Economic Analysis of Demand Side Management with Residential PV System and Energy Storage System

Abstract

Renewable energy sources (RESs) as distributed generation (DG) have an important place on distribution networks (DNs) in recent years. RESs are being used for voltage stability, low power losses and low energy cost. Two way energy transmission is possible after the development of smart distribution girds and different electricity tariffs can be applied for customers at different times of day. PV modules are growing rapidly for residential applications and PV modules applications are becoming widespread together with technological improvements. Because of the raw material continuity problem of PV modules, energy storage systems (ESSs) can be used at residential PV applications. In this paper, economical effect of the residential PV system for customer is investigated and ESS is used with PV system for more efficient PV usage. The charge/discharge timing of ESS has been set to obtain a minimum electricity bill for one home. Then we used distribution network to analyse the impact of the residential PV application. For this purpose, it was accepted that 25 per cent of homes at distribution network have residential PV and ESS (RPVESS).

Keywords

• PV Modules,Energy Storage Systems

Konutlarda PV ve Enerji Depolama Sistemiyle Talep Yönetiminin Ekonomik Analizi

Abstract

Dağıtık üretim olarak yenilenebilir enerji kaynakları, son yıllarda dağıtım şebekelerinde önemli bir yere sahiptir. Yenilenebilir enerji kaynakları; gerilim kararlılığı, düşük güç kaybı ve düşük enerji maliyeti için kullanılmaya başlanmıştır. Akıllı dağıtım şebekelerinin geliştirilmesinden sonra iki yönlü enerji aktarımı ve müşteriler için günün farklı saatlerinde farklı elektrik tarifeleri uygulanabilir hale gelmiştir. PV modüller konut uygulamaları için hızla büyümekte ve PV modül uygulamaları teknolojik gelişmelerle birlikte yaygınlaşmaktadır. PV modüllerin hammadde sürekliliği sorunu nedeniyle, konut PV uygulamalarında enerji depolama sistemleri kullanılabilir. Bu çalışmada, müşteriler için konut PV sisteminin ekonomik etkisi araştırılmış ve daha etkin PV kullanımı için PV sistemi ile birlikte enerji depolama sistemi kullanılmıştır. Enerji depolama sisteminin şarj / deşarj zamanlaması, bir ev için elektrik faturası minimum olarak ayarlanacak şekilde belirlenmiştir. Daha sonra konut PV uygulamasının etkisini analiz etmek için dağıtım şebekesi kullanılmıştır. Bu amaçla, dağıtım şebekesindeki evlerin yüzde 25'inin konut PV ve Enerji Depolama Sistemi’ne (RPVESS) sahip olduğu kabul edilmiştir.

Keywords

• PV Modül,Enerji Depolama Sistemleri,Talep Yönetimi,Dağıtım Şebekeleri

References

1. [1] Ravishankar, A. N., Ashok, S. , Kumaravel, S., Effects of demand side management & storage on renewable energy penetration to the grid, Proceedings of the 2017 Third International Conference on Advances in Electrical, Electronics, Information, Communication and Bio-Informatics (AEEICB), Chennai, 2017, pp. 329-335.
2. [2] Federica, C., Idiano, D., Massimo, G., Photovoltaic energy systems with battery storage for residential areas: an economic analysis, Journal of Cleaner Production, vol. 131, pp. 460-474, 2016.
3. [3] Numbi, B. P., Malinga, S. J., Optimal energy cost and economic analysis of a residential grid-interactive solar PV system- case of eThekwini municipality in South Africa, Applied Energy, vol. 186, pp. 28-45, 2017.
4. [4] Fernando, M. C., Rui, C., Almeida, M. E., Pires, V. F., Economic assessment of residential PV systems with self-consumption and storage in Portugal, Solar Energy, vol. 150, pp. 353-362, 2017.
5. [5] Manuel, R., Marian, H., Valentin, B., Wolf, F., Impact of residential electricity tariffs with variable energy prices on low voltage grids with photovoltaic generation, International Journal of Electrical Power & Energy Systems, vol. 79, pp. 161-171, 2016.
6. [6] Arráez-Cancelliere, O. A., Muñoz-Galeano, N., Lopez-Lezama, J. M., Performance and economical comparison between micro-inverter and string inverter in a 5.1 kWp residential PV-system in Colombia, Proceedings of the 2017 IEEE Workshop on Power Electronics and Power Quality Applications (PEPQA), Bogota, Colombia 2017, pp. 1-5.
7. [7] Lam, R. K., Tran, D. H., Yeh, H. G., Economics of residential energy arbitrage in california using a PV system with directly connected energy storage, Proceedings of the 2015 IEEE Green Energy and Systems Conference (IGESC), Long Beach, CA, 2015, pp. 67-79.
8. [8] Villalva, M. G., Gazoli, J. R., Ruppert, F. E., Modeling and circuit-based simulation of photovoltaic arrays, Proceedings of the 2009 Brazilian Power Electron. Conf., Bonito, BRAZIL, 2009, pp. 1244–1254.

9. [9] Tian, H., Mancilla-David, F., Ellis, K., Eduard, M., Peter, J., A cell-to-module-to-array detailed model for photovoltaic panels, Solar Energy, vol. 86, pp. 2695-2706, 2012.
10. [10] El-Saadawi, M. M., Hassan, A. E., Abo-al-ez, K. M., Kandil, M. S., A Proposed Dynamic Model Of Photovoltaic-DG System, in Proceedings of the 2010 1st Int. Nucl. Renew. Energy Conf., Amman, Jordan, 2010, pp. 1-6.
11. [11] Abdulkadir, M., Samosir, A. S., Yatim, A. H. M., Modeling and simulation based approach of photovoltaic system in Simulink model, ARPN J Eng Appl Sci., vol. 7, pp. 616–623, 2012.
12. [12] Yao, E., Samadi, P., Wong, V. W. S., Schober, R., Residential Demand Side Management Under High Penetration of Rooftop Photovoltaic Units, IEEE Transactions on Smart Grid, vol. 7, pp. 1597-1608, 2016.
13. [13] Strbac, G., Demand side management: Benefits and challenges, Energy Policy, vol. 36, pp. 4419–4426. 2008.
14. [14] Conejo, A. J., Morales, J. M., Baringo, L., Real-time demand response model, IEEE Trans. Smart Grid, vol. 1, pp. 236–242. 2010.
15. [15] Samadi, P., Mohsenian-Rad, H., Wong, V. W. S., Schober, R., Real-time pricing for demand response based on stochastic approximation, IEEE Trans. Smart Grid, vol. 5, pp. 789–798, 2014.
16. [16] Pedrasa, M. A. A., Spooner, T. D., MacGill, I. F., Coordinated scheduling of residential distributed energy resources to optimize smart home energy services, IEEE Trans. Smart Grid, vol. 1, pp. 134–143, 2010.
17. [17] Atzeni, I., Ordonez, L. G., Scutari, G., Palomar, D. P., Fonollosa, J. R., Demand-side management via distributed energy generation and storage optimization, IEEE Trans. Smart Grid, vol. 4, pp. 866–876, 2013.
18. [18] Adika, C. O., Wang, L., Autonomous appliance scheduling for household energy management, IEEE Trans. Smart Grid, vol. 5, pp. 673–682, 2014.
19. [19] Awad, A. S. A., Fuller, J. D., EL-Fouly T. H. M., Salama, M. M. A., Impact of Energy Storage Systems on Electricity Market Equilibrium, IEEE Transactions on Sustainable Energy, vol. 5, pp. 875-885, 2014.
20. [20] Choi, M. E., Kim, S. W., Seo, S. W., Energy Management Optimization in a Battery/Supercapacitor Hybrid Energy Storage System, IEEE Transactions on Smart Grid, vol. 3, pp. 463-472, 2012.
21. [21] Barton, J. P., Infield, D. G., Energy storage and its use with intermittent renewable energy, IEEE Transactions on Energy Conversion, vol. 19, pp. 441-448, 2004.
22. [22] Wook, K., Van-Huan, D., Thanh-Tuan, N., Woojin, C., Analysis of the effects of inverter ripple current on a photovoltaic power system by using an AC impedance model of the solar cell, Renewable Energy, vol. 59, pp. 150-157, 2103.
23. [23] http://www.kyocera.com.sg/products/solar/pdf/kc200gt.pdf Accessed 23 May 2017
24. [24] http://www.epdk.org.tr/TR/Dokuman/7292 Accessed 23 June 2017[25] Ranjan, R., Das, D., Simple and Efficient Computer Algorithm to Solve Radial Distribution Networks, Electr Power Components Syst., vol. 31, pp. 95–107, 2003.