Integrid - Bridging the Gap

36 when and where needed, based on flexibility needs for operational planning and real-time operation. To achieve this, the DSO would compute the flexibility needs and publish them through the grid-market hub. Qualified flexibility providers/operators would submit the information on their available flexibility for the desired timeframe to identify the most efficient decisions for the series of activated resources. Alternatively, in the event that the DSO identified an imminent risk to network security, flexibilities can be directly activated by the DSO through LV smart meters to temporarily reduce LV user demand. KPI calculation The following metrics were then calculated as a result of the HLUC07 demonstration. Table 4.9 shows the KPI results together with a brief description. This HLUC07 allowed us to observe and pre-qualify potential flexibility providers at a distribution level and to assess information on available flexibilities and respective updates. It was possible to define, sign and manage flexibility contracts with providers as well as manage the exchange of information between the DSO and other stakeholders for the provision of non-frequency ancillary services at a distribution level. Results from HLUC08 - Manage internal process flexibility to optimize energy consumption based on market-driven mechanisms and system operator requests Energy consumption optimization – p-optimizer The first step was to develop a data-driven control to optimize the energy consumption of wastewater pumping stations by optimally defining the operating set-point for each variable-frequency pump unit. After developing the Data-Driven Predictive control framework, it was necessary to integrate into WRRF operation. The p-Optimizer controller was installed (software p-optimizer) on a personal computer which was then put in to communication with theWRRF PLC. As this type of automatic control is new toWRRF and process control is very demanding and there is considerable pressure to guarantee the quality of wastewater, it was decided that this new controller would be performed semi-automatically, i.e. data exchange and calculations were carried out automatically, but this “mode” was activated manually by the control room operator. Therefore, it was also necessary to implement a number of changes to SCADA, such as creating a new menu for p-optimizer activation (Figure 4.16). To monitor the performance of this new controller, two key performance indicators (KPI) were defined: specific energy consumption (kWh/m3) and energy peak demand (kW). Table 4.9 - HLUC7 KPIs and Description KPI Result Description Amount of flexibility, measured in kW, the DSO contracts for operational purposes: cVPP 4689 kW -10650 kW tVPP 788 kW -8200 kW Amount of flexibility, presumably measured in kW, the DSO contracts for operational purposes. This may require introducing a differentiation per type of contract, timeframe, location and/or voltage level. Number of flexibility providers registered in flexibility service cVPP 19 tVPP: 10 Share of potential flexibility providers that comply with requirements and offer flexibility through the grid-market hub. Locational granularity should be defined. Ratio of flexibility providers that respond within the 15-min activation timeframe cVPP 65% tVPP: 40% The time it takes for a flexibility operator to respond to the DSO request. This KPI is an indication of the existence of suitable technology. Ratio of flexibility providers that respond within the 60-min activation timeframe cVPP 32% tVPP: 60% The time it takes for a flexibility operator to respond to the DSO request. This KPI is an indication of the existence of suitable technology. Amount of flexibility contracted and activated according to different parameters positive 40% negative 18% Share of the flexibility that has been previously contracted and is actually activated. This may require introducing a differentiation per type of contract, timeframe, location and/or voltage level.