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With the spotlight on smart grid development around the world, it is critical to recognize the key factors contributing to changing power system characteristics. This is more apparent in distribution systems with the integration of renewable energy sources, energy storage, and microgrid development. Utilities are also focusing on the reliability and resiliency of the grid. These activities require distribution automation (DA) strategies that take advantage of available technologies while promoting newer solutions. It is necessary to create a roadmap for holistic DA strategies in a smarter grid. Sustainable and resilient grid development is a paradigm shift requiring a new line of thinking in the engineering, operation, and maintenance of the power system. International perspectives on DA are also addressed, with the understanding that one solution will not fit all. Integrating technical, business, and policy decisions into the challenges will generate the development of technologies, standards, and implementation of the overall solution. The challenges in the development of industry standards are also discussed. This paper explores the challenges and opportunities in the changing landscape of the distribution systems. Evolution of technologies and the business case for infrastructure investment in distribution systems are covered in another paper by the same authors.

According to the U.S. Department of Energy, about 40% of total energy is consumed on buildings in industrialized countries, among which 68% is electricity. Recently research shows that 20%∼30% of building energy consumption can be saved with optimized operation and management without changing building structure and hardware configuration of energy supply system significantly. Therefore, there is a huge potential for building energy savings through efficient operation.

Smart grid, as one of the most critical infrastructures, is vulnerable to a wide variety of cyber and/or physical attacks. Recently, a new category of threats to smart grid, named coordinated cyber-physical attacks (CCPAs), are emerging. A key feature of CCPAs is to leverage cyber attacks to mask physical attacks which can cause power outages and potentially trigger cascading failures. In this paper, we investigate CCPAs in smart grid and show that an adversary can carefully synthesize a false data injection attack vector based on phasor measurement unit (PMU) measurements to neutralize the impact of physical attack vector, such that CCPAs could circumvent bad data detection without being detected. Specifically, we present two potential CCPAs, namely replay and optimized CCPAs, respectively, and analyze the adversary’s required capability to construct them. Based on the analytical results, countermeasures are proposed to detect the two kinds of CCPAs, through known-secure PMU measurement verification (in the cyber space) and online tracking of the power system equivalent impedance (in the physical space), respectively. The implementation of CCPAs in smart grid and the effectiveness of countermeasures are demonstrated by using an illustrative 4-bus power system and the IEEE 9-bus, 14-bus, 30-bus, 118-bus, and 300-bus test power systems.

Renewable energy (RE) microgrids are considered one solution for solving the increasing electricity demand and environmental pollution problem. Selecting RE sources for a microgrid plays a crucial role in determining the performance of the microgrid. Illustrated with an empirical study on a city’s microgrid project, this article proposes a new evaluation approach with a bi-capacity based multi-criteria decision making method called Bi-ELECTRE to evaluate and select RE source alternatives based on interacting performance indicators with bipolar measurement. With the novelty of the Bi-ELECTRE method, this article addresses the questions of (a) how to measure interactions between bipolar-scaled indicators when evaluating the RE source alternatives of a microgrid, and (b) how to determine the optimal combination of RE sources for a microgrid. The results from the empirical study suggest that a microgrid with a single RE source has the worst performance, compared with multi-source alternatives. In the empirical study conducted, the microgrid using a RE source combination of 20% wind, 30% solar, and 50% biomass has the best overall performance. By considering interactions between bipolar-scaled indicators and various combinations of RE sources, the proposed approach contributes to MCDM research methodologically and to the RE source selection problem for a microgrid practically.

Smart grid, as the next generation of power grid characterized by “two-way” communications, has been paid great attention to realizing green, reliable, and efficient electricity delivery for our future lives. In order to support the two-way communications in smart grid, a large number of smart meters (SMs) should be deployed to customers to report their near real-time data to control center for monitoring purpose. However, this kind of real-time report could disclose users’ privacy, bringing down the users’ willingness to participate in smart grid. In order to address the challenge, in this paper, by considering the lifetime of SMs as exponential distribution, we propose a diverse grouping-based aggregation protocol with error detection (DG-APED), which employs differential privacy technique into grouping-based private stream aggregation for secure smart grid communications. DG-APED can not only achieve privacy-preserving aggregation, but also perform error detection efficiently when some SMs are malfunctioning. Detailed security analysis shows that DG-APED can guarantee the security and privacy requirements of smart grid communications. In addition, extensive performance evaluation also verifies the effectiveness and efficiency of the proposed DG-APED.

Due to emerging environmental problems from fossil fuel usage and increasing renewable energy resources in microgrids, the need of demand response (DR) is intensified to stabilize irregular balance and to mitigate carbon dioxide emissions simultaneously. However, in order to estimate practical and factual DR potential, an analysis of load characteristics including user behavior is required based on information data. Thus, in this study, a novel analytic approach is proposed to detect resident behavior for environment responsive DR potential estimation. A new framework to determine optimal DR potential is proposed with related data analysis models. In each analysis model, resident occupancy behavior and forecasted renewable energy generation are estimated. During the process of resident behavior detection, sub-metering data of appliances are analyzed and profiled for multiple purposes by a new method based on hidden Markov model and time varying Markov chain. The optimal DR potential is estimated considering guaranteed residents’ comfort constraints and the dynamic characteristics of appliances. The proposed framework is tested on the single household environment of residential region and the results present that the proposed model is environmentally and economically effective, while also suggesting meaningful implications through resident behavior data analysis.

Integrating information network into power system is the key for realizing the vision of smart grid, but also introduces many security problems. Wireless communication offers the benefits of low cost, rapid deployment, shared communication medium, and mobility; at the same time, it causes many security and privacy challenges. In this paper, the concept of dynamic secret is applied to design an encryption scheme for smart grid wireless communication. Between two parties of communication, the previous packets are coded as retransmission sequence, where retransmitted packet is marked as “1” and the other is marked as “0.” During the communication, the retransmission sequence is generated at both sides to update the dynamic encryption key. Any missing or misjudging in retransmission sequence would prevent the adversary from achieving the keys. In our experiments, a smart grid platform is built, employing the ZigBee protocol for wireless communication. And a dynamic secret-based encryption demo system is designed based on this platform. The experiment results show that the retransmission and packet loss in ZigBee communication are inevitable and unpredictable, and it is impossible for the adversary to track the updating of the dynamic encryption key.

The increasing penetration of electric vehicles (EVs) and emerging dynamic wireless charging techniques have strengthened the coupling between traffic networks and power distribution networks. This increased coupling necessitates greater coordination between the two networks. This paper proposes a multi-period optimal traffic and power flow model that considers time-varying electricity and traffic demands. The distribution of traffic flow is represented by a semi-dynamic traffic assignment (SDTA) model, which considers flow propagation between adjacent periods. Combined second-order cone, convex hull, and McCormick envelope relaxations are employed to convexify the power and traffic flow model. Optimization-based bound tightening (OBBT) method combined with a heuristic sequential bound tightening (SBT) method is employed to improve the tightness of the relaxation. The modeling of multi-period scheduling provided by the SDTA model is thoroughly compared with that provided by the conventional static traffic assignment model. In addition, the proposed traffic and power flow model is employed to conduct congestion analysis of the coupled networks. Numerical results on two test systems demonstrate both the spatial and temporal impacts of congestion on each of the coupled networks. Moreover, numerical results verify that the proposed OBBT-SBT-based convex relaxation is sufficiently tight.

Demand response (DR), distributed generation (DG), and distributed energy storage (DES) are important ingredients of the emerging smart grid paradigm. For ease of reference we refer to these resources collectively as distributed energy resources (DER). Although much of the DER emerging under smart grid are targeted at the distribution level, DER, and more specifically DR resources, are considered important elements for reliable and economic operation of the transmission system and the wholesale markets. In fact, viewed from transmission and wholesale operations, sometimes the term ?virtual power plant? is used to refer to these resources. In the context of energy and ancillary service markets facilitated by the independent system operators (ISOs)/regional transmission organizations (RTOs), the market products DER/DR can offer may include energy, ancillary services, and/or capacity, depending on the ISO/RTO market design and applicable operational standards. In this paper we first explore the main industry drivers of smart grid and the different facets of DER under the smart grid paradigm. We then concentrate on DR and summarize the existing and evolving programs at different ISOs/RTOs and the product markets they can participate in. We conclude by addressing some of the challenges and potential solutions for implementation of DR under smart grid and market paradigms.