Demand response (DR) smart grid technology provides an opportunity for electricity consumers to actively participate in the management of power systems. Industry is one of the major consumers of electric power. In this study, we propose a DR energy management scheme for industrial facilities based on the state task network (STN) and mixed integer linear programming (MILP). The scheme divides the processing tasks in industrial facilities into nonschedulable tasks (NSTs) and schedulable tasks (STs), and takes advantage of distributed energy resources (DERs) to implement DR. Based on day-ahead hourly electricity prices, the scheme determines the scheduling of STs and DERs in order to shift the demand from peak periods (with high electricity prices) to off-peak periods (with low electricity prices), which not only improves the reliability of the electric power system, but also reduces energy costs for industrial facilities.

Wide area control (WAC) is highly desirable for maintaining the stability of large-scale smart grid. It crucially requires the support of real-time data communications with low latency. This requirement leads to the consideration of the multicast technique for routing of data packets of various measurements, control signals and commands. While the feasibility of multicast in WAC communications has been investigated, there is a lack of a general framework to formulate and solve the multicast routing problem particularly for WAC. To tackle this problem, this paper presents a systematic approach to constrained optimization of multicast routing in WAC over wide area networks (WANs) with a publish-subscribe architecture. To fulfil the requirements of real-time WAC communications, the optimization is formulated to minimize the end-to-end delay over WANs subject to bandwidth constraints. Then, the constrained optimization is solved theoretically by using Lagrangian Relaxation. The theoretic results are implemented in an iterative bandwidth-constrained minimum Steiner tree (BCMST) algorithm. Simulations are conducted to demonstrate the approach presented in this paper.

Neighbourhood Area Networks (NANs) are critical infrastructure in smart grid to support communications. With the development of wireless communication technologies, there is a great potential for large-scale wireless-mesh NANs to be deployed to smart grid systems. While there exist theoretical models of complex networks, they are not directly applicable in the generation of network topology for wireless-mesh NANs due to their lack of some specifications unique in smart grid, leading to difficulties in theoretical studies of smart grid NANs. Among various topological structures, scale-free networks are considered to be a potential candidate. Therefore, this paper presents a systematic approach to generate scale-free topology of wireless-mesh NANs in smart grid. A theoretical analysis confirms the scale-free feature of the network topology generated from the approach. To reveal the characteristics of our approach in comparison with widely used models of general complex networks, simulations are conducted on various network parameters including network diameter, average path length, clustering coefficient and fractal dimension. The simulation results show that our approach for generating wireless-mesh NAN topology is fundamentally different from these compared models, and thus is a new type of complex-network model. Specifically, our model is suitable for wireless-mesh NANs in smart grid.

Multicast routing is essential in many smart grid applications, e.g., wide area control, wide area protection, and wide area monitoring, for low-latency communications. Coexistence of multiple smart grid applications require the communication network to accommodate many multicast communications simultaneously with low latency. This requirement leads to congestion on some shared links in multiple multicast trees and consequently deteriorated multicast delay performance. While minimizing multicast routing delay has been investigated for a single multicast group, there is a lack of a general framework to deal with multicast routing delay in multiple multicast trees with shared links for smart grid. To address this issue, a systematic approach, namely Betweenness Centrality to Bandwidth ratio Tree (BCBT) approach, is presented in this paper. It formulates the multicast delay problem as a constrained BCBT optimization problem. It uses the Shortest Path Tree (SPT) multicast routing under light traffic, but switches to BCBT multicast routing when the multicast links get congested so that the SPT congestion is alleviated. A greedy algorithm with heuristics is developed to solve the BCBT optimization problem. Simulations are conducted to demonstrate the BCBT approach.

Advances in information and communication technologies have significantly influenced the operation of low-voltage distribution grids. As essential elements of distribution grids, user-side smart meters find many smart grid applications, for example to measure electrical energy use and facilitate communications. However, the service models of distribution grids remain under development in association with upgrading of user-side smart meters. These meters are resource constrained, and challenging to upgrade on a large scale. To address this issue, this article describes a container-driven service architecture, in which containers are used to create a virtual dedicated agent (digital twin) for each user-side smart meter. The agent can be deployed either in the cloud or on an edge system, and can be upgraded to support emerging smart grid applications, thus minimizing the future upgrading requirements of user-side smart meters. We built experimental test beds to verify the proposed architecture and evaluated its performance in real-world experiments.