pablo ruiz minguela - Bilbao Marine Energy Week
Transcription
pablo ruiz minguela - Bilbao Marine Energy Week
TECHNO-ECONOMIC CONSIDERATIONS FOR THE COMPETITIVE DEVELOPMENT OF OCEAN ENERGY FARMS Pablo Ruiz-Minguela Marine Renewable Energy jpablo.ruiz-minguela@tecnalia.com Session 2: Ocean Energy Projects 18th April, 2013 1. 2. 3. 4. 5. 6. 7. 8. Who we are Techno-economic Tools Project Size Deployment Site Mooring System Grid Connection Maintenance Planning Conclusions 2 Who we are TECNALIA is the first Applied Research Centre in Spain and one of the most important in Europe with around 1.500 staff, 116 million Euro turnover and over 4.000 clients. Organised in 7 Business Divisions: we work from the experience and the expertise we have acquired in the markets in which we operate, with an efficient and proactive attitude. ENERGY & ENVIRONMENT INDUSTRY & TRANSPORT INNOVATION STRATEGIES ICT - European Software Institute TECHNOLOGICAL SERVICES SUSTAINABLE CONSTRUCTION HEALTH We transform Energy and Environmental Challenges into Business Opportunities Smart Grids Renewable Energy Electric Storage and Mobility Marine Energy Solar Power Offshore Wind The Energy System of The Future Integral approach based on the deployment of marine energy farms and their costefficiency over the whole lifecycle Energy and Environment Sustainability as Mega-trend Environment and Climate Change New materials from Waste Prediction Systems Water Cycle Wave Energy 6 Technoeconomic tools for Ocean Energy 7 Affordability of Ocean Energy: Cost Reduction Three Possible Ways: Innovation, Learning-by-doing and Economies of scale “Business as usual” Innovation scenario Tidal Energy Wave Energy (Source: Carbon Trust, 2011) 8 COE as the Driving Factor to select Technical Alternatives Integral approach: Farm performance, not only device performance; Project lifecycle cost, not only manufacturing costs Project life, Discount rate FINANCIAL PARAMETERS WEC, Mooring, Electric lines, Installation, Decommisioning, Insurance CAPITAL EXPENDITURE (CAPEX) Vessels, staff, spares OPERATION EXPENDITURE (OPEX) Device type, No. units, Power, Performance Financial model of the farm COE NPV n ENERGY PRODUCTION NPV = ∑ t =1 Ce * energy n (1 + k ) n − CAPEX − OPEX ∑ (1 + k ) n t =1 ENVIRONMENTAL PARAMETERS Water depth, Resource, Environmental loads, Distance to PCC, Distance to port 9 Parametric Models They make it possible to compare and assess different alternatives 10 When it comes to ocean energy … size matters! 11 Device Level Decisions Optimal device sizing (in terms of COE) depends on Type of Device and Deployment Site Point absorbers and floating OWCs seem to be mostly efficient when deployed with relatively small diameters 12 Array Level Decisions The influence of the scale of the farm is crucial to obtain competitive COE For smaller farms, the cost of the electrical infrastructure has a significant impact on the COE 13 Rough seas make good sailors … but maybe not big profits! 14 Deployment Site Decisions: CAPEX Higher CAPEX for structural and moorings systems is required in most energetic sites in order to meet survivability conditions SITE High energy flux Moderate energy flux Low energy flux Increase In Hull Weight for a Typical Point Absorber of d = 6 m 15 Deployment Site Decisions: OPEX Component reliability is linked to conditions of operation in the deployment site: higher exposition reduces component life and increases OPEX Hs = 5,5 m Hs = 0,5 m Bearing fatigue life in years for different sea-states Instantaneous & cumulative damage 16 A ship should not ride on a single anchor … Cost-effective moorings are needed! 17 Mooring Line Decisions Mooring system represents a significant investment (literature: 15% of CAPEX) Catenary with Surface Buoy and Clump Weight Catenary Depth = 120 m Load = 4,000 kN SF = 1,67 Selection of Line Type & Optimal Configuration to Reduce CAPEX 18 Array Mooring Decisions Sharing mooring lines and components could significantly reduce costs 3-Line Mooring System (reference) Aquaculture inspired Mooring System 19 Energy cannot be created or destroyed … but it can be easily lost! 20 Farm Layout Decisions Clustering depends on global factors: Number of units, Power per unit, Location of the farm, WEC technology, Inter-device minimum distance, Mooring system Full String String Series Redundant String Star or Radial … and constraints: Series DC •Electrical physical barriers (max no. of devices per cluster) •Distribution mode (AC/DC) •Redundancy level •Switchgear system 21 Electric Lines Decisions Selection of output voltage influences maximum cable losses and section (i.e. CAPEX) Energy storage contributes to reduce instantaneous power fluctuations Grid connection Opt 1 Opt 2 Output voltage - Umbilical cable (kV) 13.2 6 BMH voltage – Static cable (kV) 13.2 13.2 Losses (% of total generation) 3,14% 4,32% Cores (Kg) (% increase) 0% 33,42% Opt 3 Opt 4 3 0.6 13.2 13.2 7,22% 8,64% 88,68% 118,05% Wave farm integration at bimep (20 MW) 22 Information is power … Let’s use it to increase profit! 23 Site Accessibility and Operability Decisions OPEX is dependant on Resource Conditions, Duration, Availability of Dedicated , Limit Conditions … and access predictability Estimating bimep accessibility for a corrective maintenance requiring 3 h towing to port and 8 h work with Hs max = 1 m 24 Maintenance Planning Decisions Maximise Project Profitability OPEX Costs Preventive Maintenance Unavailability Energy Estimates Predictive Maintenance Accessibility Resource Constraints Limit Conditions Dedicated Vessels Duration Devices Works at Sea Generation Marine Safety η Forecasts Maintenance Strategies Environment CMS Maintenance Orders Personnel Plans Corrective Maintenace Navigation Failures Revenues 25 Final word … Techno-economic tools are important to address high level challenges of Ocean Energy projects • • • • • An integral approach to cost reduction Model design parameters interdependencies Assess technical alternatives Identify improvement areas Deal with uncertainties (what-if questions) 26