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Price Regulation and the Incentives to Pursue Energy Efficiency by Minimizing Network Losses Joisa Dutra, Flavio Menezes, Xuemei Zheng Centre for Regulation, FGV; The University of Queensland June 2014 Joisa Dutra, Flavio Menezes, Xuemei Zheng


  1. Price Regulation and the Incentives to Pursue Energy Efficiency by Minimizing Network Losses Joisa Dutra, Flavio Menezes, Xuemei Zheng Centre for Regulation, FGV; The University of Queensland June 2014 Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 1 / 11

  2. Introduction Energy efficiency is usually cost-effective. Typical concern is to incentivize consumers to pursue energy efficiency. However, demand side management (DSM) is not always effective. rebound effect of consumers supplier’s incentive to maximize sales under price cap regulation — requires revenue decoupling from sales quantity Should shift the focus on the supply (e.g. transmission and distribution) side energy efficiency. overall losses between the power plant and final consumers: 8 to 15% (International Electrotechnical Commission, 2007). Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 2 / 11

  3. Our Contribution Analyse the incentives for supply side energy efficiency embedded in existing regulatory regimes. Key results: Which regime yields the highest expected welfare depends on demand, costs and the weight assigned by the regulator to the monopolist’s profits in total surplus.The comparison driven by the size of the cost of effort is complex. Policies that encourage utilities to promote end-user energy conservation may reduce the incentives that electricity suppliers face for internal energy efficiency. Add to the literature on DSM (Wirl,1995) and on incentive mechanism design (Eom, 2009; Chu & Sappington,2012; Chu & Sappington,2013). Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 3 / 11

  4. Model Setup Inverse demand function: P ( Q ) = a − bQ , with a > 0 , b > 0 Q : the amount of electricity that could be consumed by end users, P : unit price of electricity paid by consumers. Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 4 / 11

  5. Model Setup Inverse demand function: P ( Q ) = a − bQ , with a > 0 , b > 0 Q : the amount of electricity that could be consumed by end users, P : unit price of electricity paid by consumers. Φ ( · ) = Q Energy efficiency: Q S Q s : units purchased in the wholesale market, Q < Q s : due to network losses ⇒ 0 < Φ < 1. Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 4 / 11

  6. Model Setup Inverse demand function: P ( Q ) = a − bQ , with a > 0 , b > 0 Q : the amount of electricity that could be consumed by end users, P : unit price of electricity paid by consumers. Φ ( · ) = Q Energy efficiency: Q S Q s : units purchased in the wholesale market, Q < Q s : due to network losses ⇒ 0 < Φ < 1. C ( Q s , E ) = cQ s + E Cost function: C : the total cost, c > 0: fixed unit cost of electricity, E : the cost of exerting effort E , E = { 0 , e } with e > 0: the two possible levels of effort to improve energy efficiency. Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 4 / 11

  7. Model Setup Inverse demand function: P ( Q ) = a − bQ , with a > 0 , b > 0 Q : the amount of electricity that could be consumed by end users, P : unit price of electricity paid by consumers. Φ ( · ) = Q Energy efficiency: Q S Q s : units purchased in the wholesale market, Q < Q s : due to network losses ⇒ 0 < Φ < 1. C ( Q s , E ) = cQ s + E Cost function: C : the total cost, c > 0: fixed unit cost of electricity, E : the cost of exerting effort E , E = { 0 , e } with e > 0: the two possible levels of effort to improve energy efficiency. cQ The monopolist’ profit: π ( E , Q ) = P ( Q ) Q − Φ ( E ) − E Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 4 / 11

  8. Model Setup Relationship between efforts and energy efficiency Φ Φ E = 0 1 − ν ν E = e 1 − ν ν with ν > 1 2 and 0 < Φ < Φ < 1 . Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 5 / 11

  9. Model Setup Relationship between efforts and energy efficiency Φ Φ E = 0 1 − ν ν E = e 1 − ν ν with ν > 1 2 and 0 < Φ < Φ < 1 . Expected level of energy efficiency:   ΦΦ Φ l = ( 1 − ν ) Φ + ν Φ , if E = 0 Φ ( E ) = ,  ΦΦ Φ h = ν Φ +( 1 − ν ) Φ , if E = e with Φ h > Φ l by assumption. Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 5 / 11

  10. Model Setup Relationship between efforts and energy efficiency Φ Φ E = 0 1 − ν ν E = e 1 − ν ν with ν > 1 2 and 0 < Φ < Φ < 1 . Expected level of energy efficiency:   ΦΦ Φ l = ( 1 − ν ) Φ + ν Φ , if E = 0 Φ ( E ) = ,  ΦΦ Φ h = ν Φ +( 1 − ν ) Φ , if E = e with Φ h > Φ l by assumption. Overall social welfare: W ( Q , E ) = S ( Q ) + γπ ( E , Q ) W : total social welfare, S ( Q ) : consumer’s surplus, γ ( 0 < γ < 1 ) : the weight assigned on the monopolist’s expected profit. Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 5 / 11

  11. Model Setup Relationship between efforts and energy efficiency Φ Φ E = 0 1 − ν ν E = e 1 − ν ν with ν > 1 2 and 0 < Φ < Φ < 1 . Expected level of energy efficiency:   ΦΦ Φ l = ( 1 − ν ) Φ + ν Φ , if E = 0 Φ ( E ) = ,  ΦΦ Φ h = ν Φ +( 1 − ν ) Φ , if E = e with Φ h > Φ l by assumption. Overall social welfare: W ( Q , E ) = S ( Q ) + γπ ( E , Q ) W : total social welfare, S ( Q ) : consumer’s surplus, γ ( 0 < γ < 1 ) : the weight assigned on the monopolist’s expected profit. Objective of the regulator: to maximize overall social welfare Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 5 / 11

  12. The Unregulated Monopolist Lemma 1 The unregulated monopolist’s optimal choice of effort is given as follows: Effort Cost Optimal Effort Optimal Price Expected Social Welfare ( 2 γ + 1 )( a Φ l − c ) 2 e 1 � e a Φ l + c � E = 0 2 Φ l 8 b Φ 2 l ( 2 γ + 1 )( a Φ h − c ) 2 a Φ h + c 0 < e < � e 1 E = e 2 Φ h 8 b Φ 2 h e 1 = c ( 2 ν − 1 )( Φ − Φ )[ 2 a ΦΦ − c ( Φ + Φ )] where � 2 4 b Φ 2 Φ LHS: effort cost; RHS: difference of benefit obtained from positive effort and zero effort � e 1 increases when a increases (i.e., the demand shifts outward), � e 1 increases when b decreases (i.e., flatter/ less steep), � e 1 increases with c for sufficiently low values of c and decreases with c for sufficient high values of c (i.e., non-monotonic with c ). Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 6 / 11

  13. Rate of Return Regulation Lemma 2 Under rate-of-return regulation, the monopolist chooses E = 0, and regulated prices are given by: � P ROR ∗ = c Φ , Φ = Φ P ROR ∗ = , ROR ∗ = c P Φ , Φ = Φ and expected social welfare is given by: W ror ∗ = ν ( a Φ − c ) 2 + ( 1 − ν )( a Φ − c ) 2 , 2 b Φ 2 2 2 b Φ where ( a Φ − c ) 2 refers to the ex post welfare with Φ = Φ , 2 b Φ 2 while ( a Φ − c ) 2 is the ex post welfare with Φ = Φ . 2 2 b Φ Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 7 / 11

  14. Price Cap Regulation and Revenue Cap Regulation Lemma 3 The optimal price cap, level of effort and expected social welfare are fully characterized as Effort Cost Effort Level Optimal Price Cap Expected Social Welfare ( a Φ l − c ) 2 e � � c e 2 E = 0 Φ l 2 b Φ 2 � � l ( a Φ h − c ) 2 − 4 b Φ 2 ( a Φ h − c ) 2 +( a Φ h − c ) ( a Φ h − c ) 2 − 4 b Φ 2 a Φ h + c − he he ) − e 0 < e < � e 2 E = e 2 Φ h 4 b Φ 2 2 h e 2 = c ( a Φ l − c )( Φ h − Φ l ) where � b Φ h Φ 2 l LHS: effort cost; RHS: difference of benefits obtained from positive effort and zero effort. In our setting there is no meaningful distinction between price cap and revenue cap regulation. Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 8 / 11

  15. Mandated Target Regulation Lemma 4 The optimal mandated target for energy efficiency is Φ mt = Φ . The characterization of mandated target regulation is summarized as Mandated Target Effort Cost Effort Level Expected Social Welfare ( 2 γ + 1 )( a Φ l − c ) 2 Φ mt = Φ e � � E = 0 + ( 1 − γ ) νδ e 4 8 b Φ 2 l ( 2 γ + 1 )( a Φ h − c ) 2 0 < e < � e 4 E = e − γ e + ( 1 − γ )( 1 − ν ) δ 8 b Φ 2 h e 4 = ( a Φ h − c ) 2 − ( a Φ l − c ) 2 where � + ( 2 ν − 1 ) δ 4 b Φ 2 4 b Φ 2 h l LHS: effort cost; RHS: difference of benefits obtained from positive effort and zero effort, with ( 2 ν − 1 ) δ as the difference of penalization avoided for not meeting targets. Joisa Dutra, Flavio Menezes, Xuemei Zheng (Centre for Regulation, FGV; The University of Queensland) June 2014 9 / 11

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