A Stochastic Game Framework for Efficient Energy Management in Microgrid Networks

We consider the problem of energy management in microgrid networks. A microgrid is capable of generating a limited amount of energy from a renewable resource and is responsible for handling the demands of its dedicated customers. Owing to the variable nature of renewable generation and the demands of the customers, it becomes imperative that each microgrid optimally manages its energy. This involves intelligently scheduling the demands at the customer side, selling (when there is a surplus) and buying (when there is a deficit) the power from its neighboring microgrids depending on its current and future needs. Typically, the transaction of power among the microgrids happens at a pre-decided price by the central grid. In this work, we formulate the problems of demand and battery scheduling, energy trading and dynamic pricing (where we allow the microgrids to decide the price of the transaction depending on their current configuration of demand and renewable energy) in the framework of stochastic games. Subsequently, we propose a novel approach that makes use of independent learners Deep Q-learning algorithm to solve this problem. Through extensive empirical evaluation, we show that our proposed framework is more beneficial to the majority of the microgrids and we provide a detailed analysis of the results

Analysing Nordcloud's Email Campaigns: Strategies for Enhanced Effectiveness

In the constantly evolving digital landscape, efficient email marketing serves as a fundamental element for engaging customers and achieving brand visibility. This paper delves into a detailed examination of Nordcloud's email marketing tactics, focusing specifically on their welcome email, monthly newsletter, and core email drip campaigns (Migrate and Modernise, FinOps & FSI). Through a blend of data analysis from HubSpot spanning a 10-month duration and a thorough review of current literature, this research identifies crucial insights and top-notch methods to enhance email campaign effectiveness, through quantitative and secondary research methods. The results indicate that personalisation and segmentation notably boost engagement metrics, highlighting the significance of tailored content delivery. Nevertheless, areas for enhancement surface, particularly concerning content relevance and multimedia integration. Based on these findings, actionable recommendations are put forth to improve Nordcloud's email marketing endeavours. These recommendations also highlight the importance of prompt delivery of welcome emails, thorough A/B testing for sender names and subject lines, creation of localised content, and inclusion of clear calls-to-action. For newsletters, suggestions include integrating interactive elements, optimising for mobile devices, and utilising user-generated content to drive engagement. Similarly, for drip campaigns, segmenting content and maintaining a consistent tone are underscored as vital strategies. Notably, the inclusion of a senior position as a sender name in email campaigns demonstrated a noteworthy impact. Emails attributed to senior positions such as CEOs or Directors prove to have higher open rates and click-through rates compared to those sent from generic or junior-level positions. In essence, this study underscores the necessity of aligning content creation with overarching digital marketing strategies to attain campaign success. By equipping Nordcloud with practical guidelines derived from a thorough analysis and industry best practices, this research aims to empower the organisation to enhance its email marketing initiatives, thereby fostering heightened engagement and achieving superior results

Box Wing: Aerodynamic experimental study for applications in MAVs

Advancements in the field of aerial robotics and micro aerial vehicles (MAVs) have increased the demand for high payload capabilities. Closed wing designs like the annular wing, the joined wing, the box wing and spiroid tip devices improve the aerodynamic performance by suppressing the wingtip vortices along with an enhanced lift coefficient. A box wing may be defined as a wing that effectively has two main planes which merge at their ends so that there are no conventional wingtips. We propose the implementation of box wings as the main lifting surface for such systems. Box wings have a potential of generating lift with considerably less induced drag and delayed stall angles than monoplane wings. We study the aerodynamic aspects of a box wing model using wind tunnel tests and numerical simulations. We conducted Computational Fluid Dynamics (CFD) simulation subjecting the model to a steady flow and later analysed the vortex core using CFD tools. Wind tunnel measurements of the forces were obtained using sting balance. Furthermore, polyester thread tufts and smoke flow visualisation were performed to understand the qualitative behaviour of the scaled model in the open to atmosphere, suction type tunnel. Our results reveal an increase in the lift to drag (L/D) ratio of the wing by 25 % and a delay in the model’s stall angle by +6° compared to a monoplane; implying a lower stalling speed for mini unmanned aerial vehicles (UAVs) and MAVs. These advancements if applied could revolutionize the capabilities of intelligent flying systems by enabling them to carry better sensors, computational units and other payloads as per the mission