Power Transmission & Distribution > Demand Side Management

About this Training Course

The energy sector is undergoing a profound paradigm shift, characterized by the convergence of cutting-edge technologies, regulatory dynamism, and the escalating integration of renewable energy resources. This course delves into the technical intricacies of advanced methodologies for energy management. The course scrutinizes demand response and energy conservation programs, highlighting their implications on energy efficiency, grid stability, and sustainable energy practices.

Integration of Power Electronics and New Technologies: Power electronics and emerging technologies play a critical role in Demand management. Power electronics facilitate enhanced energy conversion, grid integration of renewables, and dynamic load management. The technical depth of this discussion includes power electronics’ role in grid-tied inverters for solar and wind energy systems, battery energy storage, and electric vehicle charging infrastructure.

Regulatory Frameworks and Zero Net Energy Building Codes This course dissects the technical nuances of regulatory frameworks and their impact on energy conservation strategies. Special emphasis is placed on zero net energy building codes, which mandate energy-efficient building designs, passive solar techniques, and advanced solutions. The technical details encompass building envelope modeling, system efficiency, and on-site renewable energy generation.

Public Agency Objectives: Energy Consumption and Demand Management: The technical objectives of public agencies regarding energy management are articulated. These objectives span a spectrum of technical parameters, including energy consumption reduction through lighting and HVAC optimization, load shedding techniques, and demand forecasting models for grid stability enhancement.

Demand Response for Grid Economics and System Security- Demand Response to Price is dissected technically, with a focus on its economic and security dimensions. This involves sophisticated load profiling, demand forecasting algorithms, and real-time pricing mechanisms. Grid reliability is maintained through the fine-grained control of loads, mitigating peak demand and alleviating transmission congestion.

Advanced Load Forecasting using Artificial Intelligence:  Load forecasting AI refers to the use of artificial intelligence (AI) techniques to predict and forecast electrical load or energy consumption. This is a critical task in the energy and utility sector because accurate load forecasting helps grid operators, power companies, and energy providers to optimize energy production and distribution, plan for capacity expansion, and enhance overall energy efficiency. The course tackles the key points about load forecasting AI.

Conservation Programs: Technical Attributes and Metrics The technical success criteria encompass energy audits, advanced metering infrastructure, and continuous commissioning.

Integration of Renewable Resources: Technical Challenges and Solutions As renewable energy penetration intensifies, the course underscores the technical intricacies of grid integration. Demand response is presented as a technical strategy to tackle intermittency and ensure grid stability. Topics include dynamic load forecasting, smart grid control systems, and advanced grid management algorithms.

Enhancing Market Competition and Liquidity: The course delves into the technical underpinnings of demand response as a competitive market tool. Advanced market mechanisms, such as locational marginal pricing (LMP) and demand bidding strategies, are explored. Technical aspects include demand elasticity modeling, market-clearing algorithms, and congestion pricing.

Consumer-Centric and System-Level Perspectives The course provides a technical breakdown of the dual perspectives – consumer-centric and system-level. It elucidates advanced technologies like home energy management systems (HEMS), distributed energy resource management systems (DERMS), and grid optimization algorithms. These enable real-time energy decision-making and grid-balancing at both individual and system-wide scales.

Interoperability and Transactive Energy Interoperability standards in energy systems are dissected technically. The discussion encompasses communication protocols, data modeling, and standardization bodies. Transactive energy is explored in detail, focusing on technical aspects like blockchain-based smart contracts, microgrid interoperability, and grid-edge IoT devices.

Blockchain for Cybersecurity and Peer-to-Peer Transactions The technical dimension of blockchain’s role in energy cybersecurity is elucidated. This includes blockchain consensus mechanisms, cryptographic hashing, and secure energy data exchange protocols. The practical implementation of blockchain in peer-to-peer energy transactions and Renewable Energy Certificate (REC) trading is explored.

This course offers an in-depth technical exploration of the multifaceted aspects of modern energy management. It underscores the technical prowess of power electronics, regulatory intricacies, and the sophisticated engineering required for demand response, conservation, and renewable energy integration.

As the energy landscape evolves, these technical insights serve as a compass, guiding the industry towards a sustainable and resilient energy future.

  • Regulators and government agencies advising on public energy conservation programs
  • All professionals interested in expanding their expertise, or advancing their career, or take on management and leadership roles in the rapidly evolving energy sector
  • Energy professionals implementing demand side management, particularly in power systems with increased renewable penetration, to allow the much needed operational flexibility paramount to maintaining the reliability and stability of the power system and in the same time offering all classes of customers flexible and economical choices
  • Any utility professional interested in understanding the new developments in the power industry
  • Intermediate

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.

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.
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