Integrid - Bridging the Gap

39 Table 4.11 - HLUC9 KPIs and Description KPI Result Description Ratio between minimum and maximum electricity demand within a day With PV: • Weekdays: 1% • Weekends: -1% • Weighted avg.: 1% Without PV: • Weekdays: 12% • Weekends: 16% • Weighted avg.: 13% With this KPI, it is possible to assess the difference in electricity demand before and after the installation of smart appliances and PV. As such, the difference between the average of minimum and maximum electricity demand one month after equipment installation is compared to the average of minimum and maximum electricity demand of the equivalent period. This KPI seeks to evaluate whether the flattening of the load curve in the presence of HEMS allows load redistribution to be optimised over the day, reducing consumption in peak hours. Peak demand reduction ratio With PV: • Weighted avg.: -4% Without PV: • Weighted avg.: 12% With the purpose of understanding the impact of the project on the household consumption profile, this KPI evaluates how peak demand is affected by the installation of smart home appliances and a PV panel, managed by HEMS. When the value of the formula is negative, this indicates a successful reduction in peak demand with the new household topology, thus promoting higher efficiency. Self-Consumption • Weekends: 57% • Weighted avg.: 57% This KPI evaluates the percentage of energy, produced by the PV system, that is effectively consumed behind the meter and, in this way, not injected into the distribution grid. As HEMS seeks to maximize self-consumption and self-sufficiency, the KPI result should ideally be equal to 100%. collected during the project and existing historical data; ii) Optimization of home energy by managing the controllable devices in an automated fashion and according to user comfort preferences; iii) Interconnection between users and marketplace for flexibility trading. In Table 4.11, the results of the KPIs are shown for the period between December 2018 and September 2020, broken down into customers with/without solar PV. The COVID-19 pandemic has had a huge impact on the following results as all of them are calculated using metering data collected during the same period last year, before the project. In this new scenario it is very difficult to measure the real impact of HEMS in reducing peak load, flattening the load diagram and maximizing self-consumption because domestic electricity use also changed , but not as a consequence of the project. It was clear that after February, KPIs changed significantly due to external factors (lockdown, telework). Nevertheless, the main conclusions of the analysis of the KPI results are: Peak Load Reduction – a clear reduction was noticed in the peak load values but only for participants with solar PV panels. After the lockdown period (May), the positive effect remains for the same group of participants; Between Min and Max Consumption – the results of this KPI are the same as before, much because average daily minimum power did not change significantly when compared to the same period last year. It can be concluded that without customer engagement with HEMS, this system on its own does not optimize load distribution over the day; Self-Consumption – On average, 57%of the PV energy produced was consumed behind the meter. In April there was an increase of ~10% that can be tied to the fact that customers were at home during the solar period. Results from HLUC10 - Aggregating and communicating flexibility fromMV consumers In HLUC10, EDP C rehearsed the use of aggregated building flexibility on two MV grid connected buildings. Energy market participation was through bids simulation for the Tertiary Reserve Market, anticipating an expected opportunity for DSM in Portugal in the near future.