International Conference on Recent Trends in Applied Science and Technology. International Conference organized by IPN Education Group, Malaysia and Scientific Research Publishing House, Iran
Authors:Noriza Mohd Saad,Zulkifli Abdullah,Nora Yusma Mohamed Yusof,Norhayati Mat Husin,Ahmad Lutfi Mohayiddin ,Mohamad Taufik Mohd Arshad ,
Abstract:Tariff design is the key mechanism used to allocate electricity generation and distribution costs to customers. The designing process can be very complex not only due to the regulatory policies surrounding it but also due to the need of satisfying various parties such as the electricity distributor and the different types of electricity customers. Therefore, it is the aim of this study to formulate an optimum tariff structure for Malaysia that can deal with multiple objective functions. Utilizing secondary data gathered through various energy related sources and a goal programming approach, a new optimum tariff structure has been proposed specifically focused on domestic customers and others in general. The findings show, in the case of domestic users, having only two bands of domestic customers instead of the current practice of five, may have already helped to achieve an optimum tariff structure. The findings also show that for other types of users Malaysian current tariff structure may have yet to achieve its optimum level. While these findings are subjected to few limitations, it is notable that the findings can be used to evaluate the existing tariff structure of Malaysia.
Keywords:Goal Programming, Electricity,Tariff Structure,Optimization,
I.Anderson, J. E., & Neary, J. P. (2007). Welfare versus market access: The implications of tariff structure for tariff reform. Journal of International Economics 71, 187–205.
II.Anderson, J. E., & Neary, J. P. (2016). Sufficient statistics for tariff reform when revenue matters. Journal of International Economics 98, 150–159.
III.Brown, T., Faruqui, A. & Grausz, L. (2015). Efficient tariff structures for distribution network services. Economic Analysis and Policy 48, 139–149
IV.Chen, C-Y & Liao, C-J. (2011). A linear programming approach to the electricity contract capacity problem. Applied Mathematical Modelling 35, 4077–4082.
V.Energy Commission Malaysia (2017), Kuala Lumpur, Malaysia.
VI.Economy Planning Unit (EPU) (2013). The Malaysia Economy in Figures 2013.Fernández, M.A., Zorita, A.L., García-Escudero, L.A., Duque, O., Moríñigo, D., Riesco, M. & Muñoz, M. (2013). Cost optimization of electrical contracted capacity for large customers. Electrical Power and Energy Systems 46, 123–131.
VII.Hledik, R. (2014). Rediscovering Residential Demand Charges. The Electricity Journal, 1040-6190. http://dx.doi.org/10.1016/j.tej.2014.07.003
VIII.Hledik, R. & Greenstein, G. (2016). The distributional impacts of residential demand charges. The Electricity Journal 29, 33–41.
IX.Lee, J.Y. & Chen, C.L. (2007). Iteration particle optimization for contract capacities selection of time-of-use rates industrial customers. Energy Convers. Manage. 48,1120–1131.
X.Mohd Saad, N., Mohamed Yusof, N.Y., Mamat, M.N., Abdullah, Z., Mat Husin, N. & Ibrahim, J. (2018). A Review of Tariff Efficiency Mechanisms for Malaysian Electricity Distribution Firm. 4th International Conference on Engineering, Technology and Management 2018 (ICETM 2018) at Singapore on 26th-28th January 2018.
XI.Nijhuis, M. , Gibescu, M. &Cobben, J.F.G. (2017). Analysis of reflectivity & predictability of electricity network tariff structures for household consumers. Energy Policy 109, 631–641.
XII.Nojavan, S., Zare, K. & Mohammadi-Ivatloo, B.(2017). Robust bidding and offering strategies of electricity retailer under multi-tariff pricing. Energy Economics 68, 359–372.
XIII.Passey, R., Haghdadi, N., Bruce, A. & MacGil, I. (2017). Designing more cost reflective electricity network tariffs with demand charges. Energy Policy 109, 642–649.
XIV.Picciariello, A., Reneses, J., Frías, P. & Soder, L. (2015a). Distributed generation and distribution pricing: Why do we need new tariff design methodologies?. Electric Power Systems Research 119, 370-376.
XV.Picciariello, A., Vergara, C., Reneses, J., Frías, P. & Soder,L. (2015b). Electricity distribution tariffs and distributed generation: Quantifying cross-subsidies from consumers to prosumers. Utilities Policy 37, 23-33.
XVI.Rodrı ́guez Ortega, M. P. & Pe ́rez-Arriaga, J. I. (2008). Distribution network tariffs: A closed question?. Energy Policy 36, 1712–1725.
XVII.Rubin, S. J. (2015). Moving Toward Demand-Based Residential Rates. November 2015, 28 (9), 1040-6190/# Elsevier Inc. http://dx.doi.org/10.1016/j.tej.2015.09.021
XVIII.Schlereth, C., Stepanchuk, T. & Skiera, B. (2010). Optimization and analysis of the profitability of tariff structures with two-part tariffs. European Journal of Operational Research 206, 691–701.
XIX.Tsay, M.T., Lin, W.M. & Lee, J.L. (2001). Optimal contracts decision of industrial customers, International Journalof Electrical Power Energy System 23, 795–803.
XX.Yang, Y., Chen, W. Wei, L. &Chen, X. (2018). Robust optimization for integrated scrap steel charge considering uncertain metal elements concentrations and production scheduling under time-of-use electricity tariff. Journal of Cleaner Production 176, 800-812.View | Download