BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20240310T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20241103T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:PST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240417T202003Z UID:5A5681DA-439C-41FD-B9AC-4D72C01E30C2 DTSTART;TZID=America/Los_Angeles:20240417T100000 DTEND;TZID=America/Los_Angeles:20240417T110000 DESCRIPTION:Will provide a high level brief overview of the solutions and a lgorithms evolved over the last several decades to solve the short term un it scheduling problem. The focus is on the practically most used solutions to power systems operations. The discussion will include priority merit l ist\, dynamic programming\, Linear Programming\, Lagrangian relaxation\, A ugmented Lagrangian relaxation\, and the game changer Mixed Integer Progra m (MIP). The mathematical breakthroughs and efficient search algorithms us ed in recent MIP commercial solvers made MIP the algorithm of choice widel y adopted by the power systems industry to solve such highly complex\, non -convex\, and combinatorial optimization problem. The huge reduction in th e MIP optimization solution time\, the ease of mathematical constraints mo deling\, and the increased solution quality transformed the real-time appl ications and made it possible to model large number of complex resources ’ types like combined cycle units\, startup times and cost\, transition time and cost\, dynamic ramp rates as functions of resources MW. These adv ances in MIP made it possible to also include unprecedented large set of c ross-resources and cross-time intervals coupling constraints such as trans mission\, and environment constraints in optimizing operations in day-ahea d and real-time applications.\n\nAs illustrative example\, the presentatio n will highlight the current large-scale mathematical MIP model sizes\, so lution times\, and the optimal MIP integer gaps achieved in both day-ahead and real-time market applications at the California ISO’s production sy stem.\n\nHere are the details: [https://ieee-pes.org/calendar/ieee-pes-liv e-online-evolution-of-short-term-unit-scheduling-solutions-in-power-system s-operations/](https://urldefense.com/v3/__https:/ieee-pes.org/calendar/ie ee-pes-live-online-evolution-of-short-term-unit-scheduling-solutions-in-po wer-systems-operations/__\;!!LFxIGwQ!222Ypzn-Mk1nWKO7i0zfc_ZKFEAcNHzJy95BO 4--5z7Xnqclu9fqXDogiwl_MECf67zSVcnYVnJO1UYs0_0V-bKua8uV$)\n\nSpeaker(s): D r. Khaled Abdul-Rahman\, \n\nVirtual: https://events.vtools.ieee.org/m/416 996 LOCATION:Virtual: https://events.vtools.ieee.org/m/416996 ORGANIZER:walmukdad@gmail.com SEQUENCE:21 SUMMARY:Evolution of Short Term Unit Scheduling Solutions in Power System O perations URL;VALUE=URI:https://events.vtools.ieee.org/m/416996 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="margin-bottom: 12 .0pt\;">Will provide a high level brief overview of the solutions and algo rithms evolved over the last several decades to solve the short term unit scheduling problem. The focus is on the practically most used solutions to power systems operations. The discussion will include priority merit list \, dynamic programming\, Linear Programming\, Lagrangian relaxation\, Augm ented Lagrangian relaxation\, and the game changer Mixed Integer Program ( MIP). The mathematical breakthroughs and efficient search algorithms used in recent MIP commercial solvers made MIP the algorithm of choice widely a dopted by the power systems industry to solve such highly complex\, non-co nvex\, and combinatorial optimization problem. The huge reduction in the M IP optimization solution time\, the ease of mathematical constraints model ing\, and the increased solution quality transformed the real-time applica tions and made it possible to model large number of complex resources&rsqu o\; types like combined cycle units\, startup times and cost\, transition time and cost\, dynamic ramp rates as functions of resources MW. These adv ances in MIP made it possible to also include unprecedented large set of c ross-resources and cross-time intervals coupling constraints such as trans mission\, and environment constraints in optimizing operations in day-ahea d and real-time applications.</p>\n<p><span style="font-size: 12.0pt\; fon t-family: 'Aptos'\,sans-serif\; mso-fareast-font-family: Aptos\; mso-farea st-theme-font: minor-latin\; mso-bidi-font-family: Aptos\; mso-ansi-langua ge: EN-US\; mso-fareast-language: EN-US\; mso-bidi-language: AR-SA\;">As i llustrative example\, the presentation will highlight the current large-sc ale mathematical MIP model sizes\, solution times\, and the optimal MIP in teger gaps achieved in both day-ahead and real-time market applications at the California ISO&rsquo\;s production system.<br style="mso-special-char acter: line-break\;"><!--[endif]--></span></p>\n<p><span style="font-size: 12.0pt\; font-family: 'Aptos'\,sans-serif\; mso-fareast-font-family: Apto s\; mso-fareast-theme-font: minor-latin\; mso-bidi-font-family: Aptos\; ms o-ansi-language: EN-US\; mso-fareast-language: EN-US\; mso-bidi-language: AR-SA\;">Here are the details: <a href="https://urldefense.com/v3/__https: /ieee-pes.org/calendar/ieee-pes-live-online-evolution-of-short-term-unit-s cheduling-solutions-in-power-systems-operations/__\;!!LFxIGwQ!222Ypzn-Mk1n WKO7i0zfc_ZKFEAcNHzJy95BO4--5z7Xnqclu9fqXDogiwl_MECf67zSVcnYVnJO1UYs0_0V-b Kua8uV$">https://ieee-pes.org/calendar/ieee-pes-live-online-evolution-of-s hort-term-unit-scheduling-solutions-in-power-systems-operations/</a></span ></p> END:VEVENT END:VCALENDAR