Frankfurt (Germany), 6-9 June 2011
MOCCI – IT – RIF Session 5 – Paper 999
Multi-Objective analysis of Regulatory
frameworks for Active Distribution Networks
G. Celli, F. Pilo, S. Mocci, and G. G. Soma
Department of Electrical and Electronic Engineering University of Cagliari
ITALY
Frankfurt (Germany), 6-9 June 2011
MOCCI – IT – RIF Session 5 – Paper 999
Distribution Systems integrating Distributed Energy Resources Renewable Energy Sources (RES) Consumers are Producers (Prosumers?) Medium and Small CHP
Future Plug in electric vehicles Storage devices Demand response Fully liberalized market
Author Name – Country – RIF Session ….. – Paper ID
Introduction
Smart Grid is the solution for a sustainable energy future
Frankfurt (Germany), 6-9 June 2011
MOCCI – IT – RIF Session 5 – Paper 999
Fundamental step towards Smartgrids; DERs integrated, not simply connected; DSO, producers, customers share
responsibilities for network operation; Regulation – still missing in most cases – is
the key for ADN implementation.=S
P, Q, V P, Q, V
P, Q
, V
P, Q P, -QP, Q
DMS
CHP
PVWT==SS
P, Q, V P, Q, V
P, Q
, V
P, Q P, -QP, Q
DMS
CHP
PVWT
=S
P, Q, V P, Q, V
P, Q
, V
P, Q P, -QP, Q
DMS
CHP
PVWT==SS
P, Q, V P, Q, V
P, Q
, V
P, Q P, -QP, Q
DMS
CHP
PVWT
Distribution planning of ADNs Distribution planning of ADNs
Active Distribution Networks (ADNs)
In intelligent grid era should consider opportunities coming from operation (Automation, load and DER control, storage) network investments might be deferred or avoided.
Planning still answers to why, when, what, and where make investments, considering also the Active Management.
Frankfurt (Germany), 6-9 June 2011
System stakeholders and Goals Producers (DER owners)
Energy production/selling maximization
Earning money from RES incentives
Low connection charges Network availability
MOCCI – IT – RIF Session 5 – Paper 999
The Civil Society (CS) Environmental concerned DG and RES exploitation Energy Losses reduction Reliability Reasonable Costs
DSO
CAPEX & OPEX minimization Reliability and Efficiency To increase revenues Fulfill Regulator’s Prescriptions ADN CAPEX and OPEX
System stakeholders have conflicting goals:
compromise solutions are necessary.
Frankfurt (Germany), 6-9 June 2011
Multi-Objective (MO) methods: provide a set of optimal solutions (Pareto set) instead of a single optimal solution of the traditional techniques.
Authors developed a Software tool, based on Non-dominated Sorting Genetic Algorithm (NSGA-II), for distribution system planning in presence of high levels of DG.
Multi-Objective Programming
In recent works:
MOCCI – IT – RIF Session 5 – Paper 999
MO optimization aimed at finding the Pareto-set of RES placements in planning scenarios characterized by:
different regulatory frameworks,
level of Active Management, and
incentive mechanisms.
RESULT: Active management allows higher DG shares, without the negative follow up of the “fit and forget” policy applied with unpredictable generation.
Frankfurt (Germany), 6-9 June 2011
Software Planning tool used to perform a MO optimization aimed at finding the Pareto-set of RES placements in planning scenarios characterized by advanced ADN schemes (Reconfiguration, Demand side Management, DER as active subject, providing system services).
Aim of the Study
To simulate the impact of ADN implementation level on the development and integration of DER in the System,
To assess the relationship between Regulatory environment and the level of ADN implementation.
Main novelty of the present paper:
MOCCI – IT – RIF Session 5 – Paper 999
Active operation can help solve tensions caused by investors and DSO contrasting goals, direct consequence of the regulatory mechanism
adopted.
Frankfurt (Germany), 6-9 June 2011
ScenariosScenario
ADNImplementation
DER Investor responsibility
Use of systemcharge
A.1 no no noB.1 GC(P) committed Energy curtailedB.2 GC(P) remunerated noC.1 DG Control (P&Q) committed Energy curtailedC.2 DG Control (P&Q) remunerated noD DSM remunerated noE RCF no noF GC+DSM+RCF remunerated no
Scenario A is based on the “connect and forget” policy. Full incentives mechanism (current Italian situation); RES earn Green Certificates as a function of the energy produced (1 Green
Certificate = 100 €/MWh). Energy produced by PV is bought at special price as high as 300 €/MWh, but it cannot earn Green Certificates.
RES refunds by Regulator partially allowed;
MOCCI – IT – RIF Session 5 – Paper 999
Frankfurt (Germany), 6-9 June 2011
Civil Society DSOs DER Investors
RES integrationCost of network upgrading
[(1 rDSO)·CU]Building and operation (CDG)
Energy Losses (EL) Cost of energy losses (CL) Cost of connection (CConn)
ADN OPEX(CADN) Incomes for ADN (RADN) Incentives (IEn)
Asset management (rDSO·CU) Incomes from DG (IConn)Incomes from ancillary services
(IAS)
Expenditure for incentives (EXinc)
Civil Society
Distributors
RES Investors
LUDSOConnADNDSO CCrIROF )1(
ConnDGASEnInv CCIIOF
incUDSOADNCostsCS EXCrCOF )(
Stakeholders Objective Functions
LLossesCS EOF
100
%1
DGOF DG
CS
(3 different OFs)
Frankfurt (Germany), 6-9 June 2011
DER Investors point of view
Building costs are function of DER technology / rated capacity; Operation & maintenance costs are function of energy produced.
DER building and operation costs DER building and operation costs
Connection costs calculated according to Italian legislation. At distribution level RES owners:
Do not pay for transmission network upgrading; Pay a flat connection cost, which depends on the generator power
capacity and the distance from HV/LV or MV/LV substations; Can decide to build the infrastructure by themselves. In this case,
they can receive money back from Regulator (if the connection cost is greater than the flat cost).
DER Connection costs DER Connection costs
MOCCI – IT – RIF Session 5 – Paper 999
Frankfurt (Germany), 6-9 June 2011
Case Study
Average PD of 16 MW.
3 existing overhead open loop feeders, several overhead laterals.
Voltage drop problems due to load growth.
CAPEX are 135 k€, 90% reimbursed by the Regulator. Losses < 2%. The balance is positive, 738 k€.
3 HV/MV substations
36 MV/LV (15 trunk - 21 lateral) nodes
Italian 20 kV distribution network
Without new DERs: Without new DERs:
MOCCI – IT – RIF Session 5 – Paper 999
Frankfurt (Germany), 6-9 June 2011
Results
Regulatory environment Scenario AScenario B.1(committed)
Scenario B.2(remunerated)
Scenario C.1(committed)
Scenario C.2 (remunerated)
Scenario D (DSM)
Scenario E(RCF)
Scenario F(P&Q,DSM,RCF)
OFDSO [M€] 1.4 0.6 1.1 0.6 1.2 1.3 1.3 0.9
OFInv [M€] 51.1 33.6 37.5 37.3 38.6 53.6 50.5 41.2
Civil Society (cost) [M€] 4.1 13.8 16.7 14.7 17.3 4.8 4.2 13.8
DG penetration 140 % 174 % 171 % 175 % 171 % 145 % 139 % 171 %
Net DSO CAPEX [k€] 9.5 34.2 34.2 33.7 34.6 4.9 6.6 6.2
EL [MWh] 2.52 6.76 5.80 6.70 5.13 2.67 2.68 6.19
PBT (mean value) [years] 1.8 2.0 2.1 1.9 2.0 1.8 1.7 2.0
Wind plants
avg. power 3758 kW 3928 kW 3760 kW 2677 kW 2677 kW 2881 kW 3295 kW 3295 kW
avg. No. 10.1 14.9 12.5 14.9 14.9 13.3 11.2 11.2
PV plants
avg. power 961 kW 748 kW 879 kW 955 kW 955 kW 945 kW 955 kW 955 kW
avg. No. 6.9 3.4 3.1 5.7 5.7 5.0 7.4 7.4
Biomass plants
avg. power 0 0 0 20 kW 20 kW 20 kW 0 0
avg. No. 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Average OFs values in optimal Pareto sets and significant planning parameters.
Different ScenariosDifferent Scenarios
Frankfurt (Germany), 6-9 June 2011
Conclusion Software planning tool to perform a MO optimization algorithm aimed at finding the Pareto-set of DER placements in scenarios characterized by different AND schemes.
MO optimization allows finding the good compromise solutions for the system stakeholders (Civil Society, DER investors and DSOs), highlighting the relationship between the regulatory environment and the level of Active Management implementation.
The active operation of the system is fundamental to limit network investments for the necessary network upgrading in the medium term without unfair barriers to the integration of RES.
Scenario without active management remuneration is preferable, because the reward penalizes too much the Regulator .
MOCCI – IT – RIF Session 5 – Paper 999