Novel processes for smart grid information exchange and knowledge representation using the IEC common information model

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The IEC Common Information Model (CIM) is of central importance in enabling smart grid interoperability. Its continual development aims to meet the needs of the smart grid for semantic understanding and knowledge representation for a widening domain of resources and processes. With smart grid evolution the importance of information and data management has become an increasingly pressing issue not only because far more data is being generated using modern sensing, control and measuring devices but also because information is now becoming recognised as the ‘integral component’ that facilitates the optimal flexibility required of the smart grid. This thesis looks at the impacts of CIM implementation upon the landscape of smart grid issues and presents research from within National Grid contributing to three key areas in support of further CIM deployment. Taking the issue of Enterprise Information Management first, an information management framework is presented for CIM deployment at National Grid. Following this the development and demonstration of a novel secure cloud computing platform to handle such information is described. Power system application (PSA) models of the grid are partial knowledge representations of a shared reality. To develop the completeness of our understanding of this reality it is necessary to combine these representations. The second research contribution reports on a novel methodology for a CIM-based model repository to align PSA representations and provide a knowledge resource for building utility business intelligence of the grid. The third contribution addresses the need for greater integration of information relating to energy storage, an essential aspect of smart energy management. It presents the strategic rationale for integrated energy modeling and a novel extension to the existing CIM standards for modeling grid-scale energy storage. Significantly, this work has already contributed to a larger body of work on modeling Distributed Energy Resources currently under development at the Electric Power Research Institute (EPRI) in the USA.Dr. Martin Bradley on behalf of National Grid Plc. and the Engineering and Physical Sciences Research Council (EPSRC

Digital Twinning in Smart Grid Networks: Interplay, Resource Allocation and Use Cases

Motivated by climate change, increasing industrialization and energy reliability concerns, the smart grid is set to revolutionize traditional power systems. Moreover, the exponential annual rise in number of grid-connected users and emerging key players e.g. electric vehicles strain the limited radio resources, which stresses the need for novel and scalable resource management techniques. Digital twin is a cutting-edge virtualization technology that has shown great potential by offering solutions for inherent bottlenecks in traditional wireless networks. In this article, we set the stage for various roles digital twinning can fulfill by optimizing congested radio resources in a proactive and resilient smart grid. Digital twins can help smart grid networks through real-time monitoring, advanced precise modeling and efficient radio resource allocation for normal operations and service restoration following unexpected events. However, reliable real-time communications, intricate abstraction abilities, interoperability with other smart grid technologies, robust computing capabilities and resilient security schemes are some open challenges for future work on digital twins.Comment: 7 pages, 3 figure

Integrated Energy Management of a Plug-in Electric Vehicle in Residential Distribution Systems with Renewables

International audienceAccording to innovation in grid connected transportation industry and with ever increasing concerns on environmental issues and clean energy, electric vehicles (EVs) and hybrid electric vehicles (HEVs) with low noise, zero emission, and high efficiency have attracted more and more attention of researchers, governments and industries, they are becoming the most likely fleets to replace gasoline vehicles in future power systems. In addition to the approved advantages for transportation, EVs have the potential to provide other benefits within the connected residential distribution to micro-grids and smart grids as part of a vehicle-to-grid (V2G) system, knowing that in future systems residential distribution can be seen as an energy resource with decentralized and autonomous decisions in the energy management called smart house or prosumer. They can participate effectively in helping to balance supply and demand by valley filling and peak shaving. The EV battery can be charged during low demand and the stored power can be fed power back into the micro-grid during high-demand periods, providing a spinning reserve to dump short power demand changes. V2G may also be used to buffer renewable energy sources, such as photovoltaic generators, by storing excess energy produced during illumination periods, and feeding it back into the grid during high-load periods, thus effectively stabilizing the intermittency of solar power. In this context, this paper describes an energy management system for a smart house based on hybrid PV-battery and V2G. Keywords—Vehicle-to-grid (V2G), vehicle-to-home (V2H), residential distribution, smart house, balance supply and demand

A peer-to-peer service architecture for the Smart Grid

Short paperThe Smart Grid vision needs to address hard challenges such as interoperability, reliability and scalability before it can become fulfilled. The need to provide full interoperability between current and future energy and non-energy systems and its disparate technologies along with the problem of seamless discovery, configuration, and communication of a large variety of networked devices ranging from the resource constrained sensing devices to the large machines inside a data center requires an agnostic Service Oriented Architecture. Moreover, the sheer scale of the Smart Grid and the criticality of the communication among its subsystems for proper management, demands a scalable and reliable communication framework able to work in an heterogeneous and dynamic environment. In this position paper, we propose a generic framework, based on Web Services for interoperability, and epidemic or gossip based communication protocols for reliability and scalability, that can serve a general management substrate where several Smart Grid problems can be solved. We illustrate the flexibility of the proposed framework by showing how it can be used in two specific scenarios.Important challenges in interoperability, reliability, and scalability need to be addressed before the Smart Grid vision can be fulfilled. The sheer scale of the electric grid and the criticality of the communication among its subsystems for proper management, demands a scalable and reliable communication framework able to work in an heterogeneous and dynamic environment. Moreover, the need to provide full interoperability between diverse current and future energy and non-energy systems, along with seamless discovery and configuration of a large variety of networked devices, ranging from the resource constrained sensing devices to servers in data centers, requires an implementation-agnostic Service Oriented Architecture. In this position paper we propose that this challenge can be addressed with a generic framework that reconciles the reliability and scalability of Peer-to-Peer systems, with the industrial standard interoperability of Web Services. We illustrate the flexibility of the proposed framework by showing how it can be used in two specific scenarios

Towards Predictive Energy Management in Information Systems: A Research Proposal

The progressive energy transition, driven by the growing number of renewable energies, the increasing social importance of sustainable actions, as well as new technologies, causes major challenges for enterprises and power supply companies (PSCs). While the electricity price fluctuations will continue to increase in the future, the installation of smart meters and smart meter gateways is aimed to ensure grid stability. They provide the basis for communication between companies and PSCs. In order to make companies energy consumption predictable even before the energy is needed, an automated data exchange between an energy management system (EnMS) and enterprise resource planning (ERP) system is essential. Therefore, we address this problem by following five research steps to develop a prototype for predictive energy management in information systems

Delay and energy efficiency optimizations in smart grid neighbourhood area networks

Smart grids play a significant role in addressing climate change and growing energy demand. The role of smart grids includes reducing greenhouse gas emission reduction by providing alternative energy resources to the traditional grid. Smart grids exploit renewable energy resources into the power grid and provide effective two-way communications between smart grid domains for efficient grid control. The smart grid communication plays a pivotal role in coordinating energy generation, energy transmission, and energy distribution. Cellular technology with long term evolution (LTE)-based standards has been a preference for smart grid communication networks. However, integrating the cellular technology and the smart grid communication network puts forth a significant challenge for the LTE because LTE was initially invented for human centric broadband purpose. Delay and energy efficiency are two critical parameters in smart grid communication networks. Some data in smart grids are real-time delay-sensitive data which is crucial in ensuring stability of the grid. On the other hand, when abnormal events occur, most communication devices in smart grids are powered by local energy sources with limited power supply, therefore energy-efficient communications are required. This thesis studies energy-efficient and delay-optimization schemes in smart grid communication networks to make the grid more efficient and reliable. A joint power control and mode selection in device-to-device communications underlying cellular networks is proposed for energy management in the Future Renewable Electric Energy Delivery and Managements system. Moreover, a joint resource allocation and power control in heterogeneous cellular networks is proposed for phasor measurement units to achieve efficient grid control. Simulation results are presented to show the effectiveness of the proposed schemes

Complex Large-Scale Energy Resource Management Optimization Considering Demand Flexibility

As renewable energy sources penetration is increasing in the power distribution network, an energy aggregator can provide a highly flexible generation and demand as required by the smart grid paradigm. However, this energy aggregator entity needs adequate decision support tools to overcome the complex challenges and deal with a number of energy resources. So, the energy resource management is crucial for the aggregator, to increase the profits, reduce the operation costs, reduce the carbon footprint and also to improve the system stability. Thus, this paper proposes a model for a large-scale energy resource scheduling problem of aggregators in a smart grid. Also, it is compared the performance of five evolutionary algorithms to solve this kind of problem. A realistic case study is performed using a real distribution network in Zaragoza, Spain. The results show that load flexibility can contribute to the profitability improvement of the aggregators' entities.This work has received funding from Portugal 2020 under SPEAR project (NORTE-01-0247-FEDER-040224) and from National Funds through the FCT Portuguese Foundation for Science and Technology, under Project UIDB/00760/2020. Joao Soares is supported by FCT CEECIND/02814/2017 grantinfo:eu-repo/semantics/publishedVersio

Analysis of the Harmonic Performance of Power Converters and Electrical Drives

Power converters have progressively become the most efficient and attractive solution in recent decades in many industrial sectors, ranging from electric mobility, aerospace applications to attain better electric aircraft concepts, vast renewable energy resource integration in the transmission and distribution grid, the design of smart and efficient energy management systems, the usage of energy storage systems, and the achievement of smart grid paradigm development, among others.In order to achieve efficient solutions in this wide energy scenario, over the past few decades, considerable attention has been paid by the academia and industry in order to develop new methods to achieve power systems with maximum harmonic performance aiming for two main targets. On the one hand, the high-performance harmonic performance of power systems would lead to improvements in their power density, size and weight. This becomes critical in applications such as aerospace or electric mobility, where the power converters are on-board systems. On the other hand, current standards are becoming more and more strict in order to reduce the EMI and EMC noise, as well as meeting minimum power quality requirements (i.e., grid code standards for grid-tied power systems)

An event-based resource management framework for distributed decision-making in decentralized virtual power plants

The Smart Grid incorporates advanced information and communication technologies (ICTs) in power systems, and is characterized by high penetration of distributed energy resources (DERs). Whether it is the nation-wide power grid or a single residential building, the energy management involves different types of resources that often depend on and influence each other. The concept of virtual power plant (VPP) has been proposed to represent the aggregation of energy resources in the electricity market, and distributed decision-making (DDM) plays a vital role in VPP due to its complex nature. This paper proposes a framework for managing different resource types of relevance to energy management for decentralized VPP. The framework views VPP as a hierarchical structure and abstracts energy consumption/generation as contractual resources, i.e., contractual offerings to curtail load/supply energy, from third party VPP participants for DDM. The proposed resource models, event-based approach to decision making, multi-agent system and ontology implementation of the framework are presented in detail. The effectiveness of the proposed framework is then demonstrated through an application to a simulated campus VPP with real building energy data

Product Specification: Distributed Control Module (DOE-PSU-0000922-5)

This product specification describes the architecture, implementation, and hardware descriptions of a Distributed Control Module (DCM) prototype. A DCM is an enabling technology for distributed energy resources (DER). DERs are grid-enabled generation, storage, and load devices that are owned by utility customers. DCMs enable information exchange between a distributed energy resource management system (DERMS) and DERs for the purpose of networking large numbers of DERs. The DCM prototype described within this document enables DER participation in a service-oriented aggregation system. A DERMS server provides IEEE 2030.5 smart energy resource services to DCM clients using a request/response information exchange process. DCMs serve as gateways between the DERMS and the DERs, and they act as agents on behalf of the DER owners to provide intelligent management of the DERs