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:20170523T041611Z UID:C2AE5DBE-3F6D-11E7-8752-0050568D2FB3 DTSTART;TZID=Australia/Brisbane:20170607T164500 DTEND;TZID=Australia/Brisbane:20170607T181500 DESCRIPTION:Community battery systems are shared by a small group of energy consumers and used to provide storage services. These may include the red uction of peak power demands\, energy arbitrage and the control of network voltages. A battery can provide voltage support during times of high load or restrain voltage rises during times of high generation from embedded g enerators such as roof top solar systems. A community battery may be owned and operated by a customer collective\, a network operator or by a third party such as a storage service aggregator. Batteries have significant cap ital and operating costs. The economic daily operation of energy storages is readily solvable using a range of optimisation methods. For any real ti me application the optimisation will rely completely upon daily forecasts of the aggregated customer loads and any local generation. The optimum sol ution will contain a strong periodic component which reflects the daily de mand profiles of customers and the diurnal variation in solar generation. A feature of community battery storage systems is the relatively small num ber of consumers which often falls into the range of 10 to 100. The load d iversity is higher than is observed in large electricity markets. Likewise the numbers of embedded generators is small and the generation is not geo graphically distributed to the extent that may occur in a large power syst em. The effect of spatial smoothing on reducing the variability of embedde d local generation is lower. This talk presents some approaches to battery management. The study presented in talk is based upon data recorded withi n the Perth Solar City high penetration PV field trials. The trial studied 77 consumers with 29 roof top solar systems that were connected in one lo w voltage (LV) network. Data was available from consumer smart meters and a data logger connected to the LV network supply transformer.\n\nSpeaker(s ): Peter Wolfs\, \, Peter Wolfs\, \n\nAgenda: \n4:45 - 5:00 pm - Refreshme nt\n\n5:00 - 5:45 pm - Talk\n\n5:45 - 6:00 pm - Discussion\n\n6:00 pm - Aw arding PES Outstanding Engineer plaque\n\nRoom: 0.06D\, Bldg: N25\, 170 Ke ssels Rd\, Nathan QLD 4111\, Brisbane\, Queensland\, Australia\, 4111 LOCATION:Room: 0.06D\, Bldg: N25\, 170 Kessels Rd\, Nathan QLD 4111\, Brisb ane\, Queensland\, Australia\, 4111 ORGANIZER:chandima@ieee.org SEQUENCE:2 SUMMARY:Energy Forecasting for the Diurnal Management of Community Battery Systems URL;VALUE=URI:https://events.vtools.ieee.org/m/45656 X-ALT-DESC:Description: <br /><p>Community battery systems are shared by a small group of energy consumers and used to provide storage services. Thes e may include the reduction of peak power demands\, energy arbitrage and t he control of network voltages. A battery can provide voltage support duri ng times of high load or restrain voltage rises during times of high gener ation from embedded generators such as roof top solar systems. A community battery may be owned and operated by a customer collective\, a network op erator or by a third party such as a storage service aggregator. Batteries have significant capital and operating costs. The economic daily operatio n of energy storages is readily solvable using a range of optimisation met hods. For any real time application the optimisation will rely completely upon daily forecasts of the aggregated customer loads and any local genera tion. The optimum solution will contain a strong periodic component which reflects the daily demand profiles of customers and the diurnal variation in solar generation. A feature of community battery storage systems is the relatively small number of consumers which often falls into the range of 10 to 100. The load diversity is higher than is observed in large electric ity markets. Likewise the numbers of embedded generators is small and the generation is not geographically distributed to the extent that may occur in a large power system. The effect of spatial smoothing on reducing the v ariability of embedded local generation is lower. This talk presents some approaches to battery management. The study presented in talk is based upo n data recorded within the Perth Solar City high penetration PV field tria ls. The trial studied 77 consumers with 29 roof top solar systems that wer e connected in one low voltage (LV) network. Data was available from consu mer smart meters and a data logger connected to the LV network supply tran sformer.&nbsp\;</p><br /><br />Agenda: <br /><p>4:45 - 5:00 pm - Refreshme nt</p>\n<p>5:00 - 5:45 pm - Talk</p>\n<p>5:45 - 6:00 pm - Discussion</p>\n <p>6:00 pm - Awarding PES Outstanding Engineer plaque</p> END:VEVENT END:VCALENDAR