Optimization of active distribution networks: design and analysis of significative case studies for enabling control actions of real infrastructures D.Moneta*, Giacomo Viganò**, Gianluca Alimonti***, Paolo Mora* * RSE Ricerca sul Sistema Energetico SpA - Italy ** Università degli Studi di Milano – Italy ***INFN & Università degli Studi, Milano - Italy 1

Outline RSE S.p.A. RES diffusion & scenario in Italy Active Networks / Control System Test cases Conclusion / Next activities 2

RSE S.p.A. (formerly CESI RICERCA SpA, ERSE SpA) has been established at the end of 2005, with the mission to take over funded research activities of national and international interest focused on electricity and energy sector and it started operating on January 1st RSE S.p.A. is currently owned by GSE, a publicly-owned company promoting and supporting renewable energy sources in Italy. ~320 researchers and technicians in 4 departments research on all aspects of energy sectors: security, power supply, regulation… RSE S.p.A. 3

RES diffusion & scenario in Italy 4

National Action Plan on Renewable Energy Resource “mimimum trajectory” Main contribution is expected by the electric sector to reach the overall national target of 17 % TRADITIONAL 60 % Electricity balance 2012 – net grid request (Source: Terna) 2020 targets 26.39% RES-electric RES-total 340 TWh 5

DG-RES Diffusion MV HV (source: re.jrc.ec.europa.eu/pvgis/cmaps/eur.htm/ (source: RSE) SunWind Connected Power [MW] Cumulative Data (source: ENEL D.) 14,8 PV (62,5 %) Geographical distribution of renewable resources Cumulative PV installed up today: 18.2 GW 6

Active Networks / Control System RSE experience 7

Active distribution networks Active distribution networks (ADNs) have systems in place to control a combination of distributed energy resources (DERs), defined as generators, loads and storage. Distribution system operators (DSOs) have the possibility of managing the electricity flows using a flexible network topology (and DERs). DERs take some degree of responsibility for system support, which will depend on a suitable regulatory environment and connection agreement Council on Large Electric Systems (CIGRE) WG C6.11. The Italian Authority set a threshold of at least 1% (5%) of hour per year where power flow inversion towards HV must occur for MV feeders to be considered as ‘active networks’ [delibera ARG/elt 39/10] From simple “connection” to “integration” of DG Develope of advanced control approach 8

Objectives: Maximise DG diffusion of renewable resources. Assure high quality power levels. Increase the stability and security of the network. Open market opportunities. Two different approaches: diffuse control (local) centralized control Advanced control approach Develop and verify control functions ‘slow’ actions 9

Centralized control load generator controllable gen (/load) storage unit HV MV busbar STORE DATA SETPOINT field 10 DISCoVER

Regulation resources On Load Tap Changer (OLTC): –operated by DSO Capacitor bank –operated by DSO Reactive power injection/absorption by ‘controllable’ generators (subset of DERs) Active power modulation of “controllable” generators (subset of DERs) Storage: –operated by DSO (integral constraint on 24 h period) Necessary data: - capability curves of controllable resources - costs of resources operated by the DSO - rewards of Ancillary Services (for DERs) cost 11

Optimization Procedure: DISCoVER The main part of the DISCoVER algorithm is represented by an optimal power flow (OPF), that determines the admissible working point, ‘optimal’ according to the criteria defined in the objective function. The objective of the optimization procedure is to determine, starting from a set of operating values, fixed for a series of time periods, an admissible condition for a MV network in presence of DG, with the minimum dispatching cost for the DSO. That OPF calculates network losses, too, which are then evaluated at the marginal cost of energy. 12

Test cases 13

Test network 14

Design of the cases Different case studies are implemented changing: Topology of the network: the counter-alimentation of some branch are studied Day of reference for load and generation (for example): Winter weekday Summer Sunday 7.75 MWh Voltage and current constraints Number and length of the time intervals 15

Set of available resources: OLTC Set of DG and their capability limits Storage Characteristic of the storage: Position: feeders A-B-C, different node Capability and capacity Initial and final charge Cost of the resources (active and reactive power) Case analyzed: the case analized have the following characteristic: Normal network Summer Sunday 24 periods of 1 h Baseline: No resources available Free voltage limit MV bus-bar fixed to [p.u.] Active network: Voltage range: [p.u.] OLTC Reactive power from PV generators Storage on feeder B Capability ±1MW ±1MVAr Capacity 2 MWh Initial and final charge: 1 MWh Intermediate costs for all the resources 16

Voltage in the baseline case 17

Optimization algorithm output Reactive power from DGBUS-BAR voltage Charge of the storage. Capacity of the storage: 2 MWh. Maximum power: 1 MW. Charge Discharge 18

Voltage in the optimized case 19

Others advantages 2 MWh Cases NO OPTIMIZATION STORAGE IN B STORAGE IN A DIFFERENCE Active losses [kWh] Power injected by HV network Reduction of active losses 20

Conclusions Next activities 21

Conclusion & Next activities Diffusion of Distributed Generation requires new strategies to ensure reliable and economic operations RSE methodologies permit to manage an Active MV network and to evaluate results of different control strategies depending on: – number, siting and sizing of controllable DERs, – cost of internal resources (storage, especially), – rewards for Ancillary services offered by controllable resources (generators and loads). Implement new functionality (i.e. variable loads) Comparison between different approaches (centralized vs local control) and different management of the resources. It’s necessary to adopt standard interfaces for network description and to exchange information with DERs. Demo on real networks (national projects, EU project GRID4EU) 22

…questions? Giacomo Viganò Diana Moneta Thanks for your kind attention 23