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With electric heat pumps substituting for fossil-fueled alternatives, the temporal variability of their power consumption becomes increasingly important to the electricity system. To easily include this variability in energy system analyses, this paper introduces the “When2Heat” dataset comprising synthetic national time series of both the heat demand and the coefficient of performance (COP) of heat pumps. It covers 16 European countries, includes the years 2008 to 2018, and features an hourly resolution. Demand profiles for space and water heating are computed by combining gas standard load profiles with spatial temperature and wind speed reanalysis data as well as population geodata. COP time series for different heat sources – air, ground, and groundwater – and different heat sinks – floor heating, radiators, and water heating – are calculated based on COP and heating curves using reanalysis temperature data. The dataset, as well as the scripts and input parameters, are publicly available under an open source license on the Open Power System Data platform.
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.
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.
Electricity is a peculiar economic good, the most important reason being that it needs to be supplied at the very moment of consumption. As a result, wholesale electricity prices fluctuate widely at hourly or sub-hourly time scales, regularly reaching multiples of their average, and even turn negative. This paper examines whether the demand for electricity responds to such price variations in the very short term. To solve the classical identification problem when estimating a demand curve, we use weather-driven wind energy generation as an instrument. Our robustness checks confirm that wind energy is indeed a strong and valid instrument. Using data from Germany, we estimate that a 1 €/MWh increase in the wholesale electricity price causes the aggregate electricity demand to decline by 67–80 MW or 0.12–0.14%, contradicting the conventional wisdom that electricity demand is highly price-inelastic. These estimates are statistically significant and robust across model specifications, estimators, and sensitivity analyses. At average price and demand, our estimates correspond to a price elasticity of demand of about –0.05. Comparing situations with high and low wind energy (5–95th percentile), we estimate that prices vary by 26 €/MWh, and the corresponding demand response to wholesale electricity prices is about 2 GW, or 2.6% of peak load. Our analysis suggests that the demand response in Germany can be attributed primarily to industrial consumers.
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.
Since September 2021, European natural gas prices are at record-high levels. On average, they have been six to seven times higher than pre-pandemic price levels. While the post-pandemic recovery of global natural gas demand has driven up prices around the world, the most important drivers for European gas prices were Russia's less-than-usual supply since mid-2021 and its invasion of Ukraine in February 2022. Western efforts to abandon Russian gas imports altogether mean that high natural gas prices are likely to stay for longer. While high gas prices may be the new normal, there is uncertainty about the economic reaction to this shock. How do energy-intensive industries react? Do global value chains collapse if intermediate goods produced in Europe become uneconomic because of high energy prices? Our preliminary analysis shows that industry response to has in fact been visible from the very onset of the energy crisis. A closer look at German fertilizer production, which heavily relies on natural gas as fuel and feedstock to produce ammonia as an intermediate product, reveals that increased ammonia imports have allowed domestic fertilizer production to remain remarkably stable.
Europe is in the midst of the most severe energy crisis in a generation, at the core of which is the continuously plummeting supply of Russian natural gas. With alternative supply options being limited, natural gas prices have surged. This paper empirically estimates the response of natural gas demand to the price increase, using data from Germany—the so far largest consumer of Russian natural gas. We identify the crisis response of small and large consumers separately, controlling for temperature, gas-fired power generation, and economic activity. For small consumers, including mostly households, we find a substantial demand reduction of 6% from March onwards—most likely due to political and ethical considerations after the start of Russia’s invasion of Ukraine. For industrial consumers, demand reductions started much earlier in August 2021, when wholesale prices for natural gas started to surge, with an average reduction of 11%. We conclude that voluntary industrial demand response has played a significant role in coping with the energy crisis so far.