• International Journal of Technology (IJTech)
  • Vol 10, No 6 (2019)

Dynamic Pricing Scheme for the Java-Bali System Residential Load

Eko Adhi Setiawan, Andy Prakoso, Vhania Maulia

Corresponding email: vhaniam@gmail.com


Cite this article as:
Setiawan, E.A., Prakoso, A.Maulia, V., 2019. Dynamic Pricing Scheme for the Java-Bali System Residential Load. International Journal of Technology. Volume 10(6), pp. 1194-1201

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Eko Adhi Setiawan -Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia -Tropical Renewable Energy Center TREC, Faculty of Engineering, Universi
Andy Prakoso -Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia -Tropical Renewable Energy Center TREC, Faculty of Engineering, Universit
Vhania Maulia Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia
Email to Corresponding Author

Abstract
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The monopoly electricity market in Indonesia uses flat tariffs but is being encouraged to change to dynamic pricing. Dynamic pricing scenarios have been implemented in many Western countries with various types of schemes. This paper discusses dynamic pricing scenarios based on residential load and generation in the Java-Bali system. The tariff scheme is a combination of critical peak pricing (CPP) and time-of-use (TOU). The CPP runs for only a few hours each year depending on the gas power plant operation. TOU will be used with peak and off-peak schedules as determined based on residential load characteristics. The gas power plant is a reference in designing the CPP rates because it is used to meet peak loads if other plants are unable to meet requirements and its cost of generating electricity is high compared to other power plants. The dynamic pricing scheme is simulated for a residential load. Then, the load reduction during peak times and the impact of reducing electricity consumption in the Java-Bali system is analyzed.

Basic cost of supply; Critical peak; Dynamic pricing; Electricity tariff; Time of use

Introduction

Dynamic pricing is a program launched by electric utilities to study a various rate structures to lower peak demand for electricity (Ton et al., 2013). Taylor et al. (1975), Braithwait (2000), King and Chatterjee (2003), EPRI (2008) and Faruqui et al. (2010) present the application of dynamic pricing. Dynamic electricity prices are a demand side management technique that can reduce peak loads by providing different prices at different times according to demand. A peak in the load profile is the result of unregulated requests when additional capacity is needed. This peak load capacity remains inactive during the off-peak period, which results in the loss of opportunity costs and system inefficiency. Dynamic pricing can shift demand from peak to off-peak and help avoid large capital investments.

The retail electricity market generally offers flat rate or dynamic price. Prices remain unchanged regardless of demand in the first case, while when prices are dynamic the price per unit of electricity increases or decreases as electricity consumption changes. However, generation costs to meet peak demand are compared to off-peak demand because most peak time generating units have higher operating costs compared to basic load units. Although fixed rates allow  customers’ electricity bills to be free of uncertainty, this can lead to high capacity additions. While reducing peak demand, dynamic prices can also provide every consumer the opportunity to reduce their bill and maintain a constant level by changing consumption patterns and therefore shifting loads.


Conclusion

The dynamic electricity tariff scenario was conducted with two schemes, TOU and a combination of CPP/TOU. In this case the off-peak time of the TOU scheme is between 02.00 and 18.00 with a tariff of Rp 1,099.24 and the peak time of the TOU is between 18.00 and 02.00 with a tariff of Rp 2,203.36. This price is fixed throughout the year. The off-peak time of the CPP/TOU scheme is the same as the TOU scheme. The peak interval is between 20.00–02.00 and the critical peak interval is 17.00–20.00. The off-peak and CPP/TOU peak rates are the same as the TOU, while the critical peak rates are Rp 7,385.08 for 132 hours per year or approximately 1.5% a year. Load shifting will occur by 5% during peak TOU due to its peak-to-off-peak ratio of 2:1 and 8.75% during CPP/TOU due to its peak-to-off-peak ratio of 3.5:1. Consumers can benefit my adjusting load usage to dynamic pricing with smart home technology. Dynamic pricing can encourage consumers to reduce electricity consumption at peak times, and has a positive impact by reducing utility grid company expenditure and reducing the emissions/pollutants from fossil fuels. 

Acknowledgement

This paper was supported and funded by Hibah Penelitian dan Penulisan Tugas Akhir  PITTA B   UI NKB- 0722/UN2.R3.1/HKP.05.00/2019.

References

Braithwait, S., 2000. Residential TOU Price Response in the Presence of Interactive Communication Equipment. In: A. Faruqui and K. Eakin. (eds.), Pricing in Competitive Electricity Markets. Boston: Kluwer Academic Publishers

EPRI, 2008. Price Elasticity of Demand for Electricity: A Primer and Synthesis, Palo Alto, CA

Faruqui, A., Hledik, R., and Tsoukalis, J., 2009. The Power of Dynamic Pricing. The Electricity Journal, Volume 22(3), pp. 42–56

Faruqui, A., Sergici, S., Warner, C., 2017. Arcturus 2.0: A Meta-analysis of Time Varying Rates for Electricity. The Electricity Journal, Volume 30(10), pp. 64–72

Faruqui, A., Sergici, S., 2011. Dynamic Pricing of Electricity in the Mid-Atlantic Region: Econometric Results from the Baltimore Gas and Electric Company Experiment. Journal of Regulatory Economics, Volume 40(1), pp. 82–109

Faruqui, A., Sergici, S., 2010. Household Response to Dynamic Pricing of Electricity: A Survey of 15 Experiments. Journal of Regulatory Economics, Volume 38, pp. 193–225

King, C.S., Chatterjee, S., 2003. Predicting California Demand Response, Public Utilities Fortnightly July 1, American Energy Institute

Setiawan, E.A., Asvial, M., 2016. Renewable Energy’s Role in a Changing World. International Journal of Technology, Volume 7, pp. 1280–1282

Taylor, L.D., 1975. The Demand for Electricity: A Survey. The Bell Journal of Economics, Volume 6(1), pp. 74–110

Ton, D., Biviji, M.A., Nagypal, E., Wang, J., 2013. Tool for Determining Price Elasticity of Electricity Demand and Designing Dynamic Price Program. In: IEEE PES Innovative Smart Grid Technologies Conference (ISGT), pp. 1–6