Refine
Year of publication
Document Type
- Article (43) (remove)
Keywords
- Variable renewables (7)
- Centre for Sustainability (5)
- Wind power (5)
- Solar power (4)
- Cost-benefit analysis (2)
- Integrated assessment modeling (2)
- Integration costs (2)
- renewable energy sources (2)
- Balancing power (1)
- CO2 capture and storage (1)
The expansion of wind and solar power is creating a growing need for power system flexibility. Dispatchable power plants with CO2 capture and storage (CCS) offer flexibility with low CO2 emissions, but these plants become uneconomical at the low running hours implied by renewables-based power systems. To address this challenge, the novel gas switching reforming (GSR) plant was recently proposed. GSR can alternate between electricity and hydrogen production from natural gas, offering flexibility to the power system without reducing the utilization rate of the capital stock embodied in CCS infrastructure. This study assesses the interplay between GSR and variable renewables using a power system model, which optimizes investment and hourly dispatch of 13 different technologies. Results show that GSR brings substantial benefits relative to conventional CCS. At a CO2 price of €100/ton, inclusion of GSR increases the optimal wind and solar share by 50%, lowers total system costs by 8%, and reduces system emissions from 45 to 4 kgCO2/MWh. In addition, GSR produces clean hydrogen equivalent to about 90% of total electricity demand, which can be used to decarbonize transport and industry. GSR could therefore become a key enabling technology for a decarbonization effort led by wind and solar power.
With the growth of wind and solar energy in electricity supply, the electrification of space and water heating is becoming a promising decarbonization option. In turn, such electrification may help the power system integration of variable renewables, for two reasons: thermal storage could provide low-cost flexibility, and heat demand is seasonally correlated with wind power. However, temporal fluctuations in heat demand may also imply new challenges for the power system. This study assesses the economic characteristics of electric heat pumps and wind energy and studies their interaction on wholesale electricity markets. Using a numerical electricity market model, we estimate the economic value of wind energy and the economic cost of powering heat pumps. We find that, just as expanding wind energy depresses its €/MWhel value, adopting heat pumps increases their €/MWhel cost. This rise can be mitigated by synergistic effects with wind power, “system-friendly” heat pump technology, and thermal storage. Furthermore, heat pumps raise the wind market value, but this effect vanishes if accounting for the additional wind energy needed to serve the heat pump load. Thermal storage facilitates the system integration of wind power but competes with other flexibility options. For an efficient adoption of heat pumps and thermal storage, we argue that retail tariffs for heat pump customers should reflect their underlying economic cost.
Locational Investment Signals: How to Steer the Siting of New Generation Capacity in Power Systems?
(2020)
New generators located far from consumption centers require transmission infrastructure and increase network losses. The primary objective of this paper is to study signals that affect the location of generation investment. Such signals result from the electricity market itself and from additional regulatory instruments. We cluster them into five groups: locational electricity markets, deep grid connection charges, grid usage charges, capacity mechanisms, and renewable energy support schemes. We review the use of instruments in twelve major power systems and discuss relevant properties, including a quantitative estimate of their strength. We find that most systems use multiple instruments in parallel, and none of the identified instruments prevails. The signals vary between locations by up to 20 EUR per MWh. Such a difference is significant when compared to the levelized costs of combined cycle plants of 64–72 EUR per MWh in Europe.
Upon discussion of price setting on electricity wholesale markets, many refer to the so-called merit order model. Conventional wisdom holds that during most hours of the year, coal- or natural gas-fired power plants set the price on European markets. In this context, this paper analyses price setting on European power markets. We use a fundamental electricity market model of interconnected bidding zones to determine hourly price-setting technologies for the year 2020. We find a price-setting pattern that is more complex and nuanced than the conventional wisdom suggests: across all researched countries, coal- and natural gas-fired power plants set the price for only 40 per cent of all hours. Other power generation technologies such as wind, biomass, hydro and nuclear power plants as well as lignite-fired plants set the price during the rest of the year. On some markets, the price setting is characterised by a high level of interconnectivity and thus foreign influence – as illustrated by the example of the Netherlands. During some 75 per cent of hours, foreign power plants set the price on the Dutch market, whilst price setting in other more isolated markets is barely affected by foreign markets. Hence, applying the price setting analysis to the proposed Dutch carbon price floor, we show that different carbon prices have little effect on the technological structure of the price-setting units. In this respect, the impacts of the unilateral initiative are limited. There are, however, considerable changes to be observed in wholesale power prices, import/export balances as well as production volumes and subsequent CO2 outputs of lignite-, coal- and gas-fired power plants.
Despite the importance of evaluating all mitigation options to inform policy decisions addressing climate change, a comprehensive analysis of household-scale interventions and their emissions reduction potential is missing. Here, we address this gap for interventions aimed at changing individual households’ use of existing equipment, such as monetary incentives or feedback. We have performed a machine learning-assisted systematic review and meta-analysis to comparatively assess the effectiveness of these interventions in reducing energy demand in residential buildings. We extracted 360 individual effect sizes from 122 studies representing trials in 25 countries. Our meta-regression confirms that both monetary and non-monetary interventions reduce the energy consumption of households, but monetary incentives, of the sizes reported in the literature, tend to show on average a more pronounced effect. Deploying the right combinations of interventions increases the overall effectiveness. We have estimated a global carbon emissions reduction potential of 0.35 GtCO2 yr−1, although deploying the most effective packages of interventions could result in greater reduction. While modest, this potential should be viewed in conjunction with the need for de-risking mitigation pathways with energy-demand reductions.
The hydrogen economy is currently experiencing a surge in attention, partly due to the possibility of absorbing wind and solar energy production peaks through electrolysis. A fundamental challenge with this approach is low utilization rates of various parts of the integrated electricity-hydrogen system. To assess the importance of capacity utilization, this paper introduces a novel stylized numerical energy system model incorporating the major elements of electricity and hydrogen generation, transmission and storage, including both "green" hydrogen from electrolysis and "blue" hydrogen from natural gas reforming with CO2 capture and storage (CCS). Balancing renewables with electrolysis results in low utilization of electrolyzers, hydrogen pipelines and storage infrastructure, or electricity transmission networks, depending on whether electrolyzers are co-located with wind farms or demand centers. Blue hydrogen scenarios face similar constraints. High renewable shares impose low utilization rates of CO2 capture, transport and storage infrastructure for conventional CCS, and of hydrogen transmission and storage infrastructure for a novel process (gas switching reforming) that enables flexible power and hydrogen production. In conclusion, both green and blue hydrogen can facilitate the integration of wind and solar energy, but the cost related to low capacity utilization erodes much of the expected economic benefit.
Frequency stability requires equalizing supply and demand for electricity at short time scales. Such electricity balancing is often understood as a sequential process in which random shocks, such as weather events, cause imbalances that system operators close by activating balancing reserves. By contrast, we study electricity balancing as a market where the equilibrium price (imbalance price) and quantity (system imbalance) are determined by supply and demand. System operators supply imbalance energy by activating reserves; market parties that, deliberately or not, deviate from schedules create a demand for imbalance energy. The incentives for deliberate strategic deviations emerge from wholesale market prices and the imbalance price. We empirically estimate the demand curve of imbalance energy, which describes how sensitive market parties are to imbalance prices. To overcome the classical endogeneity problem of price and quantity, we deploy instruments derived from a novel theoretical framework. Using data from Germany, we find a decline in the demand for imbalance energy by 2.2 MW for each increase in the imbalance price by EUR 1 per MWh. This significant price response is remarkable because the German regulator prohibits strategic deviations. We also estimate cross-market equilibriums between intraday and imbalance markets, finding that a shock to the imbalance price triggers a subsequent adjustment of the intraday price.
The European electricity industry, the dominant sector of the world’s largest cap-and-trade scheme, is one of the most-studied examples of carbon pricing. In particular, numerical models are often used to study the uncertain future development of carbon prices and emissions. While parameter uncertainty is often addressed through sensitivity analyses, the potential uncertainty of the models themselves remains unclear from existing single-model studies. Here, we investigate such model-related uncertainty by running a structured model comparison experiment, in which we exposed five numerical power sector models to aligned input parameters—finding stark model differences. At a carbon price of 27 EUR/t in 2030, the models estimate that European power sector emissions will decrease by 36–57% when compared to 2016. Most of this variation can be explained by the extent to which models consider the market-driven decommissioning of coal- and lignite-fired power plants. Higher carbon prices of 57 and 87 EUR/t yield a stronger decrease in carbon emissions, by 45–75% and 52–80%, respectively. The lower end of these ranges can be attributed to the short-term fuel switch captured by dispatch-only models. The higher reductions correspond to models that additionally consider market-based investment in renewables. By further studying cross-model variation in the remaining emissions at high carbon prices, we identify the representation of combined heat and power as another crucial driver of differences across model results.
Blue hydrogen and industrial base products: The future of fossil fuel exporters in a net-zero world
(2022)
Is there a place for today’s fossil fuel exporters in a low-carbon future? This study explores trade channels between energy exporters and importers using a novel electricity-hydrogen-steel energy systems model calibrated to Norway, a major natural gas producer, and Germany, a major energy consumer. Under tight emission constraints, Norway can supply Germany with electricity, (blue) hydrogen, or natural gas with re-import of captured CO2. Alternatively, it can use hydrogen to produce steel through direct reduction and supply it to the world market, an export route not available to other energy carriers due to high transport costs. Although results show that natural gas imports with CO2 capture in Germany is the least-cost solution, avoiding local CO2 handling via imports of blue hydrogen (direct or embodied in steel) involves only moderately higher costs. A robust hydrogen demand would allow Norway to profitably export all its natural gas production as blue hydrogen. However, diversification into local steel production, as one example of easy-to-export industrial base products, offers an effective hedge against the possibility of lower European blue hydrogen demand. Thus, it is recommended that hydrocarbon exporters like Norway consider a strategic energy export transition to a diversified mix of blue hydrogen and climate-neutral industrial base products.
Numerical optimization models are used to develop scenarios of the future energy system. Usually, they optimize the energy mix subject to engineering costs such as equipment and fuel. For onshore wind energy, some of these models use cost-potential curves that indicate how much electricity can be generated at what cost. These curves are upward sloping mainly because windy sites are occupied first and further expanding wind energy means deploying less favorable resources. Meanwhile, real-world wind energy expansion is curbed by local resistance, regulatory constraints, and legal challenges. This presumably reflects the perceived adverse effect that onshore wind energy has on the local human population, as well as other negative external effects. These disamenity costs are at the core of this paper. We provide a comprehensive and consistent set of cost-potential curves of wind energy for all European countries that include disamenity costs, and which can be used in energy system modeling. We combine existing valuation of disamenity costs from the literature that describe the costs as a function of the distance between turbine and households with gridded population data, granular geospatial data of wind speeds, and additional land-use constraints to calculate such curves. We find that disamenity costs are not a game changer: for most countries and assumptions, the marginal levelized cost of onshore wind energy increase by 0.2–12.5 €/MWh.