159 research outputs found

    Transmission and Distribution Co-Simulation and Applications

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    As the penetration of flexible loads and distributed energy resources (DERs) increases in distribution networks, demand dispatch schemes need to consider the effects of large-scale load control on distribution grid reliability. Thus, we need demand dispatch schemes that actively ensure that distribution grid operational constraints are network-admissible and still deliver valuable market services. In this context, this work develops and evaluates the performance of a new network-admissible version of the device-driven demand dispatch scheme called Packetized Energy Management (PEM). Specifically, this work develops and investigates the live grid constraint-based coordinator and metrics for performance evaluation. The effects of grid measurements for a practical-sized, 2,522-bus, unbalanced distribution test feeder with a 3000 flexible kW-scale loads operating under the network-admissible PEM scheme is discussed. The results demonstrate the value of live grid measurements in managing distribution grid operational constraints while PEM can effectively deliver frequency regulation services. Increased penetration of flexible loads and DERs on distribution system (DS) will lead to increased interaction of transmission and distribution (T&D) system operators to ensure reliable operation of the interconnected power grids, as well as the control actions at LV/MV grid in aggregation will have significant impact on the transmission systems (TS). Thus, a need arises to study the coupling of the transmission and distribution (T&D) systems. Therefore, this work develops a co-simulation platform based on decoupled approach to study integrated T&D systems collectively. Additionally, the results of a decoupled method applied for solving T&D power flow co-simulation is benchmarked against the collaborator developed unified solution which proves the accuracy of the decoupled approach. The existing approaches in the literature to study steady-state interaction of TS-DS have several shortcomings including that the existing methods exhibit scalability, solve-time and computational memory usage concerns. In this regard, this work develops comprehensive mathematical models of T&D systems for integrated power flow analysis and brings advancements from the algorithmic perspective to efficiently solve large-scale T&D circuits. Further, the models are implemented in low-cost CPU-GPU hybrid computing platform to further speed up the computational performance. The efficacy of the proposed models, solution algorithms, and their hardware implementation are demonstrated with more than 13,000 nodes using an integrated system that consists of 2383-bus Polish TS and multiple instances of medium voltage part of the IEEE 8,500-node DS. Case studies demonstrate that the proposed approach is scalable and can provide more than tenfold speed up on the solve time of very large-scale integrated T&D systems. Overall, this work develops practically applicable and efficient demand dispatch coordinator able to integrate DERs into DS while ensuring the grid operational constraints are not violated. Additionally, the dynamics introduced in the DS with such integration that travels to TS is also studied collectively using integrated T&D co-simulation and in the final step, a mathematically comprehensive model tackles the scalability, solve-time and computational memory usage concerns for large scale integrated T&D co-simulation and applications

    Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

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    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

    Enhancing grid reliability with coordination and control of distributed energy resources

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    The growing utilization of renewable energy resources (RES) within power systems has brought about new challenges due to the inherent uncertainty associated with RES, which makes it challenging to accurately forecast available generation. Further- more, the replacement of synchronous machines with inverter-based RES results in a reduction of power system inertia, complicating the task of maintaining a balance between generation and consumption. In this dissertation, coordinating Distributed Energy Resources (DER) is presented as a viable solution to these challenges.DERs have the potential to offer different ancillary services such as fast frequency response (FFR) when efficiently coordinated. However, the practical implementation of such services demands both effective local sensing and control at the device level and the ability to precisely estimate and predict the availability of synthetic damping from a fleet in real time. Additionally, the inherent trade-off between a fleet being available for fast frequency response while providing other ancillary services needs to be characterized. This dissertation introduces a fully decentralized, packet-based controller for a diverse range of flexible loads. This controller dynamically prioritizes and interrupts DERs to generate synthetic damping suitable for primary frequency control. Moreover, the packet-based control methodology is demonstrated to accu- rately assess the real-time availability of synthetic damping. Furthermore, spectral analysis of historical frequency regulation data is employed to establish a probabilis- tic bound on the expected synthetic damping available for primary frequency control from a fleet and the trade-off of concurrently offering secondary frequency control. It is noteworthy that coordinating a large number of DERs can potentially result in grid constraint violations. To tackle this challenge, this dissertation employs con- vex inner approximations (CIA) of the AC power flow to address the optimization problem of quantifying the capacity of a three-phase distribution feeder to accommo- date DERs. This capacity is often referred to as hosting capacity (HC). However, in this work, we consider separate limits for positive and negative DER injections at each node, ensuring that injections within these nodal limits adhere to feeder voltage and current constraints. The methodology dissects a three-phase feeder into individual phases and applies CIA-based techniques to each phase. Additionally, new approaches are introduced to modify the per-phase optimization problems to mitigate the inherent conservativeness associated with CIA methods and enhance HC. This includes selectively adjusting the per-phase impedances and proposing an iterative relaxation method for per-phase voltage bounds

    Special Topics in Information Technology

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    This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2019-20 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists

    Cross-layer energy efficiency of plc systems for smart grid applications

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    Though opinions are still divided over the specific choices of technology for smart grid, there is a consensus that heterogeneous communications network is most appropriate. Power line communication (PLC) is promising because it is readily available and it aligns with the natural topology of power distribution network. One of the emerging realities is that the communication system enabling smart grid must be energy-efficient. This thesis employs a cross-layer approach to address energy efficiency of PLC networks in different smart grid scenarios. At network layer, this work exploits the topology of a PLC-enabled advanced metering infrastructure (AMI) to improve the probability of successful packet delivery across the network. The technique, termed AMI clustering, leverages the traditional structure of the low voltage (LV) network by organising the smart meters into clusters and locally aggregating their readings. Improvement in packet delivery inherently reduces energy wastage. Next, the adaptation layer exploits the low data rate transmission techniques to reduce the energy requirements of PLC nodes. To achieve that, this work developed a network model in NS-3 (an open-source network simulator) that considers PLC transceivers as resource-constrained devices and interconnects them to emulate home energy management system (HEMS). The model was validated with experimental results which showed that in the home area network (HAN), low-rate applications such as energy management can be supported over low-power PLC networks. Furthermore, at physical layer, this thesis proposes a more energy-efficient multi-carrier modulation scheme than the orthogonal frequency division multiplexing (OFDM) used in most of the current PLC systems. OFDM is widely known for its high peak-to-average-power ratio (PAPR) which degrades energy efficiency of the systems. This thesis found that by employing vector- OFDM (V-OFDM), power requirements of PLC transmitter can be reduced. The results also showed the energy efficiency can be further improved by using a dynamic noise cancellation technique such as dynamic peak-based threshold estimation (DPTE) at the receiver. By applying the proposed methods, packet delivery can be improved by 3% at network layer (which conserves energy) and reduced data rate can save about 2.6014 dB in transmit power. Finally, at physical layer, V-OFDM and DPTE can respectively provide 5.8 dB and 2.1 dB reduction in power requirements of the PLC transceivers. These signify that if V-OFDM is combined with DPTE, future PLC modems could benefit from energy-efficient power amplifiers at reduced cost

    Transitioning power distribution grid into nanostructured ecosystem : prosumer-centric sovereignty

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    PhD ThesisGrowing acceptance for in-house Distributed Energy Resource (DER) installations at lowvoltage level have gained much significance in recent years due to electricity market liberalisations and opportunities in reduced energy billings through personalised utilisation management for targeted business model. In consequence, modelling of passive customers’ electric power system are progressively transitioned into Prosumer-based settings where presidency for Transactive Energy (TE) system framework is favoured. It amplifies Prosumers’ commitments into annexing TE values during market participations and optimised energy management to earn larger rebates and incentives from TE programs. However, when dealing with mass Behind-The-Meter DER administrations, Utility foresee managerial challenges when dealing with distribution network analysis, planning, protection, and power quality security based on Prosumers’ flexibility in optimising their energy needs. This dissertation contributes prepositions into modelling Distributed Energy Resources Management System (DERMS) as an aggregator designed for Prosumer-centered cooperation, interoperating TE control and coordination as key parameters to market for both optimised energy trading and ancillary services in a Community setting. However, Prosumers are primarily driven to create a profitable business model when modelling their DERMS aggregator. Greedy-optimisation exploitations are negative concerns when decisions made resulted in detrimental-uncoordinated outcomes on Demand-Side Response (DSR) and capacity market engagements. This calls for policy decision makers to contract safe (i.e. cooperative yet competitive tendency) business models for Prosumers to maximise TE values while enhancing network’s power quality metrics and reliability performances. Firstly, digitalisation and nanostructuring of distribution network is suggested to identify Prosumer as a sole energy citizen while extending bilateral trading between Prosumer-to- Prosumer (PtP) with the involvements of other grid operators−TE system. Modelling of Nanogrid environment for DER integrations and establishment of local area network infrastructure for IoT security (i.e. personal computing solutions and data protection) are committed for communal engagements in a decentralise setting. Secondly, a multi-layered Distributed Control Framework (DCF) is proposed using Microsoft Azure cloud-edge platform that cascades energy actors into respective layers of TE control and coordination. Furthermore, modelling of flexi-edge computing architecture is proposed, comprising of Contract-Oriented Sensor-based Application Platform (COSAP) employing Multi-Agent System (MAS) to enhance data-sharing privacy and contract coalition agreements during PtP engagements. Lastly, the Agents of MAS are programmed with cooperative yet competitive intelligences attributed to Reinforcement Learning (RL) and Neural Networks (NN) algorithms to solve multimodal socio-economical and uncertainty problems that corresponded to Prosumers’ dynamic energy priorities within the TE framework. To verify the DERMS aggregator operations, three business models were proposed (i.e. greedy-profit margin, collegial-peak demand, reserved-standalone) to analyse comparative technical/physical and economic/social dimensions. Results showed that the proposed TE-valued DERMS aggregator provides participation versatility in the electricity market that enables competitive edginess when utilising Behind-The-Meter DERs in view of Prosumer’s asset scheduling, bidding strategy, and corroborative ancillary services. Performance metrics were evaluated on both domestic and industrial NG environments against IEEE Standard 2030.7-2017 & 2030.8-2018 compliances to ensure deployment practicability. Subsequently, proposed in-house protection system for DER installation serves as an add-on monitoring service which can be incorporated into existing Advance Distribution Management System (ADMS) for Distribution Service Operator (DSO) and field engineers use, ADMS aggregator. It provides early fault detections and isolation processes from allowing fault current to propagate upstream causing cascading power quality issues across the feeder line. In addition, ADMS aggregator also serves as islanding indicator that distinguishes Nanogrid’s islanding state from unintentional or intentional operations. Therefore, a Overcurrent Current Relay (OCR) is proposed using Fuzzy Logic (FL) algorithm to detect, profile, and provide decisional isolation processes using specified OCRs. Moreover, the proposed expert knowledge in FL is programmed to detect fault crises despite insufficient fault current level contributed by DER (i.e. solar PV system) which conventional OCR fails to trigger

    MediaSync: Handbook on Multimedia Synchronization

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    This book provides an approachable overview of the most recent advances in the fascinating field of media synchronization (mediasync), gathering contributions from the most representative and influential experts. Understanding the challenges of this field in the current multi-sensory, multi-device, and multi-protocol world is not an easy task. The book revisits the foundations of mediasync, including theoretical frameworks and models, highlights ongoing research efforts, like hybrid broadband broadcast (HBB) delivery and users' perception modeling (i.e., Quality of Experience or QoE), and paves the way for the future (e.g., towards the deployment of multi-sensory and ultra-realistic experiences). Although many advances around mediasync have been devised and deployed, this area of research is getting renewed attention to overcome remaining challenges in the next-generation (heterogeneous and ubiquitous) media ecosystem. Given the significant advances in this research area, its current relevance and the multiple disciplines it involves, the availability of a reference book on mediasync becomes necessary. This book fills the gap in this context. In particular, it addresses key aspects and reviews the most relevant contributions within the mediasync research space, from different perspectives. Mediasync: Handbook on Multimedia Synchronization is the perfect companion for scholars and practitioners that want to acquire strong knowledge about this research area, and also approach the challenges behind ensuring the best mediated experiences, by providing the adequate synchronization between the media elements that constitute these experiences
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