About this Virtual Instructor Led Training (VILT) This 5 half-day Virtual Instructor Led Training (VILT) course will assist energy professionals in the planning and operation of a power system from renewable energy sources. The VILT course will discuss key operating requirements for an integrated, reliable and stable power system. The unique characteristics of renewable energy are discussed from a local, consumer centric and system perspective, bringing to life the ever-changing paradigm in delivering energy to customers. The course will explore the technical challenges associated with interconnecting and integrating hundreds of gigawatts of solar power onto the electricity grid in a safe and reliable way. With references to international case studies, the VILT course will also demonstrate the state of the art methodologies used in forecasting solar power. The flexibility of the invertor-based resources will facilitate higher penetrations of photovoltaic, battery electricity storage systems and demand response while co-optimizing customer resources. The contribution of inverter-based generators that provides voltage support, frequency response and regulation (droop response), reactive power and power quality with a high level of accuracy and fast response will be addressed. Furthermore, this VILT course will also describe how microgrids' controllers can allow for a fully automated energy management. Distributed energy resources are analyzed in detail from a technical and financial aspect and will address the best known cost based methodologies such as project financing and cost recovery. Training Objectives Upon completion of this VILT course, participants will be able to: Learn about renewable energy resources, their applications and methods of analysis of renewable energy issues. Review the operational flexibility of renewable energy at grid level, distribution network and grid edge devices. Understand and analyze energy performance from main renewable energy systems. Get equipped on the insights into forecasting models for solar energy. Predict solar generation from weather forecasts using machine learning. Explore operational aspects of a complex power system with variability from both the supply & demand sides. Manage the impact of the design of a Power Purchase Agreement (PPA) on the power system operation. Target Audience Engineers, planners and operations professionals from the following organizations: Energy aggregators who would like to understand the system operations of renewable energy power plants Renewable energy power system operator Energy regulatory agencies who aim to derive strategies and plans based on the feedback obtained from the power system operations Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-day sessions comprising 4 hours per day, including time for lectures, discussion, quizzes and short classroom exercises. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your first expert course leader is a Utility Executive with extensive global experience in power system operation and planning, energy markets, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex projects in operations and conducted long term planning studies to support planning and operational reliability standards. Specializing in Smart Grids, Operational flexibilities, Renewable generation, Reliability, Financial Engineering, Energy Markets and Power System Integration, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. She was the Operations Expert in the regulatory assessment in Oman. She is a registered member of the Professional Engineers of Ontario, Canada. She is also a contributing member to the IEEE Standards Association, WG Blockchain P2418.5. With over 25 years with Ontario Power Generation (Revenue $1.2 Billion CAD, I/S 16 GW), she served as Canadian representative in CIGRE, committee member in NSERC (Natural Sciences and Engineering Research Council of Canada), and Senior Member IEEE and Elsevier since the 90ties. Our key expert chaired international conferences, lectured on several continents, published a book on Reliability and Security of Nuclear Power Plants, contributed to IEEE and PMAPS and published in the Ontario Journal for Public Policy, Canada. She delivered seminars organized by the Power Engineering Society, IEEE plus seminars to power companies worldwide, including Oman, Thailand, Saudi Arabia, Malaysia, Indonesia, Portugal, South Africa, Japan, Romania, and Guyana. Your second expert course leader is the co-founder and Director of Research at Xesto Inc. Xesto is a spatial computing AI startup based in Toronto, Canada and it has been voted as Toronto's Best Tech Startup 2019 and was named one of the top 10 'Canadian AI Startups to Watch' as well as one of 6th International finalists for the VW Siemens Startup Challenge, resulting in a partnership. His latest app Xesto-Fit demonstrates how advanced AI and machine learning is applied to the e-commerce industry, as a result of which Xesto has been recently featured in TechCrunch. He specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. At Xesto, he leads projects that focus on applying cutting edge research at the intersection of spatial analysis, differential geometry, optimization of deep neural networks, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. In addition, he is a Ph.D candidate in the Mathematics department at UofT, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. He earned a Bachelor's and MSc in Mathematics, both at the University of Toronto. Having presented at research seminars as well as instructing engineers on various levels, he has the ability to distill advanced theoretical concept to diverse audiences on all levels. In addition to research, our key expert is also an avid traveler and plays the violin. POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations
Streaming telemetry training course description An introduction to streaming telemetry. The course progresses from a brief look at the weaknesses of SNMP onto what streaming telemetry is, how it differs from the xflow technologies, the data formats available and how to configure it. What will you learn Describe streaming telemetry. Explain how streaming telemetry works. Describe the data presentation formats available. Configure streaming telemetry. Streaming telemetry training course details Who will benefit: Network engineers. Prerequisites: TCP/IP foundation for engineers. Duration 1 day Streaming telemetry training course content What is streaming telemetry? SNMP weaknesses, Netflow, sflow, polling and the old models, push vs pull, What is streaming telemetry? Telemetry streaming architecture Model driven versus event driven telemetry, subscriptions, publications. Periodic versus on change, model selection and scalability. Telemetry streaming protocols TCP, UDP, SSH, HTTP, HTTP2, NETCONF, RESTCONF, gRPC, gNMI. Models and Encoding The role of YANG. YANG models and tools. XML/ NETCONF, JSON/RESTCONF, JSON over UDP. Protocol buffers/gRPC. Google Protocol Buffers Decoder ring, protocol definition file. GPB-KV, GPB-Compact. Keys. Streaming telemetry configuration Router: Destination, Sensor, subscription. Collector: YANG models, .proto file. Pipeline. ELK: Consume, store, visualise streaming data. Collection tools APIs, YANG development Kit, Downstream consumers, influxdata, Grafana, Kafka, Prometheus, others.
NETCONF and YANG training course description An introduction to NETCONF and YANG. The course progresses from what they are, why they are needed, and how to configure them onto a more detailed analysis of how NETCONF works and how to read YANG models. What will you learn Recognise the limits and problems of SNMP and the CLI. Describe the relationship between NETCONF and YANG. Configure NETCONF on network devices. Use NETCONF to configure devices. Read YANG models. NETCONF and YANG training course details Who will benefit: Network engineers. Prerequisites: Network management technologies Duration 1 day NETCONF and YANG training course content What are NETCONF and YANG? Network management and configuration issues. What is NETCONF? What is YANG? Protocols, data models, architecture. Hands on Configuring NETCONF on network devices, using NETCONF. NETCONF NETCONF layers, Secure transport: SSH, Messages: rpc, Operations, Content. Base operations: <get>, <get-config>, <edit-config>, <copy-config>, <delete-config>, <lock>,<unlock>, <close-session>, <kill-session> NETCONF datastores: :candidate, :startup, running. Hands on Retrieving a configuration with NETCONF, Editing a configuration with NETCONF. NETCONF more details NETCONF traffic flows, NETCONF capabilities, hello, capabilities exchange., Filtering data, atomic transactions, validating configurations. Hands on Using NETCONF. YANG YANG models, IETF standard YANG models, tree diagrams, an example: YANG interface management, Module header, Imports and includes, Containers, Lists, leaves, Data types, typedef, Instance data, XML. Hands on Reading YANG data models, creating a configuration instance.
Management of Risk (M_o_R®) Foundation: In-House Training This M_o_R® Foundation course prepares learners to demonstrate knowledge and comprehension of the four elements of the M_o_R framework: Principles, Approach, Processes, Embedding and Reviewing and how these elements support corporate governance. The M_o_R Foundation Course is also a prerequisite for the M_o_R Practitioner qualification. What you will Learn At the end of the M_o_R Foundation course, participants will gain competencies in and be able to: Describe the key characteristics of risk and the benefits of risk management List the eight M_o_R Principles List and describe the use of the key M_o_R Approach documents Create Probability and Impact scales Define and distinguish between risks and issues Create a Risk Register Create a Stakeholder map Identify the key roles in risk management Use the key techniques and describe specialisms in risk management Undertake the M_o_R Foundation examination Introduction Introduction to the M_o_R course What is a risk? What is risk management? Why is risk management so important? Basic risk definitions The development of knowledge about risk management Corporate governance and internal control Where and when should risk management be applied? M_o_R Principles The purpose of M_o_R principles Aligns with objectives Fits the context Engages stakeholders Provides clear guidance Informs decision-making Facilitates continual improvement Creates a supportive culture Achieves measurable value Risk management maturity models M_o_R Approach Relationship between the documents Risk management policy Risk management process guide Risk management strategy Risk register Issue register Risk response plan Risk improvement plan Risk communications plan M_o_R Process Common process barriers Identify contexts Identify the risks Assess estimate Assess evaluate Plan Implement Communication throughout the process M_o_R Perspectives Strategic perspective Program perspective Project perspective Operational perspective Risk Specialisms Business continuity management Incident and crisis management Health and Safety management Financial risk management Environmental risk management Reputational risk management Contract risk management
Managing Successful Programmes (MSP®) 5th Edition Foundation: In-House Training Managing Successful Programmes (MSP®) is a globally-recognized framework for best practice programme management. MSP certification provides guidance for programme managers, business change managers and the next step for project managers to develop their knowledge and skills to be able to positively respond to the challenges for managing programmes and larger, more strategic or multiple projects. MSP 5th edition emphasizes flexibility, adaptability, and responsiveness by adopting an incremental approach to the programme lifecycle and thus enabling organizational agility. AXELOS offers two levels of MSP Examination: MSP Foundation and MSP Practitioner. The MSP Foundation Examination is intended to assess whether the candidate can demonstrate sufficient recall and understanding of the MSP programme management framework. The MSP Foundation qualification is a prerequisite for the MSP Practitioner Examination, which assesses the ability to apply understanding of the MSP programme management framework in context. The MSP® 5th Edition Foundation course is a training based on the exam specification for MSP Foundation certification and is aligned with the Managing Successful Programmes (5th Edition) guide from AXELOS. What you will Learn At the end of this course, participants will be able to: Understand key concepts relating to programmes and MSP Understand how the MSP principles underpin the MSP framework Understand the MSP themes and how they are applied throughout the programme Understand the MSP processes and how they are carried out throughout the programme Key Concepts of MSP Programmes Three Lenses of MSP Principles Themes and Governance Organization Organization Theme Organization Structure Individual Roles Stakeholder Management Design Design Theme Benefits Risk Identification and Prioritization Target Operating Model Documents and Key Roles Justification Justification Theme Business Case Financial Planning Documents and Key Roles Structure Structure Theme Delivery Planning Dependencies Benefits Realization Plan Resourcing Documents and Key Roles Knowledge Knowledge Theme Knowledge Management Information Management Document and Key Roles Assurance Assurance Theme Assurance at Multiple Levels Assurance Planning Document and Key Roles Decisions Decisions Theme Issue Resolution Risk Response Data Gathering and Reporting Options and Analysis Document and Key Roles MSP Processes Identify the Programmeâ¯â¯â¯ Design the Outcomes Plan Progressive Delivery Deliver the Capabilities Embed the Outcomes Evaluate New Information Close the Programme
Cloud technologies training course description This course provides an introduction to cloud technologies, including, configuration and deployment, security, maintenance, and management. It covers all aspects of cloud computing infrastructure. It will help you to master the fundamental concepts, terminology, and characteristics of cloud computing. . What will you learn Contrast and compare AWS, GCP and Azure. Explain the different cloud services, models and characteristics. Explain cloud virtualization components and options. Explain cloud security options. Describe cloud automation, orchestration, monitoring and performance options. Cloud technologies training course details Who will benefit: Anyone working with or looking to work with cloud technologies. Prerequisites: None. Duration 2 days Cloud technologies training course contents What is the cloud? The Internet Cloud computing Benefits Disadvantages Cloud services IaaS, PaaS, SaaS, others. Cloud service providers AWS, GCP Microsoft Azure, others Cloud architectures Private, public, hybrid others Cloud based delivery The cloud and virtualization Virtual Machines, networks, storage, deployment. Accessing the Virtual Machine Secure cloud environments Security considerations. Data privacy considerations Automation and orchestration Monitoring and performance Performance Cost issues Cost containment