The transformation of passive distribution systems to more active ones thanks to the increased penetration of distributed energy resources, such as dispersed generators, flexible demand, distributed storage, and electric vehicles, creates the necessity of an enhanced test system for distribution systems planning and operation studies. The value of the proposed test system, is that it provides an appropriate and comprehensive benchmark for future researches concerning distribution systems. The proposed test system is developed by modifying and updating the well-known 33 bus distribution system from Baran & Wu. It comprises both forms of balanced and unbalanced three-phase power systems, including new details on the integration of distributed and renewable generation units, reactive power compensation assets, reconfiguration infrastructures and appropriate datasets of load and renewable generation profiles for different case studies.

Advanced information and communication infrastructures are essential to successfully operate smart grids (SGs) and provide efficient, reliable, and sustainable electricity to the customers. After providing the background of the communication paradigm in SGs, a comprehensive survey of the major issues related to the architectures, the key technologies, and the requirements of the SG communication infrastructure are analyzed in this article. The role of cloud computing and Internet of Things in SGs is also discussed. Finally, the standardization, potential applications, and future fruitful research issues of the communication infrastructures of the SGs are classified and discussed.

The smart power systems are based upon information and communication technologies, which lead to a deluge of data originating from various sources. To address these challenges concerning accumulated voluminous data, big data analysis in smart power systems is inevitable. This article comprehensively surveys the literature related to the big data issues in smart power systems. The background and motivation of the big data paradigm in smart power systems are first provided, and then the major issues related to the architectures, the key technologies, and standardizations of big data analytics in smart power systems are analyzed. Also, the potential applications of big data in smart power systems based upon the state-of-the-art research are highlighted. Finally, the future issues and challenges of the big data issues in modern power systems are discussed.

In recent two decades, the power systems have confronted with considerable changes such as the power system restructuring, growth of distributed energy sources and renewable energy sources (RESs), and emergence of smart grid concept. One of the common challenges caused by these changes is flexibility necessity of energy resources. One of the best solutions to mitigate this challenge is energy storage systems (ESSs) utilisation. The main question is how to determine size, site, and type of ESSs to maximise their benefits. This study reviews the answers to this question according to the research studies. This study first classifies the studies related to ESS expansion planning into two main categories from the viewpoint of the power system operators and the investors. Next, the first main category is divided into three subcategories: ESS expansion planning in microgrids, distribution networks, and transmission networks. The second main category is classified into two subcategories: ESS expansion planning aim to smooth RESs output power and to maximise profit. In each subcategory the modelling approaches, solving methods, and the results are evaluated. Finally, based on the existing challenges, the future research directions of ESS expansion planning are outlined.