Efficient State Estimation in Power Networks for Reactive Power Losses Compensation

We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a smart microgrid with raw measurements. We provide two distributed estimation algorithms, one ADMM-based and one JACOBI-like, in order to estimate using only local exchange of information. We prove the convergence of the ADMM algorithm to the maximum likelihood solution. Numerical simulations are included to validate the proposed algorithms, for different magnitude of error

A distributed control strategy for reactive power compensation in smart microgrids

We consider the problem of optimal reactive power compensation for the minimization of power distribution losses in a smart microgrid. We first propose an approximate model for the power distribution network, which allows us to cast the problem into the class of convex quadratic, linearly constrained, optimization problems. We then consider the specific problem of commanding the microgenerators connected to the microgrid, in order to achieve the optimal injection of reactive power. For this task, we design a randomized, gossip-like optimization algorithm. We show how a distributed approach is possible, where microgenerators need to have only a partial knowledge of the problem parameters and of the state, and can perform only local measurements. For the proposed algorithm, we provide conditions for convergence together with an analytic characterization of the convergence speed. The analysis shows that, in radial networks, the best performance can be achieved when we command cooperation among units that are neighbors in the electric topology. Numerical simulations are included to validate the proposed model and to confirm the analytic results about the performance of the proposed algorithm

Modelling and analysis of networked control strategies in smart power distribution grids: development of co-simulation tools

This thesis is focused on Smart Grid applications in medium voltage distribution networks. For the development of new applications it appears useful the availability of simulation tools able to model dynamic behavior of both the power system and the communication network. Such a co-simulation environment would allow the assessment of the feasibility of using a given network technology to support communication-based Smart Grid control schemes on an existing segment of the electrical grid and to determine the range of control schemes that different communications technologies can support. For this reason, is presented a co-simulation platform that has been built by linking the Electromagnetic Transients Program Simulator (EMTP v3.0) with a Telecommunication Network Simulator (OPNET-Riverbed v18.0). The simulator is used to design and analyze a coordinate use of Distributed Energy Resources (DERs) for the voltage/var control (VVC) in distribution network. This thesis is focused control structure based on the use of phase measurement units (PMUs). In order to limit the required reinforcements of the communication infrastructures currently adopted by Distribution Network Operators (DNOs), the study is focused on leader-less MAS schemes that do not assign special coordinating rules to specific agents. Leader-less MAS are expected to produce more uniform communication traffic than centralized approaches that include a moderator agent. Moreover, leader-less MAS are expected to be less affected by limitations and constraint of some communication links. The developed co-simulator has allowed the definition of specific countermeasures against the limitations of the communication network, with particular reference to the latency and loss and information, for both the case of wired and wireless communication networks. Moreover, the co-simulation platform has bee also coupled with a mobility simulator in order to study specific countermeasures against the negative effects on the medium voltage/current distribution network caused by the concurrent connection of electric vehicles

Combined Networking and Control Strategies for Smart Micro Grids: Analysis, Co-simulation and Performance Assessment.

The constantly increasing number of power generation devices based on renewables calls for a transition from the centralized control of electrical distribution grids to a distributed control scenario. In this context, distributed generators are exploited to achieve other objectives beyond supporting loads, such as the minimization of the power losses along the distribution lines, the sustainability of the electrical network when operated in islanded-mode (i.e., when the the energy flow from the main energy supplier is not available) and the power peaks shaving. In order to fulfill the aforementioned goals, optimized techniques aimed at managing the electrical behavior of the distributed generators (i.e., the amount of active and reactive power injected into the grid by the distributed generators at any given time), are needed. These techniques, in order to dispatch information regarding the actual state of the network agents, rely on smart metering devices (measuring instantaneous electrical quantities as, for example, active and reactive power, loads impedance and loads voltage) and on a communication infrastructure (i.e., Powerline Communication - PLC) interconnecting the smart-grid agents and allowing for the exchange of the measured quantities. Moreover, suitable communication protocols, supporting the transmission channel access and data routing, are needed. In this doctoral thesis, firstly, a full-fledged system that extends existing state-of-the-art algorithms for the distributed minimization of power losses in smart micro grids is presented. There, practical aspects such as the design of a communication and coordination protocol that is resilient to link failures and manages channel access, message delivery and distributed generator coordination is taken into account. Design rules for the networking strategies that best fit the selected optimization approaches are provided. Finally, in the presence of lossy communication links, the impact of communication and electrical grid features is assessed. Specifically, communication failures, scheduling order for the distributed control, line impedance estimation error, network size and number of distributed generators are considered as major issues. Next, it will be shown that the convergence rate of the optimization algorithms, implemented in the aforementioned system, can be improved by suitably scheduling the order in which the smart-grid agents are activated. For stability purposes, a token ring approach is often implemented for the control, where at any given time a single node with communication and control capabilities (referred to as {\em smart node}) has the token and is the only node in charge of implementing the control action entailed by the algorithms (i.e., power injection). It will be shown that the token ring approach does not always ensure the fastest convergence rate. In order to improve the convergence rate of the selected optimization techniques, optimality criteria are defined and a lightweight, distributed and heuristic (suboptimal) scheduling algorithm is designed. Another important aspect considered in this thesis, is the one concerning the power demand peak shaving. Algorithms that exploit the distributed energy sources and rely on the smart-grid communication infrastructure in order to level out the peaks in the electrical power demand, can greatly reduce the workload of the main energy supplier, thus preventing unexpected hardware failures and blackouts. The importance of leveling out the power demand peaks is even greater when dealing with smart-grids operating in islanded mode, since avoiding power demand peaks can substantially improve the self-sustainability of the electrical grid. To this end, a lightweight and effective approach for the management of prosumer communities through the synergistic control of the power electronic converters acting therein is designed. An islanded operating mode is considered, and the control strategy aims at leveling peaks in the use of energy drained from or injected into the connection point with the main power supplier. All the aforementioned techniques rely on the use of distributed generators (whose energy comes from renewable sources) to contribute to the overall grid electrical efficiency. In a real-world setting, such control actions will however depend on market models and on the revenue (monetary income) that the final users will accrue through energy trading with other users and with the smart grid operator. For this reason, an optimized market model accounting for electrical efficiency constraints, along with the demand-offer rule, is designed. Novel market rules designed to provide economical benefits to all the smart grid players (i.e., the users and the grid operator), while also driving the power grid toward a satisfactory solution in terms of electrical performance are designed. To the best of the author's knowledge, a general framework for the study of the interaction between power grid optimization algorithms (electrical performance) and energy pricing and trading strategies (revenue) is not yet available in the related scientific literature

Innovation in Energy Systems

It has been a little over a century since the inception of interconnected networks and little has changed in the way that they are operated. Demand-supply balance methods, protection schemes, business models for electric power companies, and future development considerations have remained the same until very recently. Distributed generators, storage devices, and electric vehicles have become widespread and disrupted century-old bulk generation - bulk transmission operation. Distribution networks are no longer passive networks and now contribute to power generation. Old billing and energy trading schemes cannot accommodate this change and need revision. Furthermore, bidirectional power flow is an unprecedented phenomenon in distribution networks and traditional protection schemes require a thorough fix for proper operation. This book aims to cover new technologies, methods, and approaches developed to meet the needs of this changing field

Real-Time Control Framework for Active Distribution Networks Theoretical Definition and Experimental Validation

The great challenge of massively integrating the volatile distributed power-generation into the power system is strongly related to the evolution of their operation and control. The literature of the last decade has suggested two models for such an evolution: (i) the supergrid model, based on enhanced continental/intercontinental network interconnections (mainly DC) for bulk transmission, (ii) the microgrid mode, where small medium/low voltage networks interfacing heterogeneous resources, such as local generation, energy storage and active customers, are intelligently managed so that they are operated as independent cells capable of providing different services from each other and operate in islanded mode. Irrespective of the model that will eventually emerge, the control of heterogeneous distributed resources represents a fundamental challenge for both supergrid and microgrid models. This requires the definition of scalable and composable control methods that guarantee the optimal and feasible operation of distribution grids in order to satisfy local objectives (e.g., distribution grid power balance), as well as the provision of ancillary services to the external bulk transmission (e.g., primary and secondary frequency supports). Several control methodologies have been proposed to achieve these goals, and the majority of them have been inspired by the classic time-layered approach traditionally adopted in power systems that are associated with different time-scales and extension of the controlling area, i.e. primary, secondary and tertiary controls, ranging from sub-seconds to hours, respectively. In the context of microgrids, these three levels of control can be associated with a decision process that can be centralized (i.e., a dedicated central controller decides on the operation of the system resources) and/or decentralized (each element decides based on its own rules). In the current literature, the former is used for long-term, whereas the latter for short-term decisions. In particular, primary controls are typically deployed through fully decentralized schemes mainly relying on the use of droop control. With this in mind, in this thesis we propose, and experimentally validate, a novel control framework called COMMELEC â A Composable Framework for Real-Time Control of Active Distribution Networks, Using Explicit Power Set-Points. It controls a power grid in real-time based on a multi-agent structure, using a simple and low-bandwidth communication protocol. Such a framework enables a controller to easily steer an entire network as an equivalent energy resource, thus making an entire system able to provide grid support by exploiting the flexibility of its components in real-time. The main features of the framework are (i) that it is able to indirectly control the reserve of the storage systems, thus maximizing the autonomy of the islanding operation, (ii) that it keeps the system in feasible operation conditions and better explores, compared to traditional techniques, the various degrees of freedom that characterize the system, and (iii) that it maintains the system power-equilibrium without using the frequency as a global variable, even being able to do so in inertia-less systems. Our framework has been extensively validated, first by simulations but, more importantly, in a real-scale microgrid laboratory specially designed and setup for this goal. This is the first real-scale experiment that proves the applicability of a droop-less explicit power-flow control mechanism in microgrids

Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods

Innovation in Energy Systems

It has been a little over a century since the inception of interconnected networks and little has changed in the way that they are operated. Demand-supply balance methods, protection schemes, business models for electric power companies, and future development considerations have remained the same until very recently. Distributed generators, storage devices, and electric vehicles have become widespread and disrupted century-old bulk generation - bulk transmission operation. Distribution networks are no longer passive networks and now contribute to power generation. Old billing and energy trading schemes cannot accommodate this change and need revision. Furthermore, bidirectional power flow is an unprecedented phenomenon in distribution networks and traditional protection schemes require a thorough fix for proper operation. This book aims to cover new technologies, methods, and approaches developed to meet the needs of this changing field