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Iegor Riepin

Publications and source records attributed to Iegor Riepin.

10 recordsLinked to original sources

Accelerating fossil gas independence in Europe

Recent price shocks have prompted calls to curb Europe's dependence on fossil gas imports, but the cost of this goal, and the consumer protection it affords, remain uncertain. Here we address this gap by imposing constraints on fossil gas supply in a European energy system model that co-optimises abatement across all gas uses at high spatio-temporal resolution. Cutting import reliance proves economically compelling: through savings in power generation and low-temperature heat in industry and buildings, Europe can halve its natural gas consumption for 16bnEUR/a, aligning demand with the continent's production capacity of 200 bcm. This extra system cost is comparable to what consumers spend today on a 2 EUR/MWh rise in gas import prices. However, this sovereignty alone does not shield consumers from global gas price volatility: we find that, even at a small share of the mix, gas remains dominant in shaping the marginal electricity price, leaving consumers exposed without additional policy measures.

econ.GN↗

Adaptive Robust Optimization for European Electricity System Planning Considering Regional Dunkelflaute Events

The expansion of wind and solar power is driving the European energy system transformation, thereby also driving our reliance on this weather-dependent resources. Integrating renewable scarcity events into long-term planning has therefore become essential. This study demonstrates how worst-case regional renewable scarcity events - such as the Dunkelflaute, prolonged periods of low wind and solar availability - can be incorporated endogenously into the planning of a weather-robust, interconnected energy system. We develop a capacity expansion model for a fully decarbonized European electricity system using an adaptive robust optimization framework which incorporates multiple extreme weather realizations within a single optimization run. Results show that system costs rise nonlinearly with the geographic extent of these events: a single worst-case regional disruption increases costs by 9%, but broader disruptions across multiple regions lead to much sharper increases, up to 51%. As Dunkelflaute conditions extend across most of Europe, additional cost impacts level off, with a maximum increase of 71%. The optimal technology mix evolves with the severity of weather stress: while renewables, batteries, and interregional transmission are sufficient to manage localized events, large-scale disruptions require long-term hydrogen storage and load shedding to maintain system resilience. Central European regions, especially Germany and France, emerge as systemic bottlenecks, while peripheral regions bear the cost of compensatory overbuilding. These findings underscore the need for a coordinated European policy strategy that goes beyond national planning to support cross-border infrastructure investment, scale up flexible technologies such as long-duration storage, and promote a geographically balanced deployment of renewables to mitigate systemic risks associated with Dunkelflaute events.

econ.GN↗

The role of Projects of Common Interest in reaching Europe's energy policy targets

The European Union aims to achieve climate-neutrality by 2050, with interim 2030 targets including 55% greenhouse gas emissions reduction compared to 1990 levels, 10 Mt p.a. of a domestic green H2 production, and 50 Mt p.a. of domestic CO2 injection capacity. To support these targets, Projects of Common and Mutual Interest (PCI-PMI) - large infrastructure projects for electricity, hydrogen and CO2 transport, and storage - have been identified by the European Commission. This study focuses on PCI-PMI projects related to hydrogen and carbon value chains, assessing their long-term system value and the impact of pipeline delays and shifting policy targets using the sector-coupled energy system model PyPSA-Eur. Our study shows that PCI-PMI projects enable a more cost-effective transition to a net-zero energy system compared to scenarios without any pipeline expansion. Hydrogen pipelines help distribute affordable green hydrogen from renewable-rich regions in the north and southwest to high-demand areas in central Europe, while CO2 pipelines link major industrial emitters with offshore storage sites. Although these projects are not essential in 2030, they begin to significantly reduce annual system costs by more than EUR 26 billion from 2040 onward. Delaying implementation beyond 2040 could increase system costs by up to EUR 24.2 billion per year, depending on the extent of additional infrastructure development. Moreover, our results show that PCI-PMI projects reduce the need for excess wind and solar capacity and lower reliance on individual CO2 removal technologies, such as Direct Air Capture, by 13 to 136 Mt annually, depending on the build-out scenario.

physics.soc-ph↗

Price formation without fuel costs: the interaction of demand elasticity with storage bidding

Studies looking at electricity market designs for very high shares of wind and solar often conclude that the energy-only market will break down. Without fuel costs, it is said that there is nothing to set prices. Symptoms of breakdown include long phases of zero prices, scarcity prices too high to be politically acceptable, prices that collapse under small perturbations of capacities from the long-term equilibrium, cost recovery that is impossible due to low market values, high variability of revenue between different weather years, and difficulty operating long-term storage with limited foresight. We argue that all these problems are an artefact of modelling with perfectly inelastic demand. If short-term elasticity to reflect today's flexible demand (-5%) is implemented, these problems are reduced. The interaction of demand willingness to pay and storage opportunity costs is enough to produce stable pricing. This behavior is illustrated by a model with wind, solar, batteries, and hydrogen-based storage, where the price duration curve is smoothed with a piecewise linear demand curve. This removes high price peaks, reduces the fraction of zero-price hours from 90% to around 30%, and guarantees more price stability for perturbations of capacity and different weather years. Furthermore, we show that with demand elasticity, the long-term optimisation model exactly reproduces the prices of the short-term model with the same capacities. We then use insights from the long-term model to derive simple bidding strategies for storage so that we can also run the short-term model with limited operational foresight. We demonstrate this short-term operation in a model optimised using 35 years of weather data and then tested on another 35 years of unseen data. We conclude that the energy-only market can still play a key role in coordinating dispatch and investment in the future.

econ.GN↗

Modelling the High-Voltage Grid Using Open Data for Europe and Beyond

This paper provides the background, methodology and validation for constructing a representation of the European high-voltage grid, including and above 200 kV, based on public data provided by OpenStreetMap. The model-independent grid dataset is published under the Open Data Commons Open Database (ODbL 1.0) licence and can be used for large-scale electricity as well as energy system modelling. The dataset and workflow are provided as part of PyPSA-Eur -- an open-source, sector-coupled optimisation model of the European energy system. By integrating with the codebase for initiatives such as PyPSA-Earth, the value of open and maintainable high-voltage grid data extends to the global context. By accessing the latest data through the the Overpass turbo API, the dataset can be easily reconstructed and updated within minutes. To assess the data quality, this paper further compares the dataset with official statistics and representative model runs using PyPSA-Eur based on different electricity grid representations.

physics.soc-ph↗

Spatio-temporal load shifting for truly clean computing

Companies with datacenters are procuring significant amounts of renewable energy to reduce their carbon footprint. There is increasing interest in achieving 24/7 Carbon-Free Energy (CFE) matching in electricity usage, aiming to eliminate all carbon footprints associated with electricity consumption on an hourly basis. However, the variability of renewable energy resources poses significant challenges for achieving this goal. We explore the impact of shifting computing jobs and associated power loads both in time and between datacenter locations. We develop an optimization model to simulate a network of geographically distributed datacenters managed by a company leveraging spatio-temporal load flexibility to achieve 24/7 CFE matching. We isolate three signals relevant for informed use of load flexiblity: varying average quality of renewable energy resources, low correlation between wind power generation over long distances due to different weather conditions, and lags in solar radiation peak due to Earth's rotation. We illustrate that the location of datacenters and the time of year affect which signal drives an effective load-shaping strategy. The energy procurement and load-shifting decisions based on informed use of these signals facilitate the resource-efficiency and cost-effectiveness of clean computing -- the costs of 24/7 CFE are reduced by 1.29$\pm$0.07 EUR/MWh for every additional percentage of flexible load. We provide practical guidelines on how companies with datacenters can leverage spatio-temporal load flexibility for truly clean computing. Our results and the open-source optimization model can also be useful for a broader variety of companies with flexible loads and an interest in eliminating their carbon footprint.

physics.soc-ph↗

On the means, costs, and system-level impacts of 24/7 carbon-free energy procurement

A growing number of public and private energy buyers are interested in 24/7 carbon-free energy (CFE) procurement, which means that every kilowatt-hour of electricity consumption is met by carbon-free sources at all times. It has the potential to overcome the limitations of established procurement schemes, such as the temporal mismatch between clean electricity supply and buyers' demand that is inherent to "volumetric" matching. Yet it is unclear how 24/7 CFE procurement affects the rest of the power system, and whether this effect is consistent across regional contexts and different levels of system cleanness. We use a mathematical model to systematically examine different designs, optimal procurement strategies, costs, and impacts of the 24/7 CFE matching, both for participating buyers and for regions where voluntary procurement occurs. We examine mechanisms driving system-level missions reduction and how they vary across regions and over time. Our results indicate that clean energy procurement commitments have consistent beneficial effects on participants and the electricity system. Even as grids become cleaner over time, the hourly matching strategy contributes significantly to system-level emissions reduction. In addition, voluntary commitments to 24/7 CFE have a further transformative effect on electricity systems through accelerated innovation and early deployment of advanced energy technologies.

physics.soc-ph↗

Policy choices and outcomes for offshore wind auctions globally

Offshore wind energy is rapidly expanding, facilitated largely through auctions run by governments. We provide a detailed quantified overview of applied auction schemes, including geographical spread, volumes, results, and design specifications. Our comprehensive global dataset reveals heterogeneous designs. Although most remuneration designs provide some form of revenue stabilisation, their specific instrument choices vary and include feed-in tariffs, one-sided and two-sided contracts for difference, mandated power purchase agreements, and mandated renewable energy certificates. We review the schemes used in all eight major offshore wind jurisdictions across Europe, Asia, and North America and evaluate bids in their jurisdictional context. We analyse cost competitiveness, likelihood of timely construction, occurrence of strategic bidding, and identify jurisdictional aspects that might have influenced auction results. We find that auctions are embedded within their respective regulatory and market design context, and are remarkably diverse, though with regional similarities. Auctions in each jurisdiction have evolved and tend to become more exposed to market price risks over time. Less mature markets are more prone to make use of lower-risk designs. Still, some form of revenue stabilisation is employed for all auctioned offshore wind energy farms analysed here, regardless of the specific policy choices. Our data confirm a coincidence of declining costs and growing diffusion of auction regimes.

econ.GN↗

Risk aversion in flexible electricity markets

Flexibility options, such as demand response, energy storage and interconnection, have the potential to reduce variation in electricity prices between different future scenarios, therefore reducing investment risk. Moreover, investment in flexibility options can lower the need for generation capacity. However, there are complex interactions between different flexibility options. In this paper, we investigate the interactions between flexibility and investment risk in electricity markets. We employ a large-scale stochastic transmission and generation expansion model of the European electricity system. Using this model, we first investigate the effect of risk aversion on the investment decisions. We find that the interplay of parameters leads to (i) more investment in a less emission-intensive energy system if planners are risk averse (hedging against CO2 price uncertainty) and (ii) constant total installed capacity, regardless of the level of risk aversion (planners do not hedge against demand and RES deployment uncertainties). Second, we investigate the individual effects of three flexibility elements on optimal investment levels under different levels of risk aversion: demand response, investment in additional interconnection capacity and investment in additional energy storage. We find that that flexible technologies have a higher value for risk-averse decision-makers, although the effects are nonlinear. Finally, we investigate the interactions between the flexibility elements. We find that risk-averse decision-makers show a strong preference for transmission grid expansion once flexibility is available at low cost levels.

econ.GN↗

Modelling uncertainty in coupled electricity and gas systems -- is it worth the effort?

The interdependence of electricity and natural gas markets is becoming a major topic in energy research. Integrated energy models are used to assist decision-making for businesses and policymakers addressing challenges of energy transition and climate change. The analysis of complex energy systems requires large-scale models, which are based on extensive databases, intertemporal dynamics and a multitude of decision variables. Integrating such energy system models results in increased system complexity. This complexity poses a challenge for energy modellers to address multiple uncertainties that affect both markets. Stochastic optimisation approaches enable an adequate consideration of uncertainties in investment and operation planning; however, stochastic modelling of integrated large-scale energy systems further scales the level of complexity. In this paper, we combine integrated and stochastic optimisation problems and parametrise our model for European electricity and gas markets. We analyse and compare the impact of uncertain input parameters, such as gas and electricity demand, renewable energy capacities and fuel and CO2 prices, on the quality of the solution obtained in the integrated optimisation problem. Our results quantify the value of encoding uncertainty as a part of a model. While the methodological contribution should be of interest for energy modellers, our findings are relevant for industry experts and stakeholders with an empirical interest in the European energy system.

q-fin.GN↗