Energy conversion - DNE21+
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| Institution | Research Institute of Innovative Technology for the Earth (RITE), Japan, http://www.rite.or.jp/en/. |
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DNE21+ model covers various type of energy conversion technologies, including electricity generation, coal gasification and liquefaction, natural gas reforming, and carbon dioxide capture, storage and sequestration (CCS) for energy conversion process.
Electricity
The modeled electricity generation options include: Coal power {low efficiency (subcriticality), mid-efficiency (supercriticality), high efficiency (extra supercriticality?IGCC/IGFC), and IGCC with pre-combustion CO2 capture}, Oil power {low efficiency (diesel generator, etc.), mid-efficiency (subcriticality), high efficiency (supercriticality), and CHP}, Synthetic oil power {mid efficiency, and high efficiency}, Natural gas power {low efficiency (steam turbine), mid-efficiency (conventional NGCC), high efficiency (high temperature NGCC), CHP, and oxy-fuel combustion}, Biomass power {low efficiency, and high efficiency}, Nuclear power {conventional, and next-generation (Generation IV, etc.)}, Hydro/geothermal power, Wind power, and Photovoltaics. In association with generation technologies, Power storage system for wind/PV, Hydrogen power, Electrical cable {conventional, superconducting high efficiency}, and CCS {post-combustion capture; applicable for coal, oil, synthetic oil, natural gas, biomass power} are also represented in DNE21+.
As shown above, each type of power generation technology has is classified according to level of energy efficiencies and facilities costs are differentiated corresponding to the level of efficiency. The different levels of generation efficiencies are assumed in order to represent the broader ranges in current generation efficiency levels in different countries (see Oda et al. 2012). Their technological progresses are assumed exogenously. Table 3 shows the assumptions on capital costs and the efficiency of electricity generation. Fossil fuel prices are endogenously determined within the model by using the relationship between the cumulative production of fossil fuels and production costs. However, the fossil fuel prices will be dominated not only by production prices, but also by speculation, etc. Therefore, the baseline fossil fuel prices are calibrated to meet the prices of the reference scenarios of the IEA WEO 2010 (IEA 2010b) over the assessment time periods, while the prices in the mitigation scenarios are endogenously determined by the cumulative amounts of production induced by levels of emission reductions or the MAC. DNE21+ also tracks investments by vintage capital stock.
55902795.png Table 3 Capital costs and generation efficiency
- Some of capital costs and efficiency are shown in a range because they change over time.
Electricity demand is modeled in a way that demand-supply is balanced. The demand is expressed by the load duration curves, representing four time periods, instantaneous peak, peak, intermediate, and off peak time periods, in accordance with the level of electricity demand. This enables appropriate evaluation of electricity system corresponding to the characteristics of individual power generation technologies such as the base power load power plants and the peak load power plants.
For nuclear power generation, exogenous scenarios are assumed for nuclear power generation up to 2030. Some constraints are assumed that the power generation of nuclear would be capped at 50% of the total power generation amount and that an annual expansion of conventional nuclear power generation would be 0.33%, and the expansion rate of advanced nuclear power generation would be 1%. As long as the constraints are obeyed, costs-efficient options are selected by the model.
==Other conversion==
Besides electricity and heat generation there are three further subsectors of the conversion sector represented in DNE21+, such as oil refinery, natural gas liquefaction, coal gasification, and water electrolysis, methanol synthesis.
Grid and infrastructure
Inter-regional energy transmission infrastructure, such as pipelines for liquid and gas, such as oil, natural gas, synthetic oil, ethanol, hydrogen and CO2, and power grids, are represented in the DNE21+ model.
In terms of systems integration, wind power and solar PV are represented in the DNE21+ model as follows:
(1) Capacity credit:
There are some literatures that evaluate capacity credits of wind power in the United States and Europe (e.g., Milligan and Poter 2008, Holttinen et al. 2009). The estimated capacity credits of wind power vary widely from approximately a few percent to 40% by region. It is also observed that there is a correlation between the capacity credit and the level of technology penetration: the capacity credit becomes lower in higher wind power penetration. When the share of wind power capacity in peak load is 30%, the capacity credits of wind power range from 5% to 25% (Holttinen et al. 2009). In addition, the methods used for the evaluation of the capacity credit exist widely by region, such as capacity factor in peak period and equivalent load carrying capacity.
For solar PV, GE Energy (2010) reported that the capacity credit of solar PV is higher than that of wind power according to the study by the WestConnect group in the United States. In Japan, the capacity credit of solar PV in summer is considered as 16% (Japanese government committee on electricity supply and demand 2013). However, available studies that evaluate the capacity credit of solar PV are limited compared with wind power.
In the DNE21+ model, capacity credit is defined as potential power supplies from wind power and solar PV without electricity storage at the instantaneous peak. Since the peak of these generation does not always match the instantaneous peak time period of power demand, the output of wind power generation at instantaneous peak time is constrained in the model. The capacity credit of wind power is assumed to be 10% in all regions. Although the physical situation for solar and wind energy is different, the same assumption with wind power is applied to solar PV in this paper.
(2) Grid stability
Capacities of wind power and solar PV without electricity storage are limited for the grid stability. In DNE21+, maximum shares in the total electricity supply are 10% both for wind power and PV without electricity storage. Electricity storage systems on the demand side are required for wind power and solar PV to be installed over that shares. If wind power and solar PV are deployed with electricity storage, further 20% of the total electricity supply are available from wind power and solar PV as additional capacities. The capital cost of electricity storage is exogenously assumed to be 1600$/kWh (2005) ? 40$/kWh (2050), presuming rapid technology progress for electricity storage.
Theoretically, the maximum share of wind power and solar PV together in the total electricity generation reaches 60% (10% for wind power without storage, 20% for wind power with storage, 10% for solar PV without storage and 20% for solar PV with storage). The recent large regional wind integration studies in the United States (Milligan et al. 2009) have evaluated wind energy generates up to 30% of annual energy demand. The outlook of electricity generation shares of wind power and solar PV is16% and 20% in 2020 and 2030, respectively, in EU according to the EC communication (EC 2010). The assumed total maximum share is suitable level for energy system assessment until 2050 considering these targets.
The water electrolysis for hydrogen production by photovoltaics has no upper limit, (naturally restrictions on supply of natural resources should be treated separately).