A Renewable E nergy Strategy for the Republic of Cyprus and the - PowerPoint PPT Presentation

Dimitrios Nikolaidis & Stephen R. Smith Department of civil & environmental engineering, Imperial College London A Renewable E nergy Strategy for the Republic of Cyprus and the Potential Contribution from the Solid Waste Management Sector

Motivation Rough economic situation & increasing Rising cost energy costs in competitiveness Cyprus of the electricity market Flexibility & diverseness of renewable energy technologies Importance of harnessing renewable energy

Motivation Cyprus energy system •Isolated mini-grid • Reliance on imported fossil-fuels •Diesel 2% 1% 5% •Heavy fuel oil ⇒ High energy costs Conventional ⇒ High specific greenhouse gas fuels emissions Wind Solid Waste Sector PV •Potential indigenous fuel 92% •One of the highest waste Biomass generation per capita countries in Europe

Legislation & Drivers • Cyprus joined in 2004 as a member state of the EU • Required to comply with targets and policies 2020 Climate & Energy Renewable Energy Directive Landfill Directive 1999/31/EC Package 2009/28/EC • Treatment required before • 20% cut in greenhouse gas • 20% renewable energy target waste sent to landfill emissions translated to individual Member • Reduction targets of state targets • 20% of energy produced from biodegradable waste sent to renewables • Cyprus: 13% of energy supply landfill from 1995 levels from renewable sources • 20% improvement in energy efficiency • Cyprus: 16% of electricity supply from renewables • All based on 1990 levels • Currently at 8% of electricity supply from renewables

Methodology Use of Multi-Criteria Analysis (MCA) to serve the following objectives: 1. Identifying the optimum renewable energy technologies for electricity supply in the form of a ranking list, including EfW systems and assessing their importance 2. Identifying the optimum solid waste management option for energy recovery MCA • Used in complex decision-making processes • Allows incorporation of conflicting criteria in incommensurable units

Methodology 4. Multi-criteria 1. 3. analysis (MCA) Classification Performance 5. Sensitivity and assessment •Weight coefficients 2. according to Analysis calibration of (derivation of Identification degree of performance performance of options significance criteria matrix)

Methodology MCA incorporates a degree of uncertainty and is subjective , as it is based on the decision-maker’s preferences Elimination of subjectivity: 1. Facilitating stakeholder participation and collaborative decision making 2. PROMETHEE method chosen for assessment – use of generalised transfer functions for pairwise evaluations of options depending on the type of criterion 3. Use of a sensitivity analysis to assess the subjectivity of criteria weighting

-GAIA E THE PROME

Options – Renewable E nergy Technologies Concentrated Solar Power Solar PV Wind energy (CSP) •Parabolic trough systems •Onshore •Solar Wind tower •Offshore •Dish Wind sterling Tidal Energy Hydropower Geothermal Wave Power Energy Crops Energy from Waste (EfW) •Point absorber •Surface •Thermal •Woody or attenuator technologies herbaceous •Oscillating water •Non-thermal plants column technologies

Options – Solid waste management methods • Incineration • Gasification • Pyrolysis • Co-combustion of Refused Derived Fuel (RDF)  Cement kiln  Power Plant Anaerobic Digestion (AD)  Source separated  Mechanical Biological Treatment with AD

Criteria Breakdown – Renewable E nergy technologies Economic Environment Technical Social Levelised cost Greenhouse Public of electricity Gas (GHG) Lifetime perception (LCOE) Emissions Impacts on the Technology Employment Ecosystem Status potential Contribution to Noise Impacts Reliability targets & policies Deployment Visual Impacts Potential status Land Requirements

Criteria Breakdown – Solid Waste Management Economic Environment Technical Social Potential energy Capital costs Carbon dioxide Public perception generation Contribution to Operational costs Methane Technology Status targets & policies Transport Product Acid gases Demand Marketability & Residue management Flexibility of Heavy metals & waste suitable organics for treatment Energy Noise impacts requirements Visual impacts Odour Land requirements

Results MCA 1 – Renewable E nergy Technologies MCA 1 Net flow rankings Notes 0,3 • Solar PV ranks 1 st 0,2 with φ =0.234 0,1 • Hydropower ranks 2 nd 1. Solar PV 2. Hydropower with φ =0.1753 3. Energy from Waste 0 • Energy from Waste 4. Wind Offshore Net flow ( Φ� ranks 3 rd with 5. CSP -0,1 6. Geothermal φ =0.1427 7. Wind Onshore • Tidal and wave power -0,2 8. Energy Crops rank 9 th and 10 th with 9. Tidal 10. Wave highly negative net -0,3 flows -0,4 -0,5

Discussion MCA 1 – Renewable E nergy Technologies Solar PV (1 st ) Tidal (9 th ) & Wave technologies (10 th ) PROS: PROS: • 2 nd highest irradiation potential in Europe 1920 •Lower visual and noise impacts kWh/m2 CONS: •High social acceptance •Low wave power potential & low tidal streams •Good overall performance in environmental ⇒ surrounding the island low deployment criteria potential status •Relatively good LCOE •Very high capital costs CONS: •Variable energy source ⇒ low reliability EfW (3 rd ) PROS: •High contribution to targets & policies • High reliability of supply •High deployment potential status CONS: •Greenhouse gas emissions, land requirements

Results MCA 2 – Solid Waste Management Sector MCA 2 Net flow rankings Notes 0,3 0,25 • Co-combustion of 0,2 RDF in cement kilns ranks 1 st with 0,15 φ =0.234 1. RDF Cement Kiln 0,1 2. MBT with AD • MBT with AD ranks Net flow ( Φ� 3. Pyrolysis 0,05 2 nd with φ =0.0624 4. RDF power plant 0 5. Gasification • Incineration ranks 7 th 6. Source separated AD with φ = -0.2196 -0,05 7. Incineration -0,1 -0,15 -0,2 -0,25

Discussion MCA 2 – Solid Waste Management Sector Co-combustion of RDF in cement kilns PROS: •Vassiliko Cement kiln ⇒ Low capital costs & low land requirements •High local product marketability & high export potential of cement product •Strict environmental regulations ⇒ low pollutant emissions CONS: •Poor performance in technical criteria •Technically challenging to produce co-fuel to a specification for co- combustion •High transport demand •Inexistent potential for electricity generation

Sensitivity Analysis Modification of weight distribution of criteria ⇒ Weight Stability Intervals (WSI) MCA 1 Renewable energy technologies •Solar PV consistently the optimum during fine-tuning except when increasing the reliability criterion weight coefficient • ↑ reliability weight coefficient ⇒ solar PV ↓ , hydro ranks 1st • ↓ LCOE weight coefficient ⇒ CSP ↑ • ↑ deployment potential ⇒ hydro ↓ and CSP ↑ MCA 2 Solid Waste Management Sector •RDF co-combustion in cement kilns consistently identified as optimum method when fine-tuning

Conclusion – Renewable E nergy Options Solar PV Concentrating Solar Power Energy from Waste (EfW) •Solar energy is the favoured (CSP) • Promotes the diversion renewable energy source •CSP systems could become of biodegradable •PV systems should be attractive for deployment with waste from landfills installed across the island future reductions in levelised • High reliability of supply costs CONS : Variable Source ⇒ low • Higher efficiency than PV Should be incorporated in reliability of supply • Lower land requirements the renewable energy mix •Ability to store thermal fluid ⇒ ↑ reliability

Conclusion – Solid Waste Management Sector Co-combustion of RDF in cement kilns Preferable solid waste management option compared to energy recovery processes. •Vassiliko Cement kiln ⇒ Low capital costs and low land requirements. • Dependent on reliable technical processing to produce product to a specification ⇒ TECHNICALLY CHALENGING process • Use of an efficient biodrying reactor to produce product to a specification is required

Recommendations The study could be repeated using a stochastic method • Defining the uncertainty in the input data with probability distributions • Reliability-based approach ⇒ Monte Carlo simulations • Distribution of total flows for each option will be produced according to the range of input parameters • The report provides a strong basis for future studies Thank you..

3. PROMETHEE METHOD NDIX APPE