describe the physical connection relationship between the electrical equipment. Taking a circuit breaker as an example, this paper introduces how to add the terminal attribute to an existing logical node (XCBR). The physical connection between the circuit breaker and other electrical equipment is described by adding the logic node LCNN. Then, a new logical node LTPN is added to describe the logical connection between the devices. A new logical node, FTPA, is added to describe the status of the topology analysis and the topology results. Based on these new logical nodes, this paper proposes the mechanism of topology information exchange between IEDs. Three IEDs and the IEEE 13-node model are used to build an experimental environment. The result verifies the effectiveness of this method. More distributed applications can be used to test the validity and interoperability of the proposed model.

The detection of series arc faults using fault current is difficult to overcome the influence of load types, making it difficult to establish a unified fault detection criterion. In contrast, since the arc voltage waveform of fault point is less affected by the load types and is basically a square wave shape, which provide conditions for constructing a unified fault criterion. In terms of the fault information, the fault distortion point of voltage on load-side caused by the arc voltage transition edge provides the position information of the arc voltage transition edge, and its polarity, amplitude and rate of change make it possible to distinguish from the transition edge caused by normal harmonic voltage drop, which provide the theoretical basis for fault detection using the voltage on load-side. Based on the basic analysis of arc voltage waveform features, this paper proposes an arc fault detection method based on load-side voltage sensitive feature tracking for the purpose of identifying the existence of arc voltage transition edges. The method proposed in this paper highlights the transition edge by eliminating the fundamental wave component of the voltage on load-side, the phase areas where the fault distortion points may exist are used as the sensitive area for fault detection, and the identification and tracking of the transition edge is achieved based on the same direction of voltage change, finally, the presence of arc fault voltage is characterized through the polarity, amplitude and rate of transition edge by fusion. The detection method proposed in this paper has a clear physical meaning and has the advantage of being less affected by the load types. Compared with other similar methods, the method proposed in this paper has higher detection sensitivity and stronger ability to distinguish from voltage drop distortion. The experimental results show that the average detection accuracy of the proposed method for faults detection under various loads exceeds 96%, which verifies the effectiveness of the method.