Abstract
This paper presents a data-driven spatial net-load forecasting model that is applied to the distribution network expansion problem. The model uses population census data with Information Theory-based Feature Selection to predict spatial adoption patterns of residential electric vehicle chargers and photovoltaic modules. Results are high-resolution maps (0.02 km(2)) that allow distribution network planners to forecast asymmetric changes in load patterns and assess resulting impacts on installed HV/MV substation transformers in distribution systems. A risk analysis routine identifies the investment that minimizes the maximum regret function for a 15-year planning horizon. One of the outcomes from this study shows that traditional approaches to allocate distributed energy resources in distribution networks underestimate the impact of adopting EV and PV on the grid. The comparison of different allocation methods with the presented diffusion model suggests that using conventional approaches might result in strong underinvestment in capacity expansion during early uptake and overinvestment in later diffusion stages.

Abstract
The main objective of this paper is to present a new and cost-effective Information and Communication Technology (ICT) tool that can lead to efficient energy management in buildings and optimal operation of electricity networks with increased share of Renewable Energy Sources (RES) and Electric Vehicles (EVs). The new ICT infrastructure is based on the Digital Audio Broadcasting (DAB) standard and its interoperability with smart metering technology, Intelligent Transportation Systems (ITS) and Building Automation Systems (BAS). The main idea involves the attachment of a DAB receiver to electric devices (from small household appliances up to EVs and solar systems and other RES). In this paper, the DAB protocol is described, enabling high cyber-physical security. Moreover, the results of addressing a thermostatically-controlled load using DAB-signaling in Switzerland are also presented. The next steps envisioned are i) the validation of the final protocol version and of the DAB receivers for various electric appliances and DR schemes and, ii) demonstration of the new technology in real-life cases through the National DAB broadcaster in Greece. (C) 2019 The Authors. Published by Elsevier Ltd.

Abstract
Demand management is becoming an indispensable part of grid operation with its potential to aid supply/demand balancing, reduce peaks, mitigate congestions and improve voltage profiles in the grid. Effective deployments require a huge number of reliable participators who are aware of the flexibilities of their devices and who continuously seek to achieve savings and earnings. In such applications, smart meters can ease consumption behavior visibility, while building automation systems can enable the remote and automated control of flexible loads. Moreover, gamification techniques can be used to motivate and direct customers, evaluate their performance, and improve their awareness and knowledge in the long term. This study focuses on the design and field demonstration of a flexible device-oriented, smart meter and building automation system (BAS) compatible with a gamified load management (LM) platform for residential customers. The system is designed, based on exploratory surveys and systematic gamification approaches, to motivate the customers to reduce their peak period consumption and overall energy consumption through competing or collaborating with others, and improving upon their past performance. This paper presents the design, development and implementation stages, together with the result analysis of an eight month field demonstration in four houses with different user types in Istanbul, Turkey.

Abstract
Distributed energy resources (DERs) can provide a number of functions to be used in grid services with proper establishment of control and communication systems. However, there are neither general standards for vendor independent integration of these assets in management activities, nor common consideration of specific flexibilities that different DERs have. This paper investigates characterization and comparison of individual power and energy management flexibilities of different types of distributed energy resources. Emerging DER capability identification approaches are used to highlight contrasting differences between several energy storage and distributed generation options. Experiments were conducted in a low voltage test facility to compare flexibility limits using the same control and communication infrastructure. © 2018 IEEE.

Abstract
Growing number of inverter-based distributed energy resources (DERs) and sensitive loads increase the need for coordinated power management activities in islanded operation of microgrids. Especially low voltage networks have low inertia and high RA ratio, causing instability due to fluctuations in distributed generation (DG) and local voltage problems in islanded operation. This study investigates management of DERs that operate in current mode for providing voltage regulation support to master unit(s) in islanded operation of microgrids. A special focus was set on local voltage issues in low voltage (LV) network feeders. Field experiments in a large test facility highlighted management accuracy and corrective impact potential of DERs connected to different parts of a feeder.

Abstract
The use of fossil fuel vehicles is one of the factors responsible for the degradation of air quality in urban areas. In order to reduce levels of air pollution in metropolitan areas, several countries have encouraged the use of electric vehicles in the cities. However, due to the high investment costs in this class of vehicles, it is expected that the spatial distribution of electric vehicles' adopters will be heterogeneous. The additional charging power required by electric vehicles' batteries can change operation and expansion planning of power distribution utilities. In addition, urban planning agencies should analyze the most suitable locations for the construction of electric vehicle recharging stations. Thus, in order to provide information for the planning of electric mobility services in the city, this paper presents a spatiotemporal model for estimating the rate of electric vehicles' adopters per subareas. Results are spatial databases that can be viewed in geographic information systems to observe regions with greater expectancy of residential electric vehicle adopters. These outcomes can help utilities to develop new services that ground on the rising availability of electric mobility in urban zones.