Influence of storage technologies’ cost development on the economics of power transmission grids Dmitrii Bogdanov and Christian Breyer Lappeenranta University of Technology, Skinnarilankatu 34, 53850 Lappeenranta, Finland E-mail:
[email protected],
[email protected]
Motivation & Purpose of Work
Main Objectives
Grid integration for renewable energy (RE) is in many studies observed as the major option to increase energy system reliability and decrease costs: overflows in the grid can support the system in case of component failure and decrease the need for balancing capacities.
• Define effects of large-scale power grid integration on: o Electricity cost o Electricity losses in the system o Storage capacities and operation o Transmission grid capacities and operation o System RE energy sources capacities mix and total installed capacities
Energy transmission grids additionally increase capacity utilisation and efficiency by smoothing of total demand, especially for geographically wide expanded grids. Wherefore it had been often assumed that a development of close to 100% RE systems may be only possible with the installation of extended power grids. In this work it is investigated the research question on the impact of different grid integration levels on the RE based system for different levels of storage technologies cost development.
LUT Energy Model Scenarios for this work simulated using LUT energy model
• Examine the change of grid impact on the system for different storage cost levels for different grid development levels • Define optimal parameters of storage and transmission capacities in the long term
Fig. 1: Block diagram of the energy system model elements
Simulation Scenarios
Scenarios Assumptions
Results (Key Numbers) Cost year 2020
Area-wide open trade
Region-wide open trade
Country-wide open trade
Area-wide open trade
Total LCOE
[€/MWh]
78
73
72
61
59
58
Total LCOE reduction
[%]
0
7
9
0
4
5
LCOS
[€/MWh]
18
13
11
16
13
13
LCOT
[€/MWh]
0
3
3
0
1
2
RE capacities
[GW]
5756
5144
Generated el.
[TWh]
11634 11475 11420 11835 11630 11568
PV generation share
[%]
49
41
39
56
51
50
Wind gener.
[%]
39
46
49
32
37
39
[%]
0
-23
-30
0
-17
-21
[%]
0
-39
-63
0
-19
-25
[%]
0
12
14
0
7
9
For every sub-region are defined: • historical weather data for: solar irradiation, wind speed and hydro precipitation. • available sustainable resources for biomass, geothermal energy and A-CAES caverns. • synthetic load data for every sub-region • efficiency/yield characteristics of RE plants • efficiency of energy conversion processes • capex, opex, lifetime for all energy resources • min and max capacity limits for all RE resources • nodes and interconnections configuration • gas and water desalination demand
A-CAES cap. change PtG cap. change Grid exchange
Fig. 2: Northeast Asian regional stratification and grid configuration
Results (Storage Mix)
Country-wide open trade
• Three scenarios simulated: • Region-wide energy systems; • Country-wide energy systems; • Area-wide energy system.
Input data
Region-wide open trade
• Effects of large-scale flexible demand integration observed for Northeast Asia (is comprised of 13 sub-regions similar to [1])
Cost year 2030
Results (Grid Utilisation)
5008 5926 5545 5456
Conclusion • Storage technologies cost development has a significant effect on the grid operation: o o o o
lower LCOE, reduced role of transmission grids, electricity import substituted by local generation, shift from wind based to PV based energy system.
• For all scenarios, the share of indirect energy supply (storage and grid) is around 30%. • Grid integration leads to decrease in RE capacities generations and capacities because of lower losses and curtailment. • Storage technologies cost progress leads to a change in the capacities mix and grater RE installed capacities, mainly induced by higher storage losses compared to grid losses. Acknowledgements The authors gratefully acknowledge the public financing of Tekes, the Finnish Funding Agency for Innovation, for the ‘Neo-Carbon Energy’ project under the number 40101/14.
Fig. 3: Structure of regional storage generation for the area-wide scenario for the year 2020 (top) and 2030 (bottom).
Fig. 4: Share of energy from grid in total regional energy consumption for the year 2020 (top) and 2030 (bottom) for the area-wide scenario.
References [1] Bogdanov D. and Breyer Ch., 2016. North-East Asian Super Grid for 100% Renewable Energy supply: Optimal mix of energy technologies for electricity, gas and heat supply options, Energy Conversion and Management, 112, 176-190.
