Innovative training techniques to account for power quality issues when deploying Distributed Energy Resources

Innovative training techniques to account for power quality issues when deploying Distributed Energy Resources Clémentine Coujard Athanase Vafeas Serge Galant TECHNOFI S.A. Sophia Antipolis, France ccoujard@symple.eu Raul Rodriguez LABEIN Bilbao, Spain rsergio@labein.es Math Bollen STRI AB Ludvika, Sweden math@stri.se Sébastien Grenard Tractebel Engineering Brussels, Belgium sebastien.grenard@tractebel. com Abstract Sizing and optimizing an investment in distributed energy resources (DER) must take into account power quality issues: it is then a matter of defining the right balance between the end-user s energy supply expectations and their financial capabilities to launch the investment. This requires a minimum understanding of power quality constraints during the DER unit optimization process: bridging the knowledge gaps between power quality experts and DER end-users relies on critical, complex technical and economical considerations. This paper argues that dedicated training is able to bridge such knowledge gaps: end-users will then feel more confident at taking optimal decisions when investing in DER units. It is the complexity of power quality issues that drove the development of innovative training sessions herein described: they lean on the coupling of experimental descriptions of current power quality problems faced by electrical network managers with learning by doing approaches. Key words: Training, Power quality, Distributed Energy Resources I. INTRODUCTION The concept of small electricity generation units at the enduser site is spreading over. This deployment faces technical and non-technical barriers, which are currently thoroughly investigated by the EU-DEEP project 1. Among the nontechnical barriers, a key issue is the strengthening of knowledge and skills of decision makers in Distributed Energy Resources investments. These issues include integration of distributed generation to the network, financial appraisal of an investment, structure of new electricity markets and regulations, as well as optimization of the DER system and related power quality issues in line with the customers needs. For more information about the EU-DEEP project the reader is referred to [1]. II. KNOWLEDGE GAPS ON POWER QUALITY ISSUES End-users willing to investigate investment opportunities in Distributed Energy Resources need to grasp, among other topics, some power quality fundamentals. Three key issues are at stake: The assessment of end-user power quality requirements: such needs may significantly vary according to the end-user s activity field and so does the economic impact of power quality disturbances. For instance, residential consumers may easily withstand some short power interruptions or variations, whereas commercial or industrial consumers whose 1 The EU-DEEP project is funded by the European Commission under contract N SES-CT-23-53516

activities and processes mostly rely on electronicsbased equipment - the banking sector for instance - will undergo significant equipment or data damage as well as income losses. Assessing the impact of power quality disturbanceson each consumer s activity, and therefore valuing its quality expectations, is an integral part of the design of an optimal DER solution. Potential power quality problems may arise when connecting DER units to the grid: when interconnected, the grid and the DER can interact with each other. Disturbances occurring on the grid may lead to tripping, disconnection or even damages of the DER units; conversely, a dysfunctional DER unit can impact the grid stability. Even in normal operation the DER unit may adversely impact power quality or reliability. An overall understanding of the system and of its technical barriers is necessary to ensure a proper optimization of a connected DER solution. DER optimization processes need to address both technical and economical issues: technical solutions ensure higher power quality, within higher capital and operation costs. Trade-off solutions must be found to minimize the cost of ownership of DER units. So far, apart from some commercial and most industrial customers, electricity end-users are quite unaware of their own needs in terms of quality of supply. They are even less informed on the key technical parameters that influence the value of potential DER investments. Moreover they will not devote much time to get the technical knowledge necessary to understand the physics of electrical systems. They therefore need practical examples, close to their own reality, in order to grasp the key features of their own consumption behavior and energy needs. They also require high level illustrations of the systemic dimension of networkconnected DER units and the related technical barriers that slow down deployment, in order to make the right trade-off between power quality expectations and economics. III. INNOVATIVE TRAININGS FOR ELECTRICITY END-USERS The solution investigated within the EU-DEEP European R&D project supported by the EC is the implementation of real power measurements at typical end-users sites, coupled with simulations of the behaviors of electrical systems where DER units are interconnected. More generally, the EU-DEEP trainings propose to DER end-users and investors an in-depth understanding of the interactions between new energy markets, DER technologies and evolving regulation schemes, relying on a learning by doing approach. Fig. 1 details the structure of the training in two main steps: a generic training session that enables trainees to learn the rules of the DER game; and a specific training session that allows trainees to face their real life issues, focusing on some of the most promising sectors for DER expansion. Within the specific training sessions, power quality issues are therefore addressed via real load features as a result of measurement campaigns, as well as dynamic simulations of DER-connected electrical systems. Generic training: 3 consecutive days LEARN THE RULES Knowledge about DER opportunities Keys to understand your consumption and define the needs DER can fulfil Tools to design and optimize DER solutions Tools for the financial evaluation of your investment Specific training: 3 days within two months PRACTICE IN YOUR OWN SECTOR Simulation tools to illustrate the key aspects of a DER project in your sector Real consumption data within your own segment Practice DER optimization on standard and real cases A complete DER integration and valuation approach Fig. 1, Organization of the training sessions. These two complementary approaches are very illustrative, since relying on real life data close to the trainees own cases, and on simulation tools that enable grasping electric system dynamics without entering into the detailed physics of the expected electrical transient phenomena. IV. MEASUREMENTS AT END-USERS SITES In order to approach the specificities of the electricity demands, power measurements have been performed at real life end-user sites with very different load profiles. Test campaigns were led in various commercial and residential segments throughout Europe: a hotel and a school in Greece, a university building and two apartments in Spain, an office building and an individual house in Sweden. During the campaigns, 3-phase rms voltages, current, harmonics, and power demand 1-second and 1-minute values were recorded for periods from 24 hours to three months depending on the sites. Such measurements illustrate the variety of electricity load shapes depending on the activity of the end-user, and depending on the time (weeks and week ends). Such a power measurement campaign used as a direct support to trainings gives an overview of all the considerations to be taken into account by the end-users with respect to power quality in DER. The novelty is the coverage in Europe of very different real customer situations. A typical customer will be able to recognize his own profile through the proposed portfolio of European cases. Some examples of measurement results are presented below.

A. Variations in Active Power The active power demand (energy demand) of a customer varies strongly with the time of day. Especially for small customers, large variations in active-power demand exist over a range of time scales. As an example, the variations in active power demand for a large hotel in Athens, Greece are shown in Fig. 2. The total power over the three phases is shown the oneweek measurement period (Friday through Friday). Each value corresponds to a one-minute average value. The daily variation is clearly visible; also is the power demand somewhat lower in the weekend than during weekdays. Active Power (kw) 6 5 4 3 2 1 21 22 23 24 25 26 27 28 29 :, July 26 Fig. 2, Variations in active power for a large hotel. Another example is shown in Fig. 3; it shows the variations in active power for a one-family individual house in Ludvika, in the middle of Sweden. During the measurement period the house was electrically heated, which explains the high active power demand. The large steps in active power correspond to the switching on and off of the heating. The peaks in active power correspond to the periods of domestic activity, early morning, late afternoon and evening, as well as the weekend. The pattern of load variations differs significantly from the pattern for the hotel. Active Power (kw) 18 16 14 12 1 8 6 4 2 9 1 11 12 13 14 15 16 17 : February 26 A third example is shown in Fig. 4: the variations in active power for an apartment in Valencia, Spain. Domestic activities take place during the whole day in the case. Active Power (W) 45 4 35 3 25 2 15 1 5 2 3 4 5 6 7 8 9 1 :, November 26 Fig. 4, Variations in active power for an apartment. During the measurements, the highest one-second average of the active-power demand was recorded for every one-minute interval next to the average value. The difference between the highest one-second value and the average value is an indicator for the size of the variations in active power demand at a time scale of seconds. This difference is shown in Fig. 5 for the same hotel as in Fig. 2. A DER unit supplying the load during island operation should be able to cope with these peaks in active power demand. For this hotel, the average power over the one-week period is 36 kw, whereas the highest 1-second value is equal to 618 kw, almost twice the average value. For reliable island operation, the DER unit should be rated at about twice the average power, or some electricity storage should be available in order to supply the needed amount of energy. Active power peak (kw) 8 7 6 5 4 3 2 1 : 4: 8: 12: 16: 2: : Time on 25 July 26 Fig. 5, Difference between highest one-second active power and average power per 1-minute interval for a large hotel. Fig. 3, Variations in active power for an individual house. B. Variations in Current Magnitude For the current magnitudes in each of the phases, the rms value over each one-minute interval was recorded, together

with the highest one-cycle (2-ms) value during the one-minute interval. The variations in one-minute value for the current magnitude are similar to the variations in active power as shown below. The variations in one-cycle maximum values of the current magnitude in one of the phases during the one-week measurement interval are shown in Fig. 6 for the same large hotel as before. The highest 1-cycle value measured is equal to 949 A, to be compared with the highest 1-minute value of 356 A. of the figure. The two clouds of points around the upper middle part of the figure relate to voltage drops caused by local load variations. These voltage drops are up to 7.8 V, about 3.5%. This is still within the acceptable range, but a weakening of the supply or island operation of the hotel with its on-site generation could result in unacceptable drops in voltage. 1 9 8 Maximum current (A) 7 6 5 4 3 2 1 21 22 23 24 25 26 27 28 29 :, July 26 Fig. 6, Highest one-cycle current per 1-minute interval for a large hotel. Similar patterns were visible for the other two phases. Statistics of the current variations in the three phases for this measurement site are shown in Table I. Table I STATISTICS ON VARIATIONS IN CURRENT MAGNITUDE FOR A LARGE HOTEL. Red phase Green phase Blue phase Average 356 A 714 A 761 A 95% of 1-minute values 464 A 92 A 951 A 99% of 1-minute value 564 A 187 A 1168 A Highest 1-minute value 637 A 129 A 1292 A Highest 1-cycle value 949 A 1698 A 1773 A C. Voltage and current variations In the same way as for the current, maximum and minimum one-cycle values were recorded for the voltage, next to the rms value over each one-minute interval. Short-duration rises in current are expected to lead to short-duration drops in voltage. But voltage drops may also be due to events outside of the local load. The difference between maximum and rms current (the curent peak ) has been ploted against the diference between rms and minimum voltage (the voltage drop ). The result is shown in Fig. 7 for the same large hotel as before. Each point represents a one-minute value, with different colors representing the three phases. For small drops and small peaks there is no clear correlation although there is a clear cutoff line at the upper side of the cloud of points towards the bottom left of the diagram. The points along the horizontal axis represent voltage drops that have their origin outside of the load. The highest voltage drop measured was 32.6 V, outside of the scale Fig. 7, Relation between voltage drops and peaks in current for a large hotel. The three phases are indicated by different colors and different markers. D. Rating of a DER unit The large difference between average power demand and peak demand was already pointed out earlier. This difference is very important in the design of the DER unit; it depends strongly on the type of customer. The results from our measurements at two different locations are shown in Table II. The table shows a number of statistical measures describing the load demand. Based on the type of application a different measure should be used to determine the rating (or sizing) of the DER unit. Table II DIFFERENT STATISTICAL MEASURES FOR DIMENSIONING A DER UNIT. Large hotel Apartment mean 36 kw 1%.5 kw 1 x 95%, 1 min 442 kw 123% 1.6 kw 3 x 99%, 1 min 528 kw 147% 2.7 kw 5 x max 1 min 59 kw 164% 4.2 kw 8 x max 1 sec 618 kw 172% 5.4 kw 11 x max 2-ms 1223 kva 34% 1.2 kva 2 x Sizing a unit based on the average load (36 kw for the hotel, 5 W for the apartment) will result in zero net energy use over a longer period. This does however not necessarily result in a zero electricity bill. Different rates may apply for generation and for consumption; the electricity price typically varies during the day; and the connection fee is normally based on peak current not on average active power. To be able to be self-supplying during price peaks or to operate in island during grid outages, a larger DER unit is needed. For the hotel an overrating between 25% and 7% is needed, depending on the reliability that is required. For the apartment and overrating

with a factor between 3 and 1 is needed. Note that a high overrating implies either that the unit is used inefficiently most of the time or that the customer has a large net export of electrical energy. V. SIMULATION OF ELECTRICAL SYSTEMS WITH DER UNITS Two main reasons are usually the main trigger of the investment in DER: Investors are willing to reduce their electric energy bought to the utility by producing electrical energy onsite (and even selling back surplus electricity) Investors are willing to improve the reliability of supply by running their DER in islanded mode whenever the grid is not capable of providing electric power to their site. In the first case, the investment decision is based on the tariff difference between the contract of the electricity supplier and the cost of providing electricity on site. The second case is more critical in terms of power quality; therefore its illustration is the main purpose of the dynamic simulations used for the training. The lower inertia and short-circuit capacity of the islanded system compared to the interconnected system leads to greater variations in voltage and frequency. Therefore, the extra security through islanding can only be achieved with sufficient installed capacity and appropriate protection and control systems, which all add an extra cost to the initial investment. The key challenges are to handle the transition to the island operation following a system disturbance, and to cope with load variations once the system is islanded. As such, the main message delivered during the training is to demonstrate that having local generation capacity equal to load (or critical load) in the islanded system is not sufficient. The sizing of the generator must enable the islanded network to sustain the voltage and frequency transients. Therefore, dynamic simulations of electrical systems involving DER units have been developed to illustrate transients in systems where DER is operating in islanded mode. They illustrate the impact of the size of DER and of the protection schemes operating-time on the power quality in the electrical system considered. Four different models are developed in order to cover a large range of sizes of sites for the commercial and residential segments. For each of them the three following simulations are carried out for illustration purpose: Dynamic simulation of the site connected to the grid; Dynamic simulation to illustrate the process of transition from the grid-connected operation to the island operation; Dynamic simulation of load variations in islanded mode. Fig. 5 and Fig/ 6 present the cases discussed above. On Fig. 5, the voltage in the system is described for two different timing for the disconnection from the grid. Having a protection operating time of 15ms instead of 25ms to detect a fault in the grid and disconnect the site from the grid, lessens the voltage transient which reduces the corresponding constraints on the system and on the DER. The frequency in the system is depicted on Fig. 6 where two different sizes of DER (1kVA and 2kVA) were considered. As one can notice, the higher the DER capacity (i.e. the higher the investment), the lower the frequency transients in the system following the transition to islanded operation and load variations (in this case an induction motor shut down and start up were simulated). ut he art-up down grid 1..5 Fault in the grid Voltage (pu) in the islanded system. 1 2 3 4 5 Protection operating time: 25ms Protection operating time: 125ms Fig. 8, Illustration of dynamic results: Impact of protection scheme operation time on voltage transient clearance. 52 51 5 49 48 Fault in the grid Frequency (Hz) in the islanded system Motor shut down Motor start-up 47 s 1 2 3 4 5 DER capacity: 1kVA DER capacity: 2kVA Fig. 9, Illustration of dynamic results: Impact DER size on frequency transient clearance. Such simulations illustrate clearly the trade-off to be made between: Low investment choices: slow disconnection from the main grid, and DER size with minimum capacity to supply the site s critical load s

Quality choices: protection schemes leading to faster disconnections of the island from the main grid, and DER size with higher capacity improving the stability and reliability of the island. The above power quality trade-of wil secure end-user s activity (no income loss or technical problems related to power quality defaults), but will trigger additional investments. VI. TRAINING IMPACTS At the end of such training, trainees have gained the minimum knowledge and practice to assess DER investment opportunities considering the power quality dimension. They become able to avoid inappropriate DER solutions to meet their power demand profiles. Through illustrative power measurements, the trainees understand the critical points of their own consumption patterns and are therefore able to define their power quality expectations. They can then give an approximate economic value to their power quality needs in relation with their activity. The electrical system simulations allow illustrating the trade-offs to be made between the level of power quality to be implemented and the level of investment costs. This sets up an objective framework for the trainees to build the specifications and assess their future DER investments. VII. CONCLUSIONS Within the EU-DEEP research & development project, a first complete prototype of this innovative training was developed on one real case devoted to office building application, and is now duplicated to other activity segments in commercial and residential sectors. Most power measurement results have been made available and electrical simulations are under final development. The first training sessions targeting the segments of commercial buildings and residential housing will be programmed in early 28. Training sessions will be organized over three non-consecutive days enabling the trainees to work on their own real case between each session, in line with a learning by doing training approach. ACKNOWLEDGMENT Thanks are due to Ledra Mariott Hotel in Athens, National Technical University Athens, Polytechnical University Valencia, Iberdrola Distribución - Measurements department, EPA Attiki in Athens, Zaira Trivyza, K. Bañuelos and Mats Häger for their contribution and permission to allow measurements at their premises. [1] www.eu-deep.com REFERENCES