Integration of solar pv systems into grid: Impact assessment and solutions

ehaviour of PV systems in a short circuit condition, a LV 
distribution network is used (Fig. 27). This network is powered by a 400 kVA 
(20/0.4 kV) distribution transformer. This network comprises 2 feeders with 
underground cables of 240 mm2. Each feeder has a FD 400 A fuse. The distance 
between the customers is 10 or 20 m. The the customers are well distributed among the 
three phases. Each connection has an AD 90 A fuse. 
It is assumed that there are three 3 kWp PV systems connected on three phases to 
nodes 21, 23 and 24, respectively. The anti-islanding protection of PV systems is based 
on the voltage and frequency criterion according to DIN VDE 0126-1-1. Different types 
of short circuits (single-phase, phase-phase, three-phase) are created at the different 
points of the network on the two feeders. The behaviours of PV inverters in the event of 
46 | HỘI NGHỊ KHOA HỌC VÀ CÔNG NGHỆ ĐIỆN LỰC TOÀN QUỐC 2017 
a short circuit are observed. In this section, we present only the behaviors of PV 
inverters in the case of a single-phase short-circuit. 
Fig. 27: LV distributed network with PV systems and protection systems 
Fig. 28: Behaviour of PV systems in fault phase and non-fault phase during a sing phase short circuit 
BÁO CÁO CHUNG | 47 
A single-phase short-circuit appears at t = 1.0 s on phase a at node 7. The short-
circuit current seen by the fuse FD1 reaches 7 kA (Fig 28a). This fuse melts at t = 1.41 s. 
During the short circuit, the voltage of the PV inverter connected to the faulty phase (at 
node 21) decreases to 0.52 pu (Fig. 28c). This PV inverter is disconnected 200 ms after 
the short circuit (t = 1.2 s). During the short circuit, the current of this inverter increases 
slightly but does not exceed 110% (Fig. 28d). 
Fig. 28e and Fig. 28f show the power and voltage variations of the PV inverter 
connected to the non-fault phase (phase b to node N23). This inverter maintains the 
connection during and after the fault. This is identical with the PV inverter connected on 
phase c to node N24. 
We thus show the support capacity to disturbance for the inverters on the non-
fault phases. 
Future power systems with high penetration of photovoltaic (PV) systems could 
be severely affected in a power quality disturbance, generation loss and stability 
problem if several of PV systems are tripping. Among power quality disturbances, 
voltage sag is considered as the most serious which can cause the disconnection of a 
significant amount of PV systems. These disconnections are sometimes unnecessary, 
particularly when the fault is not situated on the same feeder of PV systems (adjacent 
feeder). Therefore, this part focuses on voltage sags caused by short circuits. This work 
is to study behaviors of grid-connected PV systems facing voltage sags by taking into 
account the real urban network (MV network) protections. From simulations, 
unnecessary trip cases of PV systems are then identified. Finally, a solution by using the 
voltage-times characteristic for PV system is proposed (Fig. 29). This solution permits 
to avoid unnecessary trip of PV systems in case of a short circuit on the adjacent feeder, 
outside of PV zones. Nevertheless, in case of a short circuit in their zone, PV systems 
are disconnected. A verification of the system operation with proposed solution is also 
carried out. 
Fig. 29: PV voltage in comparison with the voltage-time characteristic for a fault on LV adjacent feeder 
(outside of the PV zone) 
48 | HỘI NGHỊ KHOA HỌC VÀ CÔNG NGHỆ ĐIỆN LỰC TOÀN QUỐC 2017 
VIII. STRATEGIES FOR BESS MANAGEMENT IN PHOTOVOLTAIC APPLICATIONS 
High capital investment cost for batteries constitute a major obstacle to the 
widespread deployment of battery energy storage systems (BESSs) as a tool to support 
the integration of renewable energy sources (RES) into the electricity grid. BESSs are 
already operated in commercial MW-scaled photovoltaic (PV) installations to facilitate 
power production levelling and participation in auxiliary services, such as frequency 
and voltage control. The optimization of dispatch schedules has been employed in the 
past to aid the sizing of BESS and drive down capital expenditures by limiting the 
installed battery capacity to the minimum required for the application. In this work, an 
optimized operation strategy is used to reduce replacement costs for the batteries by 
adapting the state-of-charge and power solicitation to achieve minimized aging. To this 
end, a simplified model for both calendar and cycle aging of Li-ion batteries is 
integrated into a mixed-integer linear programming algorithm. Results from a 
simulation using typical specifications for a BESS operated in a PV power plant in 
French overseas regions are presented and discussed. 
Fig. 30: Architecture of photovoltaic power plant with two parallel battery energy storage systems. 
Fig. 31: Plant production schedule, PV generation and BESS solicitation resulting from optimization. 
Top: without aging cost, bottom: with aging cost (average aging approach) 
BÁO CÁO CHUNG | 49 
Fig. 32: One-day production schedule of two ESSs and a PV power plant in a VPP, 
as well as net market bids in the day-ahead energy (Market) and tertiary reserve market (Res). 
Top: current German market rules, bottom: quarter-hourly energy market contracts 
and relaxed minimal reserve amount constraint. 
IX. STABILITY IN AN ISLAND NETWORK WITH HIGH RES INTEGRATION 
In a context where renewable energies from both wind and solar origin have low 
predictability, low controllability and strong variability, their massive integration into 
power systems may cause instabilities for these grids. The use of storage energy systems 
is a promising solution for solving such problems. In the present part, we focus on 
flywheel energy storage system (FESS) associated to photovoltaic power generation 
(PV). The FESS is then connected to a grid simulated by real time simulator in order to 
test its ability for grid ancillary service: voltage, frequency regulation and PV power 
smoothing. According to the inertia of the grid, the flywheel system is more or less able 
to smooth the frequency, the voltage and the PV production. 
Two application of FESS are studied: 
 PV power smoothing with three control methods (Fig. 33), 
 Frequency control (Fig. 34). 
Results obtained for these cases shows efficiency evaluation of the proposed 
solutions. 
This is in framework of smart grid in Corsia island (France). 
50 | HỘI NGHỊ KHOA HỌC VÀ CÔNG NGHỆ ĐIỆN LỰC TOÀN QUỐC 2017 
Fig. 33: Results of the PV smoothing with different control methods. PV power and PV variation are in 
red solid line. Blue solid lines represent data from the 2-D supervisor, dashed green lines data from 
the 3-D supervisor with rate limiter and dotted black lines data from the 3-D supervisor with LPF. 
From the top graph to the bottom graph: the first graph gives the smoothed powers injected to the 
grid, PV power (red) and flywheel powers; the second the speeds of the flywheel; the 3rd energies 
lost by the flywheel and the last graph the power variations of each control method compared with 
the PV power variation (red) 
Fig. 34: Frequency variation with and without frequency control (a) and Flywheel Power (b) in case of 
change of PV production 
This is in framework of smart grid in Guadeloupe island, France (Fig. 35). The 
high penetration of RES into a isolated grid can provide the stability problem. 
Fig. 36 shows the frequency variations in Guadeloupe with the penetration rate of 
RES (PV) about 2, 32, 50 and 72%, respectivelly in case of short-circuit without or with 
the intelligent protection strategies. Without solution this grid is instable and the 
maximal penetration rate of RES (PV) in this grid is limited about 30%. 
In order to increase the penetration rate of RES (PV), several intelligent solutions 
for control and protection strategies are proposed. With the proposed solutions this grid 
is always stable for different penetration rates, even with 72% of RES (PV) (Figs 36 
to 38). 
0 250 500 750 1000 1250 1500 1750 2000 2250 2500 2750 3000
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BÁO CÁO CHUNG | 51 
Fig. 35: Isolated grid of Guadeloupe 
Fig. 36: Frequency variation for 3, 32, 50 and 72% of RES (PV) penetration 
without and with proposed solutions 
Fig. 37: Voltage variation for 3, 32, 50 and 72% of RES (PV) penetration without 
and with proposed solutions 
52 | HỘI NGHỊ KHOA HỌC VÀ CÔNG NGHỆ ĐIỆN LỰC TOÀN QUỐC 2017 
Fig. 38: Rotor angle variation for 3, 32, 50 and 72% of RES (PV) penetration without and with proposed 
solutions 
X. CONCLUSIONS 
The integration of variable RES (PV systems) into electrical grids is limited 
because of their intermittences, fast power variations, highly dependence on 
meteorology and low inertia. In this paper, the forecasting, the monitoring of solar PV 
power have been investigated. Impacts of PV system integration in grid operation have 
been also analyzed. Several solutions in order to reduce these impacts, to maximize the 
ancillary services contributed by PV systems have been proposed via different projects. 
Intelligent control and energy management have been developed in order to minimize 
operation cost and to maximize the RES penetration rate into grid. 
REFERENCES 
[1] https://en.wikipedia.org/wiki/Solar_power_by_country 
[2] T. Tran-Quoc, X. Le Pivert, J. Merten, “Analysis of Photovoltaic Generation Impacts on 
Distribution Networks”; Conférence PVSEC - The 27th European Photovoltaic Solar Energy 
Conference and Exhibition, 24 - 28th September 2012, Frankfurt (DE). 
[3] Cédric Abbezzot, Tuan Tran Quoc, “Flywheel Energy Storage system used in a Photovoltaic 
Power Generation System”, 3rd International Conference on Energy Process Engineering 
(ICEPE 2013), Franfurk, Germany, 4-6th june, 2013. 
[4] NA Luu, T. Tran-Quoc, “Optimal energy management for an island microgrid by using 
Dynamic programming method”; Conference IEEE/Powertech, 29th June – 2nd july 2015, 
Eindhoven, Holand. 
BÁO CÁO CHUNG | 53 
[5] E. Krüger and Q. T. Tran, "Minimal aging operating strategies for battery energy storage 
systems in photovoltaic applications", IEEE-ISGT, Innovative Smart Grid Technologies 
Conference, 9-12 October 2016, Ljubljana, Slovenia. 
[6] Q. T. Tran, NA Luu, "Optimal Energy Management Strategies of Microgrids", The 2016 IEEE 
Symposium– Special Session: Intelligent Management of Micro Grids and Buildings (IEEE SSCI 
- CIASG 2016) – 6-9 december 2016 Athens, Geece. 
Ph.D. thesis 
T1. Guillaume RAMI, "Adaptive voltage control for distributed generations connected to 
distribution networks", PhD thesis prepared at the Grenoble-INP, Defended on 9 November 
2006. 
T2. Thanh Luong LE “Detection of instability in grid with high RES penetration”, PhD thesis 
prepared at the Grenoble-INP, Defended on 22 January 2008. 
T3. Thi Minh Chau LE, "Coupling Photovoltaic inverters to the network, aspects of control and 
support capacity for disturbances", PhD thesis prepared at the Grenoble-INP, Defended on 
25 January 2012. 
T4. Van Linh NGUYEN, "Coupling photovoltaic systems and electric vehicles to the grid: Problems 
and solutions"; PhD Thesis prepared at the Grenoble-INP and CEA-INES, Defended on 1st 
October 2014. 
T5. Cedric ABBEZZOT, "Flywheel energy storage system coupled to the photovoltaic generator 
and controlled by a real-time simulator"; PhD Thesis prepared at the CEA-INES, Defended on 
15 December 2014. 
T6. Ngoc An LUU, "Strategies of control and management for microgrids", PhD Thesis prepared 
at the CEA-INES and G-INP, Defended on 18 December 2014. 
T7. Eiko KRUGER, "Development of algorithms for optimal management of energy storage 
systems based on adaptive models", PhD Thesis prepared at the CEA-INES, Defended on 21 
November 2016. 
T8. GABIN A. KOUCOI, "Energy Management in PV/Diesel hybrid system for isolated and rural 
zones: optimization and experimentation”, PhD Thesis prepared at the CEA-INES and 
University of Burkina Faso, Defended on 28 February 2017. 
T9. Elvira AMICARELLI, "Management strategy for power grids with a high rate of distributed 
renewable production", PhD Thesis prepared at the CEA-INES, Defended on 16 October 2017. 
T10. Hélène CLEMOT, "Strategies for optimal management of marine wave resources", PhD 
Thesis prepared at the CEA-INES and ECN, Defended in 2017. 
T11. Tung Lam NGUYEN, "Smart control strategies in Microgrids with Multi Agent Systems", PhD 
Thesis prepared at the CEA-INES and G-INP. 
T12. Karla SOUSA, "Stability in large network with high RES penetration”. 
T13. Laurène PARENT, "Primary and secondary reserve in large network with high RES 
penetration". 
T14. Anthony ROY, "Management of an island grid in ocean (Marine+PV+wind+storage)". 
T15. Tran The HOANG, "Smart protection strategies in Microgrid". 
T16. Tai LE, "New Architecture of PV power plants". 
T17. A. Arief, “Self-consumption and ancillary services”. 
T18. I. Karray, “Stability and HVDC solution”. 
54 | HỘI NGHỊ KHOA HỌC VÀ CÔNG NGHỆ ĐIỆN LỰC TOÀN QUỐC 2017 
Several Projects 
[P1] GREENLYS: Smart-grid demonstration. 
[P2] REFLEXE: Smart-grid demonstration at the south-east of France. 
[P3] PARADISE (ANR PROGELEC Project ID: ANR-13-PRGE-0007): high penetration of renewable 
energy resources into grid with DS. 
[P4] ERIGRID (H2020, European project ID: 654113) European Research Infrastructure supporting 
Smart Grid Systems Technology Development, Validation and Roll Out. 
[P5] SEAS (Call 7 ITEA2, European project No. 1204) Smart Energy Aware Systems. 
[P6] UNITED-GRID (H2020, European Project ID: 314175): Autonomous Management System 
Developed for Building and District Levels. 
[P7] M2M GRID (ERA-NET, European Project ID: 82136): From micro to Mega GRID: Integration 
approach for the new generation of smart grids. 
[P8] PPInterop (Carnot project): Interoperability between two platforms: PRISME-PREDIS. 
[P9] FENIX (European project) Virtual power plants. 
[P10] DERri (European project No.: 228449) Tools and methodologies to perform steady-state, 
dynamic and real-time simulation of DER and power systems –Hardware Interfaces.