NEW AND RENEWABLE ENERGY SOURCES FOR SUSTAINABLE COMMUNITIES
by
M. G. Carvalho L. Alves, A. Costa, N. Duic
VII Encontro Regional do Engenheiro Angra do Heroísmo – Terceira – Açores 20 Julho 2002 CONTENTS OF THE PRESENTATION
Characteristics of Sustainable Communities
Types of Sustainable Communities
Description of on-going projects for enhanced sustainability
Conclusions SUSTAINABLE COMMUNITIES
Rio summit: Agenda 21
EU White Paper for RES, Campaign for Take-off, ALTENER
EU Green Paper on Security of Supply
Kyoto Protocol THE GOALS OF THE SUSTAINABLE COMMUNITY
Integration of new technologies and concepts in socio-economic development
Intensive use of RES
Diversify energy sources
Social and economic benefits CHARACTERISTICS OF THE SOLUTIONS
Competitive cost of NRET (when compared to conventional solutions)
High percentage of NRES
Decentralised generation
Satisfy the needs of a community → INTEGRATION INTEGRATION
Integration of NRES: Wind, Biomass, Small hydro, Geothermal, Distributed Generation, PV and solar heating, hydrogen, energy storage….
Rational use of energy (buildings, energy management , CHP...) is also important TYPES OF COMMUNITY
Islands (small/medium)
Isolated rural areas
Non-isolate urban areas (blocks of buildings, neighbourhoods in residential areas, commercial / light industrial developments) Islands ISLANDS
High economic dependence on imported energy sources – High energy costs
Environmental fragility
Seasonability of energetic, water and waste disposal needs - Tourism
Small size of the local grids Island projects SANTO ANTÃO
Metodology for the Evaluation of Renewable Energy Sources Potential EVALUATION OF SOLAR POTENTIAL IN GIS Clean sky Typical day •Height Gp •Visibility Measurements of global •Climatic zone radiation in metereological stations •Sun zenith •Ground reflexion •Lattitude Gp K h # # Vila Rib.Gran. U K = # # p N # Lugar de Guene # Boca de Coruja # Pinhão Cha de igreja # # # # # # Vila das Pombas U G # # # Eito hp # # # # # # João Afonso Campo de Ca#o # # # # # # # # # # # # Cabo da Ribeira Garca de Cima # #
# # # # Lom. de Figueira Pico da Cruz Alto Mira # # # # # Ribeirão Fundo # Morro do Vento # # # Hourly maps # Jorge Luis Lagoa
# Rib. dos Bodes Cirio # # # # SIG # Rib. Fria SIG # Cha de Morte SIG of direct and C.das Vacas SIG Porto Novo Monte Trigo # # Radiação média anual (wh/m2) SIG SIG # Tabuga 3897.817 - 3982.671 diffuse # 3982.671 - 4067.524 SIG Mato Estreito # # # Manuel Lopes 4067.524 - 4152.378 X Catano Spatial Model # 4152.378 - 4237.232 Lombo da# s Lanças 4237.232 - 4322.085 radiation Tarrafal # 4322.085 - 4406.939 4406.939 - 4491.793 # 4491.793 - 4576.646 4576.646 - 4661.5 No Data
010Kilometers Grid of global estimated global Ghp
radiation with clean sky Gh
(METHODOLOGY DEVELOPED BY INESC – PORTO) MAP OF RENEWABLE RESOURCES - SUN #
# Vila Rib.Gran. U # # N # Lugar de Guene # Boca de Coruja # Pinhão Cha de igreja # # # # # # Vila das Pombas U # # # Eito # # # # # # J# oão Afonso Campo de Cao# # # # # # # # # # # # Cabo da Ribeira Garca de Cima # #
# # # # Lom. de Figueira Pico da Cruz Alto Mira # # # # # Ribeirão Fundo # Morro do Vento # # # # Jorge Luis Lagoa
# Rib. dos Bodes Cirio # # # # # Rib. Fria # Cha de Morte C.das Vacas Monte Trigo Porto Novo # # # Radiação média anual (wh/m2) Tabuga 3897.817 - 3982.671 # 3982.671 - 4067.524 Mato Estreito # # # Manuel Lopes 4067.524 - 4152.378 Catano # 4152.378 - 4237.232 Lombo da# s Lanças 4237.232 - 4322.085 Tarrafal # 4322.085 - 4406.939 4406.939 - 4491.793 # 4491.793 - 4576.646 4576.646 - 4661.5 No Da t a
010Kilometers MAP OF RENEWABLE RESOURCES - WIND #
# # Vila Rib.Gran. U # N # # # # Cha de igreja # # # Vila das Pombas U # # # # #
# # # # # # # Corda # # # # # # # # # # # # Cabo da Ribeira Janela # #
# Pico da Cruz # # # # # # # # #
# # # #
# # # # # # # Porto Novo # # #
# velocidade média (m/s) # # # 0 = vel
# 0 < vel <4 # 4 < vel < 5
# 5 < vel < 6
# 6 < vel < 7 7 < vel < 8 8 < vel < 11 No Da t a
0 10 Kilometers MAP OF RENEWABLE RESOURCES - GEOTHERMAL ELECTRICITY DISTRIBUTION NETWORK CABO VERDE
The potential for Clean Development Mechanism in Electricity Production ECONOMY
2000 0 2000 Maio Maio 1800 1800
Br= 10 ava Brava 1600 1600 Tourism investments 1400 Business as Usual Fog1o400 Fogo 1980 1980 = 100 1200 S. N1200icolau S. Nicolau e e d
rd 1000 r 1000 Boavista Boavista e V Ve 800
800 Sal Sal e e p p 600 600 a a S. Antão S. Antão C 400 C
400 , ,
SaP ntiago Santiago P 200 200 GD GD 0 S. Vice0nte S. Vicente 1980 1990 2000 2010 2020 2030 1980 1990 2000 2010 2020 2030
2000 Year Year
100 1800 1600 80 = 1400 Low development 19 1200 Regional GDP distribution for e d
r 1000 800 Ve 3 economic scenaria, per e
p 600 a
C 400
, island P 200
GD 0 1980 1990 2000 2010 2020 2030
Year ELECTRICITY DEMAND
1800 Wh G 1600 Tourism investment , n 1400 Business as usual 1200 Low development uctio 1000 d 800 600 y pro 400 icit r 200 0
Elect 1980 1990 2000 2010 2020 2030 Tourism sector Year 3000 Electrification rate p. Tourism investment ca 2500 Business as usual h/ Low development
W 2000 Security of supply 1500 y, k
icit 1000 r 500 Elect 0 1980 1990 2000 2010 2020 2030 Year ELECTRICITY SUPPLY
1200 Wind h 1000 Diesel + steam W ← Baseline
G 800 on,
i 600 t c 400 1200
odu Wind r h 1000 p 200 Diesel + steam W 800 0 G 2000 2010 2020 2030 on,
i 600 t c
year u 400 od r 30% wind → p 200 1200 0 Wind h 1000 Diesel + steam 2000 2010 2020 2030
W Combined Cycle
G 800 year , on 600 ti c u 400 d o pr 200 ← Combined cycle 30% wind 0 2000 2010 2020 2030
year Business as usual economic scenario CDM VALUE
5.0 4.5 Santiago, CC Wind in all 4.0 Maio Brava D 3.5 islands S Fogo U 3.0 São Nicolau M , e Boavista
lu 2.5 a Sal v 2.0 M Santo Antão Combined D
C 1.5 Santiago, wind 1.0 São Vicente cycle only 0.5 in Santiago 0.0 2000 2010 year 2020 2030
Business as usual economic scenarium
Medium CDM price scenarium – 15$/tCO2 INSTALLED POWER BY ISLAND
15
10
MW 5
0 40 2000 201 0 2020 2030 30
20
25 MW 20 10 15 3 0
MW 10 2000 2010 2020 2030 2 5 0 MW 1 10 200 0 2010 202 0 2030 0 2000 2010 2020 2030 5
Frontier, w ind MW BAU, w ind 0 PakW radise, wind 10 2000 2010 2020 2030 0
Fron1 tier, CC
000 020 030 5
BAU20 , CC MW Para2 2 d2 ise, CC 0 2 100 3.0 2000 2010 2020 2030 80 2.0 1 60 MW MW
MW 40 1.0 0 20 0.0 2000 2010 2020 2030 0 2000 2010 2020 2030 200 0 2010 202 0 203 0 PORTO SANTO
Renewable Energy Solutions for Islands 100% RES Island PORTO SANTO Madeira, Portugal RESOURCES TECHNOLOGIES COMMODITIES Sustainable Solar panels Community
Heat Porto Santo
Hydrogen
Solar Hydrogen Cold Storage
Electrolysis Water Reforming Fuel cell Trigeneration
Electricity Gas PV panels
Desalination Gasification Wind Wind turbines Sea
Wastewater treatment Waste
Wastewater EQUIPMENT TO BE INSTALLED PILOT HYDROGEN SYSTEM PRESENT SITUATION •75 kW Electrolyser •3.5 MW Diesel •300 kWh Storage •3.4 MW Fuel Oil •25 kW Fuel Cell •1.1 MW Wind (4.4%) •Peak Power – 5.6 MW •Low Power – 2 MW •Growth rate – 20%
SAVINGS
•27 tCO2/year •Cost: 830,000 € (33,000 €/kW) H2RES MODEL
RESOURCES TECHNOLOGIES COMMODITIES Sustainable Community Porto Santo
Solar Hydrogen Storage
Electrolysis Fuel cell Trigeneration Electricity PV panels
Desalination
Wind Wind turbines H2RES MODULES
WIND LOAD
SOLAR
STORAGE H2RES – WIND MODULE
Hourly wind velocity data obtained 0.14 Adjusted to the hub height z vz = v10 Converted into hourly potential output 10
120% r e
w Example for 100% po l VESTAS wind a
n 80% i turbines, as 60% nom installed on f o
t 225kW r 40% Porto Santo, 660kW pa ,
t Madeira,
u 20% average (1110kW) p Portugal
out 0% 0 5 10 15 20 25 30 wind velocity, m/s H2RES – SOLAR MODULE
Hourly total radiation on horizontal surface obtained
Adjusted to the inclined surface (RETSCREEN)
Converted into hourly potential output by efficiency provided from supplier H2RES – LOAD MODULE
Hourly load of power system obtained
Limit to renewable intake
Excess renewable rejected
4000 3500
3000 load 2500 solar output wind output 2000
kW renewable output 1500 renewable limit renewable taken 1000 renewable excess 500 0 0 4 8 12 16 20 hours H2RES – STORAGE MODULE – FILLING
Excess renewable taken to electrolyser ¾ If less than electrolyser capacity ¾ If hydrogen tank not full
The rest rejected – taken to desalination or other electricity dump H2RES – STORAGE MODULE – H2 USED
During peak hours (various definition) fuel cell is turned on using hydrogen stored until tank is empy
4000 3500 load renewable limit 3000 to electrolyser 2500 H2 produced H2 retrieved 2000 fuel cell kW 1500 1000 500 0 0 4 8 12 16 20 hours H2RES MODEL
Electricity delivered to power system
4000 3500 Diesel fuel cell 3000 renewable taken 2500 2000 kW 1500 1000 500 0 048121620 hours PORTO SANTO
Population: 5000 in winter ⇒ 20000 in summer PORTO SANTO
Power system (2000): 13.8 MW thermal + 1.1 MW wind 24.1 GWh thermal + 1.1 GWh wind 5.6 MW peak, 2 MW base, 20% growth PEAK SHAVING SCENARIA
Scenaria 1. Wind only 2. Wind as installed + solar
Up to 30% renewable at any time can be taken by power system
Excess to electrolyser
Fuel cell for peak shaving, optimised at 1.8% of electricity delivered PEAK SHAVING SCENARIA
3000 30000 wind 2500 solar 25000 electrolyser fuel cell 2000 storage vessel 20000 1500 15000 h kW kW 1000 10000 500 5000 0 0 Wind only Wind&solar PEAK SHAVING SCENARIA
solar excess desalination fuel cell wind ren. taken electrolyser ren. taken 30 30 30 ren. taken 30 Diesel Diesel Dies el Diesel
25 25 25 25
20 20 20 20 ] ] ] ] h h h h W W W W G G G G [ [ [ [ t 15 t 15 t 15 15 u ut u u p p p p t t t t ou ou ou ou 10 10 10 10
5 5 5 5
0 0 0 0 Wind only Wind&solar Wind only Wind&solar Wind only Wind&solar Wind only Wind&solar
peak serving time Wind only 53% Wind&solar 62% 100% RENEWABLE SCENARIA
Scenaria 1. Wind only 2. Wind + solar
Up to 100% renewable at any time can be taken by power system
Excess to eletrolyser + desalination
Fuel cell to cover load when no renewable available
Optimised on no Diesel 100% RENEWABLE SCENARIA
30 3 wind 25 solar 2.5 electrolyser fuel cell 20 storage vessel 2 15 1.5 h MW GW 10 1 5 0.5 0 0 Wind only Wind&solar 100% RENEWABLE SCENARIA
solar output excess desalination fuel cell w ind output ren. taken electrolyser ren. taken 70 70 70 ren. taken 70 Diesel Diesel Dies el Diesel
60 60 60 60
50 50 50 50 ] ] ] ] h h h h 40 40 W 40 W 40 W W G G G G [ [ [ [ t t t t u u u u p p p p t t
t 30 t 30 30 30 ou ou ou ou
20 20 20 20
10 10 10 10
0 0 0 0 Wind only Wind&solar Wind only Wind&solar Wind only Wind&solar Wind only Wind&solar
fuel cell serving time Wind only 37% Wind&solar 41% H2RES CONCLUSIONS
3000 30000 30 3 wind wind 2500 solar 25000 25 solar 2.5 electrolyser electrolyser 2000 fuel cell 20000 fuel cell storage vessel 20 storage vessel 2 h h 1500 15000 15 1.5 kW kW MW GW 1000 10000 10 1
500 5000 5 0.5
0 0 0 0 Wind only Wind&solar Wind only Wind&solar
For peak shaving wind&solar takes smaller storage and electrolyser
For 100% renewable better wind only CONCLUSIONS FOR PORTO SANTO
A model for optimising integration of hydrogen storage with intermittent renewable energy sources (wind and solar) was devised
Storage module can be upgraded to work with batteries or pump storage
The model was applied to Porto Santo
The results were intriguing AZORES ARCHIPELAGO ELECTRICITY PRODUCTION, STORAGE AND USE
WIND END SOLAR USERS PHOTOVOLTAIC
Electricity
Storage
H2 or Batt OBJECTIVES OF THE WORK
To look at ways to increase the penetration of Renewable Energy Sources in Corvo and Graciosa Islands
To test the potentiality of the developed H2RES model devoted to this kind of work.
To build and fully model scenaria for the Corvo and Graciosa islands to increase security of supply, and reduce pollution, based on existing load and meteorological data and envisaging the following technologies: wind, solar PV, and batteries and hydrogen storage. THE TARGET ISLANDS FOR THE CASE STUDIES
SCENARIA FOR GRACIOSA ISLAND
MG.1 - An already planned enlargement by the local utility (EDA) of the wind park up to 530 kW with an imposed wind energy limit of 30% of the “instant” load in the system. MG.2 - The same conditions as in MG.1 + 2,000 m2 of installed PV. MG.3 - 30% RE contribution: wind power 1,200 kW, no restrains on the percentage of renewable energy with variable output placed into the grid. MG.4 – 45% RE contribution to the annual consumption: 1,200 kW of wind power + 20000 m2 of PV, in the same conditions as in MG.3. MG.5 – 100% RE penetration: 9,000 kW of wind power + electrolyser with 8,900 kW power + 74 days hydrogen storage + fuel cell 1,600 kW power, allowing no renewable energy excess in the system. MG.6 - 100% RE penetration: 5,000 kW of wind power + 80,000 m2 of PV + electrolyser with 8,500 kW power + 31 days hydrogen storage + fuel cell 1,750 kW power, allowing no renewable energy excess in the system. RESULTS FOR GRACIOSA ISLAND
MG. 1 MG. 2 (30% limit) (MG.1 + 2000 M2 PV)
Wind (kW) 530 530 Solar (kWp) 0 170 Renewable (kW) 530 700 RESULTS FOR GRACIOSA ISLAND
MG. 1 MG. 2 (30% limit) (MG.1 + 2000 M2 PV) Wind output (GWh) 1.3 1.3 Solar output (GWh) 0 0.2 Ren. output (GWh) 1.3 1.5
Ren. taken (GWh) 1.1 1.2
Dump (GWh) 0.2 0.3 RESULTS FOR GRACIOSA ISLAND
1600 1400
1200 renewable limit 1000 load 800 renewable output kW 600 renewable taken renewable excess 400 200 0 1 4 7 22 10 13 16 19 Hours
MG.1 simulation, January 1 RESULTS FOR GRACIOSA ISLAND
1600 1400 1200 1000 Renewable taken 800 KW Diesel 600 400 200 0 1 4 7 19 22 10 13 16 Hours
MG.1 simulation, January 1. The source of electricity taken by the power system. RESULTS FOR GRACIOSA ISLAND
MG. 3 MG. 4 (30% RE ) ( MG. 3 + 45% RE) Wind (kW) 1200 1200 Solar (kWp) - 1700 Renewable (kW) 1200 2900
Wind output (GWh) 2.8 2.8
Solar output (GWh) - 1.7
Ren. output (GWh) 2.8 4.5
Ren. taken (GWh) 2.7 4.0
Dump (GWh) 0.1 0.5 RESULTS FOR GRACIOSA ISLAND
MG. 5 MG. 6 (100% RE) (100% RE) Wind (kW) 9000 5000 Solar (kWp) - 6800 Renewable (kW) 9000 11800
Electrolyser (kW) 8900 8500
Storage vessel (GWh) 2.8 1.3
H2 storage (days) 74 31
Fuel cell (kW) 1600 1750 RESULTS FOR GRACIOSA ISLAND
MG. 5 MG. 6 (100% RE) (100% RE) Wind output (GWh) 22.4 11.8 Solar output (GWh) - 6.9 Ren. output (GWh) 22.4 18.7 Ren. taken (GWh) 5.8 6.3 Electrolyser (GWh) 16.6 12.4 Dump (GWh) 0 0 Fuel cell (GWh) 3.2 2.8 Fuel cell serving time 45 % 40 % (%) RESULTS FOR GRACIOSA ISLAND
10000 9000 8000 to electrolyser 7000 H2 produced 6000 H2 retrieved 5000 fuel cell kW 4000 load 3000 RE output 2000 RE taken 1000 0 1 4 7 22 10 13 16 19 Hours
MG.5 simulation, January 1, for this particular day more hydrogen is stored than retrieved RESULTS FOR GRACIOSA ISLAND
3000000
2500000 h
W 2000000 , k d
e 1500000 r o t
s 1000000 2 H 500000
0 1 24 48 71 95 189 212 236 259 283 307 330 354 118 142 165 da y
MG.5 simulation, hydrogen stored during the year CONCLUSIONS FOR GRACIOSA ISLAND
The choice among the different scenaria depends mainly on comparing the costs of PV installation and of the hydrogen storage and on the available space.
Due to actual high cost of PV, the scenaria involving only wind seems to be preferable. SCENARIA FOR CORVO ISLAND
MC.1 – 60% re contribution to the annual consumption: 6,500 m2 PV + 150 kW (18h) battery power, no restrains on the percentage of renewable energy with variable output placed into the grid. MC.2 – 80% re contribution: 10,000 m2 PV + 150 kW (36h) battery power, in the same conditions as MC.1. MC.3 - 100% RE penetration: 25,000 m2 PV + 170 kW (6 days) battery power MC.4 - 75% RE contribution: 300 kW wind power, Pão de Açucar, + reversible hydro power plant (RHPP, 150 kW pump, 150 kW turbine, 2x2000 m3 reservoir). MC.5 - 96% RE contribution: 300 kW wind power, Morra da Fonte, + RHPP (100 kW pump, 150 kW turbine, 2x2000 m3 reservoir). RESULTS FOR CORVO ISLAND
300
250 to storage 200 retrieved from batt electricity from batt 150 kW load 100 RE output RE taken 50
0 1 4 7 22 10 13 16 19 Hours
MC.2 simulation, January 1 RESULTS FOR CORVO ISLAND
160 140 120 100 RE taken 80 Diesel kW 60 from bat teries 40 20 0 1 3 5 7 9 19 21 23 11 13 15 17 Hours
MC.2 simulation, January 1, the source of electricity taken by the power system. RESULTS FOR CORVO ISLAND
10% Diesel 25% hydro 14%
hydro wind wind 13% 62% 76%
MC.4 Pão de Açucar MC.5 Morra da Fonte CONCLUSIONS FOR CORVO ISLAND For a small energy system, very high intermittent RE penetration can only be reached by energy storage. PV needs large area – might be unacceptable for Corvo. Morra da Fonte – excellent location for wind turbine, possible to achieve 90% RE penetration with 300 kW wind – need for MT grid connection. Pão de Açucar – needs more study – with 300 kW wind turbine hard to achieve more than 75% RE penetration ISOLATED RURAL AREAS ISOLATED RURAL AREAS
Variable energy demands (tourism)
Low degree of grid connection
Protected environments
Dificult accessibility for maintenance
High installation costs due to remoteness GREEN HOTEL
Integrating Self Supply Into End Use For Sustainable Tourism INTEGRATED ENERGY SYSTEM
Natural Environment
Utilization
Wind Solar Thermal Solar PV Natural Ventilation Power Plant
Grid Day lighting (backup)
Fuel Cell Electrical LPG Lighting Computers, Energy and others... “W aste” Heat
Chilled Water Cooling Hot Water Absorption “Waste” Heat Cold Desiccant Cooling
Boiler Domestic Hot Water LPG (backup) Heat and Water Mullion INTERFACE NETWORK / RES
Community Needs
PRES > Consumption Send to the grid
Grid RES PRES < Consumption Taken from the grid INTEGRATED WATER SYSTEM
RES Sea water Rain water catchment Runoff collecting V
r P Pumping a
Sol Roofs Watershead Landscape (Impermeable management Treatment surfaces)
Wind PP Desalinisation Fresh Runoff water water
Storage Storage e s
U Hotel & Boats and Marina Irrigation car washing End
Storage Dried material Agriculture Compost
Sun Sewage Treatment Solid Sludge (to dry) INTEGRATED MOBILITY PLAN
Solar Trolleys and Cars
GPL Taxis and Fuel Cell Bus Fuel Cell bikes ... to go for a ride
Funchal Airport Green Hotel
Taxi boat ...between Funchal and the Hotel VIEW OF THE HOTEL AND MARINA RURAL TOURISM IN ALENTEJO (EDEN PROJECT) RURAL TOURISM IN ALENTEJO
Photovoltaic
Sun
Alentejo Solar heater Heat
Wind Turbine Electricity Fuel cell
Wind
Gasifier Electrolysis
Hydrogen storage Reforming
Biogas Biomass NON-ISOLATED URBAN AREAS NON- ISOLATED (URBAN) AREAS
Innovative approach for increasing RES awareness in Communities
New opportunities for showcase projects involving industry and consumers
Opportunities for residential communities
Integrate the users of energy services in the production MADEIRA TECNOPOLO (EDEN PROJECT) MADEIRA SCIENCE AND TECHNOLOGY PARK Photovoltaics
Sun
Solar Heaters Heat Park Tower
Electricity Fuel cells
Electrolysis Hydrogen storage Reforming
GPL TAGUS PARQUE (EDEN PROJECT) TAGUS PARQUE TAGUS PARQUE
Heat Tagus Park Electricity Fuel cells
Photovoltaics Electrolysis Hydrogen storage
Reforming
Sun GPL CONCLUSIONS
Combine diverse (renewable) energy sources and technologies to resolve in an integrated way the problems of energy, water and residues Î Integrated solutions
Better integration between suply and demand
Island and remote regions as pioneers of zero emission society (e.g. Iceland), following the prophecy of Jules Verne in “L'Île mystérieuse”. FINANCING INSTITUTIONS
European Commission
DG Research
DG Tren
Direcção Geral de Energia – Portugal
Ministério da Ciência e Tecnologia - Portugal