Wind power in Portugal: Renewable identification and security of supply

Transcription

1 Wind power in Portugal: Renewable identification and security of supply INVESTIGACIÓN Y DESARROLLO TECNOLÓGICO TRANSFERENCIA DE TECNOLOGÍA Y VALORIZACIÓN FORMACIÓN AVANZADA CONSULTORÍA PRE-INCUBACIÓN DE EMPRESAS DE BASE TECNOLÓGICA

2 Wind energy in Portugal: why? There are no fossil fuel resources in Portugal Constraints in using fossil fuels ( CO 2 ) The economic rationality of new nuclear option in Portugal not yet assessed Good wind resources Great complementary between hydro and wind sources for energy generation (hydro share is about 20% of total consumption, on average ) Good sites for wind power are far away of demand centers 2 Chile 2011 Acknowledgment: REN Redes Energéticas Nacionais (kind permission: Engº Vítor Baptista)

3 Wind, hydro and thermal generation Hydro Thermal 3 Chile 2011 Acknowledgment: REN Redes Energéticas Nacionais (kind permission: Engº Vítor Baptista)

4 Wind generation, load and challenges 2.March March.2010 Load Wind Power greater than load!!! wind farms monitored at transmission level Wind Wind power integration in large scale requires reinforced interconnections 4 Chile 2011

5 Identification of Renewable Potential Campus da FEUP Rua Dr. Roberto Frias, Porto Portugal T F www@inescporto.pt Decision support regarding renewable resource through the GIS and Fuzzy sets 2011

6 WHY NEGOTIATION? Investors search for the most profitable locations to install renewable generation The State has a policy for the territory Environmentalists organize opposition movements to renewable energy sources THREE ACTORS each with his own objectives or criteria, or ideas on what is favorable and what is not 6 Chile 2011

7 Methodology Coverages Criteria Weighting criteria Attribute 7 Chile 2011

8 Example Environment interest Tolerance map 8 Chile 2011

9 Example Investors interest generation Tolerance map 9 Chile 2011

10 Results on GIS Example of conciliation for 220 MW wind parks 10 Chile 2011

11 Security of Supply Campus da FEUP Rua Dr. Roberto Frias, Porto Portugal T F www@inescporto.pt Probabilistic Evaluation of Reserve Requirements of Generating Systems with Renewable Power Sources: The Portuguese and Spanish Cases 2011

12 Motivation Monitoring the Security of Supply in both countries for the years to come The work was developed in the framework of a RTD project financed by the TSO of Portugal and Spain (REN and REE, respectively) within their activities related to MIBEL (the Iberian electricity market), with the aim of maximizing the integration of renewable energy Important issues Penetration of wind power and other intermittent sources will increase dramatically in the next years, both in Portugal and Spain The two systems have a strong hydro component including pumping storage plants Adequate operating reserve levels must be defined and monitored Avoiding loss of renewable energy is an important concern 12 Chile 2011

13 Developing a tool Strategy Chronological Monte-Carlo simulation with well-being analysis Forced outages, maintenance, hydro, wind power, solar, other (PRE) Detailed treatment of the operating reserve Use the tool to perform different studies 13 Chile 2011 Adequacy evaluation for Static and Operating reserve: Alternative scenarios with increased penetration of intermittent power Loss of renewable energy at valley hours Comparing alternatives for increasing the operating reserve Benefits of interconnections Relate intermittent power penetration with the adequate reserve levels

14 Operating reserve definition R P (t) = Primary reserve at time t R S (t) = Secondary reserve at time t R T (t) = Tertiary reserve (<1 h) at time t R OPE (t) = Operating reserve at time t L = Short term load deviation at time t PW = Wind power capacity variation at time t G = Lost generating capacity at time t 14 Chile 2011

15 Reliability indices Conventional Reliability Indices 15 Chile 2011 LOLP = loss of load probability LOLE = loss of load expectation EPNS = expected power not supplied EENS = expected energy not supplied LOLF = loss of load frequency LOLD = loss of load duration Well-being indices EM = expected marginal hours Success Healthy Marginal Failure FH and FM = expected frequency of healthy and marginal states DH and DM = expected duration of healthy and marginal states Indices were calculated both for capacity analysis and operating reserve analysis

16 Some case studies (Portugal and Spain) Base case All historical hydrological and wind series were simulated H + scenario the wettest hydrological year was considered H - scenario the driest hydrological was simulated HWM scenario driest hydrological condition wind series reduced by 50% maintenance was increased by 20% 16 Chile 2011

17 LOLE (h/yr) LOLE (h/yr) Some results Portugal Capacity analysis (Portugal) Base HWM H- H Operating reserve (Portugal) Base HWM H- H Chile 2011

18 LOLE (h/yr) LOLE (h/yr) Some results Spain Capacity analysis (Spain) Base HWM H- H Operating reserve (Spain) Base HWM H- H Chile 2011

19 LOLE (h/yr) Some results monthly variation of LOLE Monthly variation of the operating risk (Portugal 2025) H- Base H Month 19 Chile 2011

20 LOLE (h/yr) Some results maintenance Effect of +20% in maintenance outaged power (Portugal 2025) M+ Base Month 20 Chile 2011

21 Conclusions The approach is able to deal with the new issues raised by the increased penetration of intermittent sources of electricity Specific analysis of operating reserve needs detects risk situations not captured by the traditional capacity analysis Influence of the forecast error can be assessed Adequate levels for reserve are identified Possible solutions to increase the reserve levels can be tested The role of fast tertiary reserve is crucial when possibly large unexpected variations of load and intermittent power have to be addressed Loss of renewable energy at valley hours can be estimated Possible solutions to avoid this situation can be tested and evaluated 21 Chile 2011

22 SPIN-OFF MADE AT INESC TEC FROM RESEARCH TO BUSINESS Previsión de potencia eólica Actividad iniciada en parques eolicos como clientes Software INESC TEC Socios: las empresas, INESC Porto 22 Chile 2011

23 JOINT BRAZIL-PORTUGAL RESEARCH New development of prediction models for wind farms in Brazil Research promoted by ONS the TSO in Brazil Partnership with a Brazilian University (UFPE) Consultancy by INESC TEC 23 Chile 2011

24 JOINT CHILE-PORTUGAL RESEARCH We are looking for to do something Partnership with INESC TEC 24 Chile 2011