Smart Grid for the Smart City

Modern cities are embracing cutting-edge technologies to improve the services they offer to the citizens from traffic control to the reduction of greenhouse gases and energy provisioning. In this chapter, we look at the energy sector advocating how Information and Communication Technologies (ICT) and signal processing techniques can be integrated into next generation power grids for an increased effectiveness in terms of: electrical stability, distribution, improved communication security, energy production, and utilization. In particular, we deliberate about the use of these techniques within new demand response paradigms, where communities of prosumers (e.g., households, generating part of their electricity consumption) contribute to the satisfaction of the energy demand through load balancing and peak shaving. Our discussion also covers the use of big data analytics for demand response and serious games as a tool to promote energy-efficient behaviors from end users

Joint Optimal Pricing and Electrical Efficiency Enforcement for Rational Agents in Micro Grids

In electrical distribution grids, the constantly increasing number of power generation devices based on renewables demands a transition from a centralized to a distributed generation paradigm. In fact, power injection from Distributed Energy Resources (DERs) can be selectively controlled to achieve other objectives beyond supporting loads, such as the minimization of the power losses along the distribution lines and the subsequent increase of the grid hosting capacity. However, these technical achievements are only possible if alongside electrical optimization schemes, a suitable market model is set up to promote cooperation from the end users. In contrast with the existing literature, where energy trading and electrical optimization of the grid are often treated separately or the trading strategy is tailored to a specific electrical optimization objective, in this work we consider their joint optimization. Specifically, we present a multi-objective optimization problem accounting for energy trading, where: 1) DERs try to maximize their profit, resulting from selling their surplus energy, 2) the loads try to minimize their expense, and 3) the main power supplier aims at maximizing the electrical grid efficiency through a suitable discount policy. This optimization problem is proved to be non convex, and an equivalent convex formulation is derived. Centralized solutions are discussed first, and are subsequently distributed. Numerical results to demonstrate the effectiveness of the so obtained optimal policies are then presented

Lightweight energy management of islanded operated microgrids for prosumer communities

The paper presents and evaluates a lightweight and effective approach for the management of prosumer communities through the synergistic control of the power electronic converters acting therein. These controllable elements are the utility interface (UI), installed at the point of common coupling with the electrical utility, and the energy gateways (EGs), interfacing distributed generation units and energy storage devices with the distribution grid. The UI acts as the control master for the microgrid, collecting information on generators and power demand and dispatching a control parameter that regulates both energy storage devices and generators. An islanded operation mode is considered, and the control strategy aims at leveling peaks in the energy drained from or injected into the UI. The proposed control strategy is tested on a residential microgrid model, 100 kVA rated, which has been developed and utilized to analyze selected performance metrics in the presence of realistic and time varying power demand and energy generation processes. This model allows a fine-grained analysis of (a) the energy storage state at each residential unit, (b) the amount of energy required at the UI, and (c) the locally generated energy injected into the micro grid by each EG. As a further result, our framework returns the amount of distributed storage required to achieve a target peak-shaving performance level, according to the number of residential users with generation capability and their storage capacity