Multi-Stage Operation Optimization of PV-Rich Low-Voltage Distribution Networks
Abstract
:1. Introduction
- A proposed time series MINLP OPF-based model that coordinates conventional and cutting-edge control mechanisms in the ADN. The focus is on the existing network components and inverter-based energy resources. The model is developed to minimize two of the most common problems for DSO caused by the impact of high PV integration—voltage violations and power losses. The multi-stage optimization is introduced and performed for different time horizons.
- Since the model is MINLP without approximations and represents the most accurate and hardest-to-solve problem, a co-simulation optimization framework is proposed and used to maintain the originality of the problem. The power flow system analyzer is co-simulated with the CI optimization method. The used CI optimization method in this paper is PSO. This approach enables a full unbalanced AC power flow analysis and enhances the efficiency, accuracy and reliability of the model and obtained solutions.
- A solar irradiance profile represents real-life data obtained by one of the author’s measurements.
2. Proposed Multi-Stage Control Scheme and OPF Formulation
2.1. OPF Problem Formulation
- —active power losses in time t;
- —reactive power losses in time t.
- —active power at bus i in time t;
- —reactive power at bus i in time t;
- —voltage magnitude at bus i in time t;
- —voltage magnitude at bus k in time t;
- — element of bus admittance matrix ;
- —voltage phase angle at ith bus in time t;
- —voltage phase angle at kth bus in time t;
- —phase angle of th element of bus admittance matrix .
- —apparent power of PV in time t;
- —active power of PV in time t;
- —reactive power of PV in time t.
- —minimal transformer tap position;
- —maximum transformer tap position;
- —transformer tap position in time t.
- —current tap position;
- —previous tap position;
- —apparent power of PV in time t;
- —active power of PV in time t;
- —reactive power of PV in time t.
2.2. General Co-Simulation Optimization Description
3. Test Network Model, Case Study and Optimization Settings Description
3.1. Test Network Model
3.2. Case Study Description
3.3. Optimization Settings
4. Results
4.1. Voltage Values
4.1.1. Base Case
4.1.2. Case Study 1
4.1.3. Case Study 2
4.1.4. Case Study 3
4.2. Losses
4.3. Performances
4.4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
RES | Renewable energy sources |
DN | Distribution networks |
DSO | Distribution system operator |
OLTC | On load tap changer |
CB | Capacitor bank |
VR | Voltage regulator |
ADN | Active distribution network |
APC | Active power curtailment |
RPC | Reactive power control |
BESS | Battery energy storage system |
MINLP | Mixed integer nonlinear programming |
NSGA—II | Non-dominated sorting genetic algorithm—II |
MISOCP | Mixed integer second-order cone programming |
DG | Distributed generation |
WT | Wind turbine |
SQP | Sequential quadratic programming |
SOCP | Second-order cone programming |
PSO | Particle swarm optimization |
CI | Computational intelligence |
LVDF | Low voltage distribution feeder |
FACTS | Flexible AC transmission system |
References
- Cortés, A.; Mazón, J.; Merino, J. Strategy of management of storage systems integrated with photovoltaic systems for mitigating the impact on LV distribution network. Int. J. Electr. Power Energy Syst. 2018, 103, 470–482. [Google Scholar] [CrossRef]
- Ivas, M.; Marušić, A.; Havelka, J.G.; Kuzle, I. P-Q capability chart analysis of multi-inverter photovoltaic power plant connected to medium voltage grid. Int. J. Electr. Power Energy Syst. 2020, 116, 105521. [Google Scholar] [CrossRef]
- Karimi, M.; Mokhlis, H.; Naidu, K.; Uddin, S.; Bakar, A.H. Photovoltaic penetration issues and impacts in distribution network - A review. Renew. Sustain. Energy Rev. 2016, 53, 594–605. [Google Scholar] [CrossRef]
- Kraiczy, M.; Stetz, T.; Braun, M. Parallel operation of transformers with on load tap changer and photovoltaic systems with reactive power control. IEEE Trans. Smart Grid 2018, 9, 6419–6428. [Google Scholar] [CrossRef]
- Pamshetti, V.B.; Singh, S.P. Optimal coordination of PV smart inverter and traditional volt-VAR control devices for energy cost savings and voltage regulation. Int. Trans. Electr. Energy Syst. 2019, 29, e12042. [Google Scholar] [CrossRef]
- Shailendra, S.; Pamshetti, V.B.; Thakur, A.K.; Singh, S.P. Multistage multiobjective Volt/VAR control for smart grid-enabled CVR with solar PV penetration. IEEE Syst. J. 2020, 15, 2767–2778. [Google Scholar]
- Dubravac, M.; Fekete, K.; Topić, D.; Barukčić, M. Voltage Optimization in PV-Rich Distribution Networks—A Review. Appl. Sci. 2022, 12, 12426. [Google Scholar] [CrossRef]
- Havrlik, M.; Libra, M.; Poulek, V.; Kourim, P. Analysis of Output Signal Distortion of Galvanic Isolation Circuits for Monitoring the Mains Voltage Waveform. Sensors 2022, 22, 7769. [Google Scholar] [CrossRef]
- Lamedica, R.; Ruvio, A.; Ribeiro, P.F.; Regoli, M. A Simulink model to assess harmonic distortion in MV/LV distribution networks with time-varying non linear loads. Simul. Model. Pract. Theory 2019, 90, 64–80. [Google Scholar] [CrossRef]
- Ma, W.; Wang, W.; Chen, Z.; Hu, R. A centralized voltage regulation method for distribution networks containing high penetrations of photovoltaic power. Int. J. Electr. Power Energy Syst. 2021, 129, 106852. [Google Scholar] [CrossRef]
- Ji, H.; Wang, C.; Li, P.; Zhao, J.; Song, G.; Ding, F.; Wu, J. A centralized-based method to determine the local voltage control strategies of distributed generator operation in active distribution networks. Appl. Energy 2018, 228, 2024–2036. [Google Scholar] [CrossRef]
- Jin, X.; Moradi, Z.; Rashidi, R. Optimal Operation of Distributed Generations in Four-Wire Unbalanced Distribution Systems considering Different Models of Loads. Int. Trans. Electr. Energy Syst. 2023, 2023, 8763116. [Google Scholar] [CrossRef]
- Zhang, Z.; da Silva, F.F.; Guo, Y.; Bak, C.L.; Chen, Z. Double-layer stochastic model predictive voltage control in active distribution networks with high penetration of renewables. Appl. Energy 2021, 302, 117530. [Google Scholar] [CrossRef]
- Li, H.; Liu, W.; Yu, L. Centralized-local PV voltage control considering opportunity constraint of short-term fluctuation. Glob. Energy Interconnect. 2023, 6, 81–91. [Google Scholar] [CrossRef]
- Wagle, R.; Sharma, P.; Sharma, C.; Amin, M. Optimal power flow based coordinated reactive and active power control to mitigate voltage violations in smart inverter enriched distribution network. Int. J. Green Energy 2023, 21, 359–375. [Google Scholar] [CrossRef]
- Su, X.; Masoum, M.A.; Wolfs, P.J. Optimal PV inverter reactive power control and real power curtailment to improve performance of unbalanced four-wire LV distribution networks. IEEE Trans. Sustain. Energy 2014, 5, 967–977. [Google Scholar] [CrossRef]
- Procopiou, A.T.; Ochoa, L.F. Voltage Control in PV-Rich LV Networks Without Remote Monitoring. IEEE Trans. Power Syst. 2017, 32, 1224–1236. [Google Scholar] [CrossRef]
- Liu, M.Z.; Procopiou, A.T.; Petrou, K.; Ochoa, L.F.; Langstaff, T.; Harding, J.; Theunissen, J. On the Fairness of PV Curtailment Schemes in Residential Distribution Networks. IEEE Trans. Smart Grid 2020, 11, 4502–4512. [Google Scholar] [CrossRef]
- Gerdroodbari, Y.Z.; Razzaghi, R.; Shahnia, F. Decentralized Control Strategy to Improve Fairness in Active Power Curtailment of PV Inverters in Low-Voltage Distribution Networks. IEEE Trans. Sustain. Energy 2021, 12, 2282–2292. [Google Scholar] [CrossRef]
- Dewangan, C.L.; Chakrabarti, S.; Singh, S.N.; Sharma, M. A Fair Incentive Scheme for Participation of Smart Inverters in Voltage Control. IEEE Trans. Ind. Inform. 2022, 18, 656–665. [Google Scholar] [CrossRef]
- Sun, X.; Qiu, J.; Tao, Y.; Ma, Y.; Zhao, J. Coordinated Real-Time Voltage Control in Active Distribution Networks: An Incentive-Based Fairness Approach. IEEE Trans. Smart Grid 2022, 13, 2650–2663. [Google Scholar] [CrossRef]
- Karagiannopoulos, S.; Mylonas, C.; Aristidou, P.; Hug, G. Active Distribution Grids Providing Voltage Support: The Swiss Case. IEEE Trans. Smart Grid 2021, 12, 268–278. [Google Scholar] [CrossRef]
- Olivier, F.; Aristidou, P.; Ernst, D.; Van Cutsem, T. Active Management of Low-Voltage Networks for Mitigating Overvoltages Due to Photovoltaic Units. IEEE Trans. Smart Grid 2016, 7, 926–936. [Google Scholar] [CrossRef]
- Guggilam, S.S.; Dall’Anese, E.; Chen, Y.C.; Dhople, S.V.; Giannakis, G.B. Scalable Optimization Methods for Distribution Networks with High PV Integration. IEEE Trans. Smart Grid 2016, 7, 2061–2070. [Google Scholar] [CrossRef]
- Far, S.R.; Moeini, A.; Chandra, A.; Kamwa, I. ADMM-Based Multi-Objective Control Scheme for Mitigating the Impact of High Penetration DER Integration in the Modern Distribution Systems. IEEE Access 2023, 11, 38589–38603. [Google Scholar] [CrossRef]
- Kim, I.; Harley, R.G. Examination of the effect of the reactive power control of photovoltaic systems on electric power grids and the development of a voltage-regulation method that considers feeder impedance sensitivity. Electr. Power Syst. Res. 2020, 180, 106130. [Google Scholar] [CrossRef]
- Zhang, C.; Xu, Y.; Dong, Z.; Ravishankar, J. Three-Stage Robust Inverter-Based Voltage/Var Control for Distribution Networks with High-Level PV. IEEE Trans. Smart Grid 2019, 10, 782–793. [Google Scholar] [CrossRef]
- Zhang, C.; Xu, Y.; Dong, Z.Y.; Zhang, R. Multi-Objective Adaptive Robust Voltage/VAR Control for High-PV Penetrated Distribution Networks. IEEE Trans. Smart Grid 2020, 11, 5288–5300. [Google Scholar] [CrossRef]
- Kumar Tatikayala, V.; Dixit, S. Multi-stage voltage control in high photovoltaic based distributed generation penetrated distribution system considering smart inverter reactive power capability. Ain Shams Eng. J. 2023, 15, 102265. [Google Scholar] [CrossRef]
- Liu, K.; Zhan, H.; Wei, Y.; Kang, T. A dynamic optimization method for power distribution network operation with high ratio photovoltaics. IET Gener. Transm. Distrib. 2022, 16, 4417–4432. [Google Scholar] [CrossRef]
- CENELEC. CENELEC—EN 50160. Available online: https://www.cencenelec.eu/ (accessed on 10 October 2023).
- IEEE. IEEE PES Distribution Systems Analysis Subcommittee Radial Test Feeders. Available online: https://cmte.ieee.org/pes-testfeeders (accessed on 10 October 2023).
- Electric Power Research Institute. Simulation Tool—OpenDSS. Available online: https://smartgrid.epri.com/SimulationTool.aspx (accessed on 10 October 2023).
- Biscani, F.; Izzo, D. A parallel global multiobjective framework for optimization: Pagmo. J. Open Source Softw. 2020, 5, 2338. [Google Scholar] [CrossRef]
- Kennedy, J.; Eberhart, R. Particle swarm optimization. In Proceedings of the ICNN’95—International Conference on Neural Networks, Perth, WA, Australia, 27 November–1 December 1995. [Google Scholar] [CrossRef]
Case Studies | Without Control | OLTC | PV RPC |
---|---|---|---|
Base case | √ | × | × |
Case study 1 | × | √ | × |
Case study 2 | × | × | √ |
Case study 3 | × | √ | √ |
Case Study | Base Case | 1 | 2 | 3 |
---|---|---|---|---|
Energy losses by active power [kWh] | ||||
Energy losses by active power reduction [%] | - | |||
Energy losses by reactive power [kVARh] | ||||
Energy losses by reactive power reduction [%] | - |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Dubravac, M.; Žnidarec, M.; Fekete, K.; Topić, D. Multi-Stage Operation Optimization of PV-Rich Low-Voltage Distribution Networks. Appl. Sci. 2024, 14, 50. https://doi.org/10.3390/app14010050
Dubravac M, Žnidarec M, Fekete K, Topić D. Multi-Stage Operation Optimization of PV-Rich Low-Voltage Distribution Networks. Applied Sciences. 2024; 14(1):50. https://doi.org/10.3390/app14010050
Chicago/Turabian StyleDubravac, Marina, Matej Žnidarec, Krešimir Fekete, and Danijel Topić. 2024. "Multi-Stage Operation Optimization of PV-Rich Low-Voltage Distribution Networks" Applied Sciences 14, no. 1: 50. https://doi.org/10.3390/app14010050
APA StyleDubravac, M., Žnidarec, M., Fekete, K., & Topić, D. (2024). Multi-Stage Operation Optimization of PV-Rich Low-Voltage Distribution Networks. Applied Sciences, 14(1), 50. https://doi.org/10.3390/app14010050