FLEXIBLE FUEL USE IN RENEWABLE THERMAL SYSTEMS - OPPORTUNITIES AND COSTS

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1 FLEXIBLE FUEL USE IN RENEWABLE THERMAL SYSTEMS - OPPORTUNITIES AND COSTS Monica Havskjold, Erik Trømborg (presenting author), Torjus Folsland Bolkesjø og Åsa Grytli Tveten RERC Session Renewable Energy Storage, June Norwegian University of Life Sciences 1

2 CONTENT Objectives and background of the Flexelterm-project Purpose of the study Premilinary results Way forward and questions Norwegian University of Life Sciences 2

3 Flexible interaction between the power market and thermal energy in the future energy system 3

4 The European and Norwegian energy systems are undergoing changes Increasing shares of variable renewable energy, ambitions to reduce energy consumption, increased transmission capacity at all levels: Challenges in load balancing, increased demand for short-run flexibility Increased transmission capacity will influence the Nordic power price structure Dry and cold years will continue to challenge the Nordic power market Uncertainty about CO2 prices and the role of nuclear power Periods with low power prices, more use of electricity for heating? Thermal systems can provide flexibility, but lack of incentives (?)

5 CENTRAL ISSUES IN FLEXELTERM Where and how should thermal energy be used in the future energy system? What are the opportunities of lower and more variable power prices for actors in the thermal sector? Should oil-burners be converted to heat pumps, electric boilers or biomass? Possibilities for CHP in Norway Future role of energy storage in thermal systems What are efficient policy means to secure needed flexibility and a robust energy system? How should energy and load be priced and supported? 5

6 WORKPACKAGES WP1: Technology development and choices WP2: Flexibility and interaction development of regional partial equilibrium model for the North European power and heat sectors (Balmorel) WP3: Policy means comparative studies and modelling 6

7 OBJECTIVES OF THIS STUDY Overall: Analyze how the flexibility provided by bio based heating systems is affected by different market conditions. More specifically, analyze how investment in boiler types, energy use and economic performance in district heating systems and local heating centrals are affected by factors such as (a) Electricity prices and grid tariffs (b) Start-up, investment and running costs of boilers (c) Structure of heat demand 7

8 METHODS Analyses of a model plant small scale district heating system Modelled in energypro simulation tool for daily operation and optimization Forecasts on the future electricity prices, and electricity price variations generated in the North European energy market model Balmorel and used as input in the energypro model Winter week 2025 from Balmorel 8

9 CASE Plant Boilers Gross heat production: 76 GWh/ 274TJ Max capacity: 25 MW Grid loss: 10% of delivered energy 15 MW wood chips (min 3 MW) 15 MW LPG-boiler 10 MW LPG-boiler Heat price (revenue): 95% av el-price (spot + grid tariff + el-specfic taxes) Demand 80% service sector 20% households Hourly data from 2012 Fuel prices (LH delivered plant) Bio: NOK 0.20 kwh -1 / 24.7 MWh -1 / 6.6 GJ -1 LPG: NOK 0.50 kwh -1 / 61.7 MWh -1 / 17.1 GJ -1 + CO 2 tax of 0,99 NOK/kg CO 2 = 122 mt- 1 El: Spot price + grid rent + el-specific tax of NOK kwh -1 /0.56 MWh - 1

10 Reference bio + LPG 85% 92% 92% Production: 76 GWh Delivered: 69 GWh Max capacity requirement (demand): 25 MW 10% grid loss (delivered energy) Local tariffs: Grid rent DH-prices Trondheim Oslo Kristiansand Stavanger Norwegian University of Life Sciences 10

11 Under which circumstances can increased use of electricity be profitable? Electricity boiler with capacity 10.5 MW Grid-tariff Hourly metering Immediate bypass/switch of by DSO if needed Low el-tax (NOK kwh -1 ) Tittel på presentasjon Norwegian University of Life Sciences 11

12 Grid tariffs Grid component Fixed component (NOK/år) Energy component summer/winter NOK kwh -1 Load tariff Summer/Winter NOK/Kw -1 Season Calculation of load tariff TrønderEnergi- Trondheim, , / /4.32 MWh (per year) 49,383 MW -1 No Max houry load last 12 month Hafslund Oslo , / /4.07 MWh -1 13/63 (per month) 1,605/7,778 MW -1 s: April-Oct v: Jan- March, Nov-Dec Max load per month Agder Energi Nett - Kristiansand 8.300, / /5.8 MWh -1 90/350 (per year) 11,111/43,210 MW -1 s: Mai-Oct v: Jan-April, Nov-Des Max load per month Lyse Nett - Stavanger ,- 2,00/ /3.74 MWh -1 0/33 (per month) 0/4,074 MW -1 s: April-Oct v: Jan-Mar, Nov-Dedc Max load per month Tittel på presentasjon Norwegian University of Life Sciences 12

13 NOK/MWh El-price, spot (sorted in ascending order) Hours Tittel på presentasjon Norwegian University of Life Sciences 13

14 Electricity costs vary by spot prices, grid tariffs and utilization factors Example Hafslund/Oslo January 2012 NOK/MWh Cost of electricity by utilization rate El-tax Grid-load Grid-energy Spot price Norwegian University of Life Sciences 14

15 Winter cases by grid tariff Hafslund January 2012 ex-ante Hafslund January 2012 ex-post expost if electric boiler is started in the given month NOK/MWh Cost produced heat NOK/MWh Cost produced heat Electricity Biomass LPG Electricity Biomass LPG Norwegian University of Life Sciences 15

16 Summer cases ex-ante Hafslund May 2012 Lyse May no load tariff NOK/MWh Cost produced heat NOK/MWh Cost produced heat Electricity Biomass LPG Electricity Biomass LPG Norwegian University of Life Sciences 16

17 energypro analyzes Priority to bio boiler Optimization based on «short run marginal cost» Optimization without Fix component Load tariff No other fixed and variable costs All costs are included in calculation of annual profit Tittel på presentasjon Norwegian University of Life Sciences 17

18 Varmeproduksjon (GWh) Varmeproduksjon (GWh) Results Reference without el: LPG as peak load and summer load when demand is below minimum load of bio boiler With el- possibility: LPG replaced by el. Highest consumption during summer 12 Referanse 12 Case LPG Bio 6 El-kjel Bio Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Tittel på presentasjon Norwegian University of Life Sciences 18

19 Pre-limenary conclusions Structure of grid-tariffs important for use of el and the flexibility Load tariffs imply minimum utilization per month, ex-ante decisions and limits the flexibility/use of electricity Optimization with load tariffs problematic in energypro Electricity replaces LPG (and oil) but to a limited extent biomass in existing boilers Norwegian University of Life Sciences 19

20 Future work Basis Price/weather Demand category Grid rent Storage Cold/dry (2010) Households Trønderenergi Wet (2012) Service Hafslund Future (2030) Mix (Trh) Lyse Nett Agder Energi nett Base scenario New structures

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