Weather based power curtailments have a huge share in total customers outage. Hence, reliable-affordable exploitation of networks during the adverse weather condition is one grid operator’s main issue. This article addresses an approach for optimal operational by considering dynamic line outages rate during extreme weather condition. In this paper, resiliency modification is accomplished by probing influences of weather condition on line outages using embedded sources, power storages and feeder topology reconfiguration. This work addresses objectives associated with resiliency issue in order to minimize total operation cost from distribution Company’s viewpoint, reduce amount of outages and maximize private sector’s benefits by probing weather changes during operational time interval. In this regard, a multi-objective optimization problem including both economic and resiliency targets is proposed to model the behavior of distribution company and private sector. Also, a benefit sharing mechanism is applied to increase synergistic integration between these players. A hybrid genetic- ɛ constraint strategy employing fuzzy decision maker is applied to achieve optimum Pareto-front solution based on fair profit sharing. Results proves that the proposed method increase profits for all players due to reduction in energy not supplied penalty cost as well as it enhance resiliency during adverse weather conditions.

Access to cash for many in society is remainingessential during the current COVID-19 lock-down around theglobe. A smart city requires the banking industry to exploit IoTand Artificial Intelligence (AI) in order to track its ATM networkand predict outages due to cash shortages. In this paper, we studythe real-time cash replenishment planning problem under outflowuncertainty where the fee of the security companies grows if thereplenishment ends up falling on a weekends/holidays. Our modelis based by the Double Deep Q-Network (DQN) algorithm whichcombines popular Q-learning with a deep neural network. Theproposed method is used to minimize the ATM replenishmentcost where the cash demand changes dynamically at each day.The performance analysis of the proposed method for differentamounts of replenishment cash shows that the the proposedmethod can effectively work under real word conditions andreduce the ATM operational cost compared with the other stateof-the-art cash demand prediction schemes.Index Terms—cash replenishment planning, deep learning,ATM, reinforcement learning, double Q-network.

Information and communication technology (ICT) has transformed how we live our lives and the way we interact in different contexts. Benefits of ICT and its upcoming efficiencies (i.e. energy efficiency) are becoming the heart of many public services’ reforms which have influenced the time, distance and space concepts. At present, not only there is a lack of clarity about what high-quality ICTbased urban services look like, and an urgent need to articulate a clear vision of ‘better’ services, but also the integration of this new transformations in spatial urban planning (e.g. service delivery planning) has not been comprehensively considered. Therefore, the main debate in this paper comprises of simplifying the e-services delivery process and architecture and its integration to the spatial planning process.Illustration of the resulted benefits of such integration is another outcome of the paper. This paper aims at developing a conceptual framework of e-services and its impact on urban public service delivery in line with developing an integrated process of e-services and spatial urban planning. The main outcomes of the research are comprised of an integrated conceptual service delivery process as well as strategies to achieve and optimize such integration.

Despite there are too many different viewpoints and definitions of the “ smart City” notion, the management part of a particular city needs to formulate a special definition of this concept for the city, based on its specific characteristics and priorities. The main question of this research is "What are the general characteristics of the smart city concept, and how we can derive customized characteristics for a particular city using these general characteristics"? This paper provides an approach to determine a set of validated, customized and prioritized characteristics for the target city. These characteristics can be used for formulating a desired definition for the city. In addition, they can serve as an input for strategic planning of the city and a criterion for prioritizing the urban projects for the target city. The first phase of our approach is based on a systematic review on the literature in order to take a valid range of different characteristics of the smart city notion. The second phase relies on the characteristics resulted in the first phase and determines a set of particular characteristics for the target city, based on its upstream documents and stakeholders’ opinions. In order to illustrate the second phase as well as showing the usability of our approach, we applied this approach to Tehran, the capital of I. R. Iran. Our study resulted in 35 common characteristics which are candidate for all cities. Then, 10 main characteristics were particularly extracted for the future smart Tehran. These characteristics were used to derive the mission, vision, and values of smart Tehran, as well as prioritizing the six main components of smart cities for this city in the following order: smart economy; smart mobility; smart living; smart governance; smart people; smart environment.