Multi-Objective analysis of Regulatory frameworks for Active Distribution Networks
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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. MOCCI – IT – RIF Session 5 – Paper 999. Introduction.

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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

MOCCI – IT – RIF Session 5 – Paper 999


Mocci it rif session 5 paper 999

Introduction

  • 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

Smart Grid is the solution for a sustainable energy future

Author Name – Country – RIF Session ….. – Paper ID

MOCCI – IT – RIF Session 5 – Paper 999


Mocci it rif session 5 paper 999

Active Distribution Networks (ADNs)

  • 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.

Distribution planning of 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.

MOCCI – IT – RIF Session 5 – Paper 999


System stakeholders and goals

System stakeholders and Goals

  • 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

  • Producers (DER owners)

    • Energy production/selling maximization

    • Earning money from RES incentives

    • Low connection charges

    • Network availability

System stakeholders have conflicting goals:

compromise solutions are necessary.

MOCCI – IT – RIF Session 5 – Paper 999


Multi objective programming

Multi-Objective Programming

Multi-Objective (MO) methods:  provide a set of optimal solutions (Pareto set) instead of a single optimal solution of the traditional techniques.

In recent works:

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.

  • MO optimization aimed at finding the Pareto-set of RES placementsin 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.

MOCCI – IT – RIF Session 5 – Paper 999


Aim of the study

Aim of the Study

Main novelty of the present paper:

  • Software Planning tool used to perform a MO optimization aimed at finding the Pareto-set of RES placementsin planning scenarios characterized by advanced ADN schemes (Reconfiguration, Demand side Management, DER as active subject, providing system services).

  • To simulate the impact of ADN implementation level on the development and integration of DER in the System,

  • To assess the relationship between Regulatoryenvironment and the level of ADN implementation.

Active operation can help solve tensions caused by investors and DSO contrasting goals, direct consequence of the regulatory mechanism adopted.

MOCCI – IT – RIF Session 5 – Paper 999


Scenarios

Scenarios

  • 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


Mocci it rif session 5 paper 999

Stakeholders Objective Functions

Civil Society

(3 differentOFs)

Distributors

RES Investors


Der investors point of view

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 Connection 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).

MOCCI – IT – RIF Session 5 – Paper 999


Case study

Case Study

Italian 20 kV distribution network

  • Average PD of 16 MW.

  • 3 existing overhead open loop feeders, several overhead laterals.

  • Voltage drop problems due to load growth.

  • 3 HV/MV substations

  • 36 MV/LV (15 trunk - 21 lateral) nodes

Without new DERs:

  • CAPEX are 135 k€, 90% reimbursed by the Regulator.

  • Losses < 2%.

  • The balance is positive, 738 k€.

MOCCI – IT – RIF Session 5 – Paper 999


Results

Results

Different Scenarios

Average OFs values in optimal Pareto sets and significant planning parameters.


Conclusion

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


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