International Workshop on Mini-Grids Berlin, Germany, 19 th March 2014 Challenges during the system design and risk minimization: Demand forecast and possibilities of standardization Alexandre Pineau Xavier Vallvé -Trama TecnoAmbiental, Barcelona,Spain alex.pineau@tta.com.es
Member of: 1. TTA in brief
Trama TecnoAmbiental (TTA) SME Founded in Barcelona en 1986 Independent Consultants in distributed Renewable Energy Consultancy, engineering, research, project management, social aspects, financial, Since 1987: Off-grid rural electrification practitioners Design and Project management of RE-hybrid micro-power plants and micro grids for rural electrification in southern Europe, Africa, Latin America, Oceania Member of:
Pioneer experience in rural micro-grids Akane (Morocco) Font:TTA Font:TTA Santo Antâo (Cape Verde) Chad Font:TTA Cal Peraire (Spain) Font:TTA 2005 2006 2007 2009 2012 2013 2002 Font:TTA Font:TTA Las Balsas (Ecuador) 1997 Atouf (Palestine) 1994 Font:TTA Escuain (Spain) Beni Said (Morocco) Beginning: Country house electrification (Spain) Font:TTA Font:TTA Diakha Madina (Senegal) Font:TTA
2. What s a micro-grid: advantages and shortcomings Member of:
Micro-grid with Solar Generation (MSG) - definition - Electricity generation based on renewable energies or hybrid(re + genset) Steady village-level electricity service, offering also the possibility to be upgraded to either more capacity, clustering or interconnection Installed capacity up to 100 kw (according to IEC) Distribution grid in Low Voltage Single or 3-phase grid Under one operational scheme PV Hybrid Micro Grid in West Bank, Palestine Challenge: sharing the energy available without conflicts Need comprehensive experience in technical and management levels with multidisciplinary skills Need innovative approach to energy distribution and metering!
3. Demand characterization: Risks and challenges Member of:
Demand characterization challenges in rural micro grids Social Aspects: - to identify the different energy needs (basic, productive, deferrable, etc) and to ensure a resource distribution without conflicts Individual energy demand management: - to encourage the consumption during surplus RE generation periods - to manage each user s energy in an independent and flexible way - to guide users energy consuming habits to optimize energy management Techno-economic long term sustainability: - to reduce uncertainty on revenue and unpaid fees - to ensure that batteries, inverters etc. will operate within design range - to plan for load growth (clustering, scale up, interconnectability)
Demand characterization main risks Social Aspects: - Not all the users have the electricity - Users should be able to pay the tariff (considering costs) - Acceptance from the users - User are not expert to estimate their current and future energy needs Techno-economic risks: - Stress on the batteries - Black-outs - Increase diesel consumption and operation costs - Over sizing: Not enough revenues to ensure the sustainability of the project
Member of: 4. Demand characterization: methodologies
Demand characterisation 1. ASSESS THE ENERGY DEMAND THROUGH SURVEYS and QUESTIONNAIRES Objectives To obtain the necessary data for the power plant design To influence on the consumption rationalization Problem The users are not experts The current and future demand estimation is the most important step of the design Methodology To enable the user his demand requirements To consider socio-economic data
Demand characterisation 2. ENERGY EFFICIENCY APPROACH Three mechanisms that enable the energy savings without loosing the quality of the service Mechanisms of demand management optimization Diversification of energy sources (where applicable) Use of efficient appliances (where applicable)
usuarios % del total usuarios % del total Demand characterisation 3. COMPARATIVE DEMAND CHARACTERISATION Assessment of load categories based on data analysis of similar villages El Ayote: 12.733 kwh / 485 us. - Bocay: 17.766 kwh / 465 us. - Huacaraje: 3.508 kwh / 215 us. - Baures: 11.357 kwh / 258 us. - El Cuá: 15.601 kwh / 526 us. 25% Pefil consumo para uso doméstico, servicios, pequeña industria (<200 kwh/mes) 35% 20% 30% 25% 20% El Ayote Bocay Huacaraje Baures El Cuá 15% 10% 15% 5% 10% 5% 0% 0% 3,5 14 24,5 35 45,5 56 66,5 77 87,5 98 108,5 119 129,5 140 Rangos de consumo mensual(kwh) Rangos de consumo mensual (kwh)
Member of: 5. Construction of normalized load profiles
Normalized yields Typically registers of energy [Wh] are normalized dividing by the PV capacity at STC in order to represent on a same scale all PV plants.
Normalized reports
Load profile analysis For each site we have hourly registers of the load
Demand Segmentation We group the consumers according to energy daily demand and load profile category Type of use Essential consumption characteristics Probable needed power Average energy over 24h Category A Category B Category C Category MSG Individual basic very low and low energy consumption (lighting and audio/video). Low number of receivers Low power of receivers Slim rigid load profile (P1) Individual medium services (same as category 1 + freezer or refrigerator and appliances) Or community services (health care centre: lighting and freezer, etc.) Medium number of receivers Receivers more powerful Slim rigid and base load profiles (P1+P2+P3) or Multiple basic users (P1+P1+.. n) Individual high services (same as category 2 + washing machine, vacuum cleaner, odd jobs, etc.) Or public lighting High number of receivers Some receivers are powerful High instantaneous power inrush "Variable load profile (P1+P2+P4+P5) or Multiple users (P1+P1+P2+.. N) Multi-user micro grid with aggregate of individual and community loads of category A, B and C Powerful receivers High instantaneous power inrush P 100 W 0,1 kw < P < 1,5 kw 0,5 kw P < 3 kw P 3 kw Many users some with "Variable load profile (P1+P2+P4+P5) E 1000 Wh/d E 2kWh/d 2,2 kwh/d < E < 5 kwh/d E < 50 kwh/d
Types of loads -1 1 Daily cycle 25% 20% 15% 10% 5% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Types of loads 2a 2a Base Load 25% 20% 15% 10% A+ 5% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Types of loads 2b 2b Base Load Interruptible 25% 20% A+ 15% 10% 5% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Types of loads 2c 2c Base Load Stand-by 25% 20% 15% 10% 5% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Types of loads - 3 3 Daily Deferrable 25% 20% 15% 10% 5% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Types of loads - 4 4 Periodical Deferrable 25% day 1 day 2 20% 15% 10% 5% 0% 1 5 9 13 17 21 1 5 9 13 17 21
Types of loads - 5 5 Dump or ballast 25% 20% 15% 10% 5% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Daily average normalized Load Profiles SAMPLES CATEGORY A Sample of 90 households (Morocco, Ecuador and Palestine) 25% 20% 15% 10% Sample 1 Sample 2 Sample 3 Sample 4 5% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Daily average normalized Load Profiles (IDEALIZED) CATEGORY A 20% 18% 16% 14% 12% 10% 8% 6% 4% 2% A Category A Idealized V bat/cell V bat/cell 2,60 2,50 2,40 2,30 2,20 2,10 2,00 1,90 1,80 1,70 1,60 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1,50
Daily average Load Profiles SAMPLES CATEGORIES B and C Sample of 15 households (Senegal and Spain) 16% 14% 12% 10% 8% 6% 4% Sample 1 Sample 2 Sample 3 Sample 4 Sample 5 Sample 6 Sample 7 Sample 8 Sample 9 Sample 10 Sample 11 Sample 12 Sample 13 2% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
7% 6% 5% 4% 3% 2% 1% Daily average normalized Load Profiles (IDEALIZED) CATEGORY B and C B Category C Category B-C Idealized Vbat bat/cell V bat/cell 2,60 2,50 2,40 2,30 2,20 2,10 2,00 1,90 1,80 1,70 1,60 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 1,50
6. Tools for system design and risk minimization Member of:
Load Management issues User information interface + training Automatic total load disconnect Automatic selective load switching Individual Energy Daily Allowance (in micro grids)
Tariff Schemes for energy management Financial Sustainability : Tariffs designed to ensure enough revenues to cover its M&O&M, replacement and unforeseen costs and, including or not, pay-back of investment Tariff schemes: -Flat (forfait) -Power-based -Energy-based -Service-based -Combination of above
Innovative concept: Service based - Energy Daily Allowance (EDA) Traditionally in conventional grid connection: users pay for consumed kwh In autonomous electrification with RE: Key aspect is the constrain on available energy In RE electricity, user should pay for availability not for the consumed energy Tariff based on the Energy Daily Allowance (fee for service prepayment) Clearer and easier financial planning for operator and for client It reduces transaction costs because of flat fees
Member of: 7. Output of a demand-side management
Effect of individual Load Management 6% 5% 4% 3% 2% 1% 0% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 2a Base Load 1 Daily Cycle 3 Daily Deferrable
Effect of individual Load Management Wh/d 2600 2400 2200 2000 1800 1600 1400 1200 SL05028 1000 0 1 2 3 4 5 6 7 8 Hp Spring Summer Autum Winter DD (Wh) Spring-06 Summer-06 Autum-06 Winter-07
8. Example of a system design: Cape Vert micro-grid Member of:
Case study of PV rural micro grid in Africa Monte Trigo, Cape Verde Site: Monte Trigo, 17º01 N, 25º19 O, 00 m s.l. 38
Demand characterization Monte Trigo community: - 56 families - 1 school - 1 health center - 1 street lighting - 1 periodical deferrable load: ice machine MSG daily load aggregate load profile:
RURAL RE MICROGRID ( kwh/day PV GENERATOR Installed PV capacity 27 300 Wp Module type 130 Wp 36 cell mono crystalline Number of modules 210 Inclination / orientation 15º / +20º S PV CHARGE CONTROLLER Rated power 2x12 000 Wp Control algorithm MPPT - Boost BACK UP GENSET Rated power 20 kva 3- phases Fuel Diesel BATTERY Number of elements (voltage) 24 (48V)X2 Type Lead acid OPzS tubular Capacity (C100) 3 850 Ah 370 kwh Autonomy 4 days INVERTER Voltage input / output 48 V DC / 230 V AC Rated power 2 X 8 000 W Harmonic distortion < 2,5% DATA LOGGER Type of data Energy, voltage, radiation, etc. ELECTRICITY DISPENSER METER Input 230 V AC 50 Hz Maximum current Configurable Algorithm Configurable Energy Daily Allowance DISTRIBUTION LINE AND STREET LIGHTING Line Length 800m Number of lamps 20 Type 70 W hp Na / 2 level electronic ballast INDIVIDUAL LOADS Households 825 Wh/day 20 Households 1100 Wh/day 18 Households 1650 Wh/day 14 Households 2200 Wh/day 6 School 1650 Wh/day 1 Ice machine 4200 Wh/day 1
Electricity Dispenser/meter Single phase electric meter with dispenser functions Main Current Switch (40A): Energy Daily Allowance (EDA) management according to the contracted tariff Virtual storage of saved energy: 6 x EDA Programmable power limitation Auxiliary Smart switch (5A): for deferrable loads Smart RFID card for: Tariff management Energy swapping between users Invoicing management Certified energy meter
The EDA algorithm As an analogy, we can imagine the dispenser as a buffer water tank The tank gets a constant trickle inflow from the micro-grid proportional to the contracted energy daily allowance The tank empties as energy is consumed When the consumption is equal to the fill up rate we are in balanced consumption The tank has a capacity equivalent to 3 days of energy daily allowance You can use this energy anytime but you cannot store more units than the tank s capacity
Added value solution: deferrable consumptions
Added value solution: Engage the users
Technical solution: User interface
Sustainability: Users and up keepers training
Monitoring the results: Normalized Performance indicators Stable daily aggregate load (red bars) Battery state of Charge (red line) always between 85% and 95%
Added value solution: Scalable 2013 2012
Thanks for your attention! alex.pineau@tta.com.es xavier.vallve@tta.com.es