BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Australia/Brisbane BEGIN:STANDARD DTSTART:19920301T020000 TZOFFSETFROM:+1100 TZOFFSETTO:+1000 TZNAME:AEST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20220913T073216Z UID:881017BF-7336-4F86-A8FD-E9F5F2D05732 DTSTART;TZID=Australia/Brisbane:20220913T130000 DTEND;TZID=Australia/Brisbane:20220913T163000 DESCRIPTION:For the purpose of managing the climate change and efficient an d sustainable use of energy resources the significant amount of renewable energy sources (RES) have and are being connected to transmission and dist ribution networks around the world. The power systems with significant RES penetrationn\, often intermittent and stochastic\, demonstrate different steady state and dynamic behaviour and variable levels of and reliability in supplying demand. Therefore\, there is growing requirement for cost eff ective\, security\, control and flexibility provision by the RES\, demand and energy storage. The focus of this presentation is on one of these new system service providers\, namely end users or demand side management.\n\n Demand Side Management (DSM) is the modifications of demand side energy co nsumption patterns through methods such as financial incentives or raising awareness of environmental sustainability. Usually\, the objective of DSM is to encourage end-users to reduce demand consumption during peak times or shift the energy use to off-peak times\, e.g.\, during the night\, to c ater for system operational economics\, network investment deferral\, and system reliability enhancement. In order to perform any DSM for the purpos e of provision of advanced network services the necessary condition is ful l observability and controllability of demand. The advancement of electric ity market liberalization\, the proliferation of renewable but intermitten t energy resources and cost reduction of energy storage devices has enable d a wide range of applications of DSM in electrical energy systems.\n\nFol lowing the roll-out of smart meters in residential districts around the wo rld\, the end-users will gain better observability of their consumption\, as well as higher potential to participate in the power network daily oper ation. Higher granularity of low-level consumption data in the future dist ribution grid will bring benefits to both consumers and the distribution s ystem operator (DSO). On one hand\, smart metering will facilitate awarene ss of consumers about their daily consumption and enable them to make savi ngs by reacting to price signals or various types of incentives triggered by their electricity supplier. On the other\, smart meter data will provid e information to the DSO about individual load profiles\, enabling more ad vanced profiling of consumers in different areas and at different levels o f aggregation.\n\nLoad profiling has shown crucial role in the studies of direct load control\, Demand Response (DR) programs\, design of tariffs an d involvement of local generation. An important part of load profiling is flexibility profiling\, i.e. assessment of the size of controllable (shift able) load within the total load. The assessment can be performed in two d imensions: i) Time: observing the change in the size of controllable load within the total load over a day or a season\; ii) Space: observing the si ze of controllable load over a distribution network. In this case\, differ ent network buses will have different flexibility potential\, depending on their load mix (namely residential\, industrial or commercial users).\n\n Numerous business models for DSM activities\, which can generally be class ified into energy efficiency and demand response\, have been extensively i nvestigated and some have already been trailed in pilot sites by industrie s. Energy efficiency related business models\, which involve a permanent r eduction of electricity demand by replacing them with new more efficiency appliances such as washing machines and florescent lights\, may be investi gated for bidding for energy saving performance contracts with customers a nd capacity resources with system operators and so on. On the other hand\, demand response related business models\, which are more extensively stud ied compared to energy efficiency\, consist of interruptible/direct contro l loads for system reliability enhancing service\, increase/decrease loads together with energy storage devices for frequency regulation\, change lo ad shapes for wholesale price reduction and compensate for the intermitten t renewables with different actors of the networks including SO\, TSO\, DS O\, consumers/prosumers\, retailers\, and aggregators.\n\nAll existing mod els focus on various promising services that DSM can provide based on its merits of flexibility or ramp provision. The DSM actions\, as described ab ove\, however will have an impact on global power system operation such as voltage stability and angular stability. For example\, shifting large amo unt of induction motors (e.g.\, washing machines or air conditioning) from peak time to off-peak time\, the load mix at both\, peak and off-peak hou rs will be changed and hence the load response to network disturbances loc ally (at buses where DSM was performed) and globally across the network. T his may result in higher sensitivity of buses and the whole network to dis turbances and potentially lead to unexpected network responses to disturba nces and even to maloperation of protection system which would have been s et based on historic network performance. Without proper analysis of the i mpact on power system performance\, the action of DSM may endanger the sys tem and lead to operation close to stability (voltage or angular or both) margin especially if the disturbance happens right after DSM action.\n\nTh is seminar discusses advances in load modelling\, demand profiling and sha ping of dynamic response of demand from efficient processing of large amou nt of data coming from smart meters and extraction of information from exi sting customer data bases to forecasting demand composition\, controllabil ity and dynamic signatures of demand\, to the effect of DSM actions on ove rall distribution and transmission network efficiency and stability and su ch highlights potential that advanced prediction and control of demand cou ld have on operation of distribution and transmission networks with increa sing penetration of stochastic and uncertain renewable generation.\n\nBiog raphy of the presenter\n\nJovica V Milanović received Dipl.Ing. and M.Sc. degrees from the University of Belgrade\, Yugoslavia\, Ph.D. degree from the University of Newcastle\, Australia\, and D.Sc. degree from The Univer sity of Manchester\, UK. Prior to joining The University of Manchester\, U K\, in 1998\, he worked with “Energoproject”\, Engineering and Consult ing Co. and the University of Belgrade in Yugoslavia\, and the Universitie s of Newcastle and Tasmania in Australia.\n\nCurrently\, he is a Professor of Electrical Power Engineering and incoming Head of the Department of El ectrical and Electronic Engineering (from 1st January 2023) at The Univers ity of Manchester\, UK\, and Visiting Professor at the University of Novi Sad and the University of Belgrade\, Serbia. He was chairman of 5 internat ional conferences\, editor or member of editorial/technical boards of 70+ international journals and conferences\, research project assessor or pane l member for numerous international government research funding councils\, member of 9 (convenor of 3) past or current IEEE/CIGRE/CIRED WG and consu ltant or member of advisory boards for several international companies and organisations. Professor Milanovic participated in or lead numerous resea rch projects with total value of more than £80 million\, published over 6 00 research papers (including several prize papers) and reports\, gave ove r 30 key-note speeches at international conferences and presented about 15 0 courses/tutorials and lectures to industry and academia around the world .\n\nSpeaker(s): Prof Jovica V Milanović\, \n\nRoom: 914\, Bldg: Andrew N. Liveris Building (46) - UQ Maps | St Lucia\, 46-914 Seminar Room \, The University of Queensland \, Birsbane\, Queensland\, Australia\, 4072\, Vi rtual: https://events.vtools.ieee.org/m/323000 LOCATION:Room: 914\, Bldg: Andrew N. Liveris Building (46) - UQ Maps | St Lucia\, 46-914 Seminar Room \, The University of Queensland \, Birsbane\, Queensland\, Australia\, 4072\, Virtual: https://events.vtools.ieee.org/m/ 323000 ORGANIZER:saha@itee.uq.edu.au SEQUENCE:3 SUMMARY:Demand modelling\, profiling and management for efficient and secur e operation of net-zero power networks URL;VALUE=URI:https://events.vtools.ieee.org/m/323000 X-ALT-DESC:Description: <br /><p>For the purpose of managing the climate ch ange and efficient and sustainable use of energy resources the significant amount of renewable energy sources (RES) have and are being connected to transmission and distribution networks around the world. The power systems with significant RES penetrationn\, often intermittent and stochastic\, d emonstrate different steady state and dynamic behaviour and variable level s of and reliability in supplying demand.&nbsp\; &nbsp\;Therefore\, there is growing requirement for cost effective\, security\, control and flexibi lity provision by the RES\, demand and energy storage. &nbsp\;The focus of this presentation is on one of these new system service providers\, namel y end users or demand side management.</p>\n<p>Demand Side Management (DSM ) is the modifications of demand side energy consumption patterns through methods such as financial incentives or raising awareness of environmental sustainability. Usually\, the objective of DSM is to encourage end-users to reduce demand consumption during peak times or shift the energy use to off-peak times\, e.g.\, during the night\, to cater for system operational economics\, network investment deferral\, and system reliability enhancem ent. In order to perform any DSM for the purpose of provision of advanced network services the necessary condition is full observability and control lability of demand. The advancement of electricity market liberalization\, the proliferation of renewable but intermittent energy resources and cost reduction of energy storage devices has enabled a wide range of applicati ons of DSM in electrical energy systems.</p>\n<p>Following the roll-out of smart meters in residential districts around the world\, the end-users wi ll gain better observability of their consumption\, as well as higher pote ntial to participate in the power network daily operation. Higher granular ity of low-level consumption data in the future distribution grid will bri ng benefits to both consumers and the distribution system operator (DSO). On&nbsp\;&nbsp\; one hand\, smart metering will facilitate awareness of co nsumers about their daily consumption and enable them to make savings by r eacting to price signals or various types of incentives triggered by their electricity supplier. On the other\, smart meter data will provide inform ation to the DSO about individual load profiles\, enabling more advanced p rofiling of consumers in different areas and at different levels of aggreg ation.</p>\n<p>Load profiling has shown crucial role in the studies of dir ect load control\, Demand Response (DR) programs\, design of tariffs and i nvolvement of local generation. An important part of load profiling is fle xibility profiling\, i.e. assessment of the size of controllable (shiftabl e) load within the total load. The assessment can be performed in two dime nsions: i) Time: observing the change in the size of controllable load wit hin the total load over a day or a season\; ii) Space: observing the size of controllable load over a distribution network. In this case\, different network buses will have different flexibility potential\, depending on th eir load mix (namely residential\, industrial or commercial users).</p>\n< p>Numerous business models for DSM activities\, which can generally be cla ssified into energy efficiency and demand response\, have been extensively investigated and some have already been trailed in pilot sites by industr ies. Energy efficiency related business models\, which involve a permanent reduction of electricity demand by replacing them with new more efficienc y appliances such as washing machines and florescent lights\, may be inves tigated for bidding for energy saving performance contracts with customers and capacity resources with system operators and so on. On the other hand \, demand response related business models\, which are more extensively st udied compared to energy efficiency\, consist of interruptible/direct cont rol loads for system reliability enhancing service\, increase/decrease loa ds together with energy storage devices for frequency regulation\, change load shapes for wholesale price reduction and compensate for the intermitt ent renewables with different&nbsp\; actors of the networks including SO\, TSO\, DSO\, consumers/prosumers\, retailers\, and aggregators.</p>\n<p>Al l existing models focus on various promising services that DSM can provide based on its merits of flexibility or ramp provision.&nbsp\; The DSM acti ons\, as described above\, however will have an impact on global power sys tem operation such as voltage stability and angular stability. For example \, shifting large amount of induction motors (e.g.\, washing machines or a ir conditioning) from peak time to off-peak time\, the load mix at both\, peak and off-peak hours will be changed and hence the load response to net work disturbances locally (at buses where DSM was performed) and globally across the network. This may result in higher sensitivity of buses and the whole network to disturbances and potentially lead to unexpected network responses to disturbances and even to maloperation of protection system wh ich would have been set based on historic network performance. Without pro per analysis of the impact on power system performance\, the action of DSM may endanger the system and lead to operation close to stability (voltage or angular or both) margin especially if the disturbance happens right af ter DSM action.</p>\n<p>&nbsp\;&nbsp\;&nbsp\; &nbsp\;&nbsp\;&nbsp\;&nbsp\; &nbsp\;&nbsp\;&nbsp\; This seminar &nbsp\;discusses advances in load model ling\, demand profiling&nbsp\; and shaping of dynamic response of demand f rom efficient processing of large amount of data coming from smart meters and extraction of information from existing customer data bases to forecas ting demand composition\, controllability and dynamic signatures of demand \, &nbsp\;to the effect of DSM actions&nbsp\; on overall distribution and transmission network efficiency and stability and such highlights potentia l that advanced prediction and control of demand could have on operation o f distribution and transmission networks with increasing penetration of st ochastic and uncertain renewable generation.</p>\n<p>&nbsp\;</p>\n<p><stro ng>Biography of the presenter</strong></p>\n<p><strong>&nbsp\;</strong></p >\n<p><strong>&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\; Jovica V Milanovi ć</strong> received Dipl.Ing. and M.Sc. degrees from the University of Be lgrade\, Yugoslavia\, Ph.D. degree from the University of Newcastle\, Aust ralia\, and D.Sc. degree from The University of Manchester\, UK. Prior to joining The University of Manchester\, UK\, in 1998\, he worked with &ldqu o\;Energoproject&rdquo\;\, Engineering and Consulting Co. and the Universi ty of Belgrade in Yugoslavia\, and the Universities of Newcastle and Tasma nia in Australia.</p>\n<p>&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\;&nbsp\ ;&nbsp\;&nbsp\;&nbsp\;&nbsp\; Currently\, he is a Professor of Electrical Power Engineering and incoming Head of the Department of Electrical and El ectronic Engineering (from 1<sup>st</sup> January 2023) at The University of Manchester\, UK\, and Visiting Professor at the University of Novi Sad and the University of Belgrade\, Serbia. He was chairman of 5 internationa l conferences\, editor or member of editorial/technical boards of 70+ inte rnational journals and conferences\, research project assessor or panel me mber for numerous international government research funding councils\, mem ber of 9 (convenor of 3) past or current IEEE/CIGRE/CIRED WG and consultan t or member of advisory boards for several international companies and org anisations. Professor Milanovic participated in or lead numerous research projects with total value of more than &pound\;80 million\, published over 600 research papers (including several prize papers) and reports\, gave o ver 30 key-note speeches at international conferences and presented about 150 courses/tutorials and lectures to industry and academia around the wor ld.</p> END:VEVENT END:VCALENDAR