On the efficiency of connection charges under renewable integration in distribution systems

The economic efficiency of two-part retail electricity tariffs in the presence of renewable resources in the distribution system is analyzed. Two integration models are considered: (i) a centralized model involving a regulated retail utility who owns the resources as part of its generation portfolio, and (ii) a decentralized model in which each consumer individually owns and operates the resources behind the meter and is capable of selling surplus electricity back to the retailer in a netmetering setting. The structure of the optimal two-part tariffs is obtained. For both integration models, it is shown that, under two-part tariffs, renewable resources generally improve efficiency and consumer surplus. In contrast, under linear tariffs, the integration of renewable resources by consumers may lower both consumer surplus and social welfare.

[1]  Lang Tong,et al.  Day ahead dynamic pricing for demand response in dynamic environments , 2013, 52nd IEEE Conference on Decision and Control.

[2]  Luiz Augusto N. Barroso,et al.  Time-of-Use Tariff Design Under Uncertainty in Price-Elasticities of Electricity Demand: A Stochastic Optimization Approach , 2013, IEEE Transactions on Smart Grid.

[3]  Raghuram Iyengar,et al.  Nonlinear pricing , 2022 .

[4]  Marija D. Ilic,et al.  Control and optimization methods for electric smart grids , 2012 .

[5]  Ram Rajagopal,et al.  Stochastic dynamic pricing: Utilizing demand response in an adaptive manner , 2014, 53rd IEEE Conference on Decision and Control.

[6]  F. Ramsey.  A Contribution to the Theory of Taxation , 1927 .

[7]  Richard T. B. Ma,et al.  Monotonic marginal pricing: demand response with price certainty , 2014, PERV.

[8]  Lang Tong,et al.  Dynamic Pricing and Distributed Energy Management for Demand Response , 2016, IEEE Transactions on Smart Grid.

[9]  S. Borenstein.  Private Net Benefits of Residential Solar PV: The Role of Electricity Tariffs, Tax Incentives, and Rebates , 2015, Journal of the Association of Environmental and Resource Economists.

[10]  S. Borenstein,et al.  Dynamic Pricing, Advanced Metering, and Demand Response in Electricity Markets , 2002 .

[11]  C. Goldman,et al.  Demand Response from Day-Ahead Hourly Pricing for Large Customers , 2006 .

[12]  Severin Borenstein,et al.  Regional and Income Distribution Effects of Alternative Retail Electricity Tariffs , 2011 .

[13]  Severin Borenstein,et al.  The Redistributional Impact of Nonlinear Electricity Pricing , 2012 .

[14]  K. M. Chandy,et al.  Impact of residential PV adoption on Retail Electricity Rates , 2013 .

[15]  Na Li,et al.  Optimal demand response: Problem formulation and deterministic case , 2012 .

[16]  J. Tirole,et al.  Retail Electricity Competition , 2004 .

[17]  Severin Borenstein,et al.  The Redistributional Impact of Non-Linear Electricity Pricing , 2010 .

[18]  Lang Tong,et al.  Optimal pricing for residential demand response: A stochastic optimization approach , 2012, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[19]  M.D. Anderson,et al.  Dynamic pricing [of electricity] , 2000, IEEE Potentials.

[20]  M. Feldstein.  Equity and Efficiency in Public Sector Pricing: The Optimal Two-Part Tariff , 1972 .

[21]  M. Boiteux,et al.  On the management of public monopolies subject to budgetary constraints , 1971 .

[22]  Lang Tong,et al.  Renewables and Storage in Distribution Systems: Centralized vs. Decentralized Integration , 2016, IEEE Journal on Selected Areas in Communications.

[23]  Lang Tong,et al.  Renewable in distribution networks: Centralized vs. decentralized integration , 2015, 2015 IEEE Power & Energy Society General Meeting.