Powering Europe with North Sea Offshore Wind: The Impact of Hydrogen Investments on Grid Infrastructure and Power Prices

Hydrogen will be a central cross-sectoral energy carrier in the decarbonization of the European energy system. This paper investigates how a large-scale deployment of green hydrogen production affects the investments in transmission and generation towards 2060, analyzes the North Sea area with the main offshore wind projects, and assesses the development of an offshore energy hub. Results indicate that the hydrogen deployment has a tremendous impact on the grid development in Europe and in the North Sea. Findings indicate that total power generation capacity increases around 50%. The offshore energy hub acts mainly as a power transmission asset, leads to a reduction in total generation capacity, and is central to unlock the offshore wind potential in the North Sea. The effect of hydrogen deployment on power prices is multifaceted. In regions where power prices have typically been lower than elsewhere in Europe, it is observed that hydrogen increases the power price considerably. However, as hydrogen flexibility relieves stress in high-demand periods for the grid, power prices decrease in average for some countries. This suggests that while the deployment of green hydrogen will lead to a significant increase in power demand, power prices will not necessarily experience a large increase.Comment: Submitted to Energ

The impact of wind uncertainty on the strategic valuation of distributed electricity storage

The intermittent nature of wind energy generation has introduced a new degree of uncertainty to the tactical planning of energy systems. Short-term energy balancing decisions are no longer (fully) known, and it is this lack of knowledge that causes the need for strategic thinking. But despite this observation, strategic models are rarely set in an uncertain environment. And even if they are, the approach used is often inappropriate, based on some variant of scenario analysis—what-if analysis. In this paper we develop a deterministic strategic model for the valuation of electricity storage (a battery), and ask: “Though leaving out wind speed uncertainty clearly is a simplification, does it really matter for the valuation of storage?”. We answer this question by formulating a stochastic programming model, and compare its valuation to that of its deterministic counterpart. Both models capture the arbitrage value of storage, but only the stochastic model captures the battery value stemming from wind speed uncertainty. Is the difference important? The model is tested on a case from Lancaster University’s campus energy system where a wind turbine is installed. From our analysis, we conclude that considering wind speed uncertainty can increase the estimated value of storage with up to 50 % relative to a deterministic estimate. However, we also observe cases where wind speed uncertainty is insignificant for storage valuation

Synergy of smart grids and hybrid distributed generation on the value of energy storage

In smart grids, demand response and distributed energy systems aim to provide a higher degree of flexibility for load-shifting operations and the leverage to control intermittent wind supply. In this more dynamic energy system, deployment of energy storage at the site of consumption is envisioned to create synergies with the local distributed generation (DG) system. From a large end-user perspective, this paper contributes to the practical understanding of smart grids by modelling the impact of real-time pricing schemes (smart grids) on a hybrid DG system (mixed generation for heating and electricity loads) coupled with storage units. Specifically, we address: How does the portfolio of DG units affect the value of energy storage? and, what is the value of energy storage when assessing different designs of demand response for the end-user? To this end, we formulate a dynamic optimization model to represent a real-life urban community’s energy system composed of a co-generation unit, gas boilers, electrical heaters and a wind turbine. We discuss the techno-economic benefits of complementing this end-user’s energy system with storage units (thermal storage and battery devices). The paper analyses the storages policy strategies to simultaneously satisfy heat and electricity demand through the efficient use of DG units under demand response mechanisms. Results indicate that the storage units reduce energy costs by 7–10% in electricity and 3% in gas charges. In cases with a large DG capacity, the supply–demand mismatch increases, making storage more valuable

Modelling long term EU decarbonization policies along with detailed country energy system adequacy and security assessments

The assessment of adequacy and security of the energy system requires the detailed knowledge of physical and operational characteristics. In contrast, studies concerning energy transitions employ stylized models that oftentimes ignore the technical properties but have a lasting influence on longterm energy policies. This paper investigates the gap between energy system planning and operational models by linking these two perspectives: (1) a long-term investment model with low spatial resolution and high level of aggregation, and (2) a spatially resolved system security model that captures the interdependences between the backbone of the electric power sector, i.e., the electricity and the gas infrastructures. We assess EU decarbonisation pathways of the electricity sector towards 2050 by integrating the investment decisions of the long-term planning model and the safety performance of the resulting system operations via the security model. In a large RES deployment scenario, we investigate two flexibility options: gas power plants and cross-country transmission expansion. Using the integrated model, we analyze how the adequacy and security of supply under extreme short-term operational conditions impact the long-term planning of the energy system and the investment decision-making. We provide country specific recommendations for UK. Results indicate weaknesses in the gas-electricity system and suggest improvements on capacity allocation

Decarbonizing the European energy system in the absence of Russian gas: Hydrogen uptake and carbon capture developments in the power, heat and industry sectors

Hydrogen and carbon capture and storage are pivotal to decarbonize the European energy system in a broad range of pathway scenarios. Yet, their timely uptake in different sectors and distribution across countries are affected by supply options of renewable and fossil energy sources. Here, we analyze the decarbonization of the European energy system towards 2060, covering the power, heat, and industry sectors, and the change in use of hydrogen and carbon capture and storage in these sectors upon Europe's decoupling from Russian gas. The results indicate that the use of gas is significantly reduced in the power sector, instead being replaced by coal with carbon capture and storage, and with a further expansion of renewable generators. Coal coupled with carbon capture and storage is also used in the steel sector as an intermediary step when Russian gas is neglected, before being fully decarbonized with hydrogen. Hydrogen production mostly relies on natural gas with carbon capture and storage until natural gas is scarce and costly at which time green hydrogen production increases sharply. The disruption of Russian gas imports has significant consequences on the decarbonization pathways for Europe, with local energy sources and carbon capture and storage becoming even more important.Comment: 39 pages, 7 figures, submitted to the Journal of Cleaner Productio

Swarm electrification: Harnessing surplus energy in off-grid solar home systems for universal electricity access

peer reviewedAchieving universal access to electricity by 2030, as set out by the Sustainable Development Goals, presents a significant challenge given the current rate of progress. A recent promising concept is swarm electrification. Its central idea is the peer-to-peer energy sharing of surplus energy in solar home systems (SHSs) to connect additional neighbors and grow a bottom-up grid. This paper studies the surplus energy in SHSs and its underlying influencing factors as a basis for swarm electrification. An open-source multi-model-based techno-economic analysis of off-grid SHS including surplus energy as a value is presented. Three distinct household types from the tier 3 category in the Multi-tier framework are compared based on their unique ratios of peak-to-average demand and percentage of load consumption during sun hours. A statistical analysis of surplus energy for each household type is presented and energy sharing with additional households at tier 1–2 is simulated. Two economic analysis methods, including surplus energy, are presented and compared: single-objective cost minimization and multi-objective compromise programming. The study finds that a low ratio of demand during sun hours leads to higher surplus energy volumes, while a peak-to-average ratio alone cannot give such indications. Both economic methods suggest that optimizing the SHS design for tier 3 households involves a slight increase in solar power capacity when considering the expected revenue from selling surplus energy to 2–3 households in tiers 1–2. The total cost for the tier 3 households are reduced by 40%−64%, additionally to decreasing their own lost load by 4%−7%, and reducing the up-front cost to get electricity access for the tier 1–2 households by 50% compared to purchasing their own full SHS

Flexibility Characterization, Aggregation, and Market Design Trends with a High Share of Renewables: a Review

Purpose of Review Balancing a large share of solar and wind power generation in the power system will require a well synchronized coordination of all possible flexibility sources. This entails developing market designs that incentivize flexibility providers, and define new flexibility products. To this end, the paper reviews latest trends in the characterization of flexibility by understanding its dimensions in terms of time, spatiality, resource type, and associated risks. Also, as aggregators have emerged as important actors to deliver, and to reward end-user flexibility, the paper reviews latest trends in the topic. Recent Findings The review reports latest trends and discussions on power system flexibility and their relations to market design. The current academic literature indicates that there are open question and limited research on how to reward shortterm flexibility while considering its long-term economic viability. Demand-side flexibility through aggregation holds great potential to integrate renewables. Summary Research in power system flexibility has to put effort on analysing new time-structures of electricity markets and define new marketplaces that consider the integration of new flexibility products, actors (e.g. aggregators, end-users), and mechanisms (e.g. TSO-DSO coordination).Flexibility Characterization, Aggregation, and Market Design Trends with a High Share of Renewables: a ReviewpublishedVersio

Uncertainty Modeling for Participation of Electric Vehicles in Collaborative Energy Consumption

This paper proposes an accurate and efficient probabilistic method for modeling the nonlinear and complex uncertainty effects and mainly focuses on the Electric Vehicle (EV) uncertainty in Peer-to-Peer (P2P) trading. The proposed method captures the uncertainty of the input parameters with a low computational burden and regardless of the probability density function (PDF) shape. To this end, for each uncertain parameter, multitude of random vectors with the specification of corresponding uncertain parameters are generated and a fuzzy membership function is then assigned to each vector. Since the most probable samples occur repeatedly, they are recognized by the superposition of the generated fuzzy membership functions. The simulation results on various case studies indicate the high accuracy of the proposed method in comparison with Monte-Carlo simulation (MCs), Unscented Transformation (UT), and Point Estimate Method (PEM). It also scales down the computational burden compared to MCs. Also, a real-world case study is employed to examine the ability of the method in capturing the uncertainty of EVs’ arrival and departure time. The studies on this case reveal that involving EVs in P2P trading augments the amount of energy traded within the prosumers.©2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Flexbuild final report. The value of end-use flexibility in the future Norwegian energy system

The Flexbuild project aimed to understand how end-use flexibility could impact the future energy system in Norway. This initiative brought together industrial partners, public organizations, universities, and research institutions to investigate various aspects of energy flexibility. To achieve its objectives, the project employed a combination of models and explored four different energy transition scenarios, or storylines, named as Energy Nation, Petroleum Nation, Nature Nation, and Climate panic. The models developed and used in the project included BUILDopt for building energy use, IFE-TIMES-Norway for the Norwegian energy system, EMPIRE for the European power market, and EMPS for the Norwegian hydropower system. These models were interconnected through a soft linking approach, allowing them to influence each other's input and results, until some predefined convergency criteria are met. The project's input data and calibration involved regionally dividing the Norwegian building stock, defining potential for district heating expansion, and calibrating models against statistical data. Capacity Expansion of the European Power System EMPIRE is a long-term investment model designed to optimize technology portfolios within the European power system while considering factors like carbon dioxide (CO2) emissions targets, supply-demand balance, and technical constraints. The model represented thirty-one European countries connected through interconnectors, excluding Norway, which was divided into five market areas. EMPIRE was expanded to incorporate demand response from residential appliances, allowing it to consider residential electric load flexibility. This expansion indicated potential cost reductions of about 1% from 2020 to 2055. Activation of End-Use Flexibility in Buildings BUILDopt was developed to model end-use flexibility in buildings. It optimizes both operational and investment costs for a single building's energy system, considering factors like grid tariffs, spot prices, and flexible load profiles. The model incorporated flexibility sources such as indoor temperature control, thermal storage, and electric vehicle (EV) charging. BUILDopt's simulations revealed the potential for significant peak load reduction and cost savings through flexibility activation. The choice of grid tariff was a critical factor, with tariffs including a power fee component offering more cost-effective peak load reduction. The model also explored investment optimization in heating technologies, solar PV, and batteries. The results showed that activating existing flexibility sources could eliminate the need for investing in battery systems while it would accelerate the adoption of solar PV in buildings, particularly in houses. Energy System in Norway IFE-TIMES-Norway was linked with both EMPIRE and BUILDopt to understand interactions within the Norwegian and European power systems and the building sector, respectively. This linkage facilitates a holistic view of the energy transition. The results of this model emphasize the value of end-use flexibility in reducing energy transition costs. These flexibility options help align local energy production, especially from PV, with demand, reducing the need for grid expansion. They also increase profits from international electricity trade. End-use flexibility's impact on peak demand reduction varies by region and storyline. Importantly, it plays a role in lowering the need for hydrogen and thermal storage. Hydropower System in Norway The EMPS model focused on assessing how flexible end-use of electricity demand would affect Norway's hydropower-dominated power system. The study found that end-use flexibility had minimal effects on the power system, leading to slight reductions in energy demand and higher energy surplus in Norway. Power prices saw small decreases, especially in 2050, while hydropower production remained relatively stable, with minor changes in average power production and water reservoir usage. However, it also led to reduced income for both hydropower and wind power producers, particularly in 2030. The main objective of the project was to provide knowledge on how end-use flexibility available in the building stock will impact the development of the overall energy system. The main takeaways of Flexbuild are here summarized with respect to the project’s objectives. Objective 1: Develop a robust and novel stochastic modelling framework of the Norwegian energy system capable of evaluating the impacts of end-use flexibility in the energy system. The project created the BUILDopt model to assess end-use flexibility in buildings. It also expanded the IFE-TIMES-Norway model with stochastic elements to account for uncertainty in energy storage investments. Additionally, the project developed a methodology for linking these models. The results from the linking show that buildings remain fundamentally price-takers, and even if energy demand becomes flexible in the entire building stock, this has only a marginal impact on the energy price formation. Objective 2: Assess cost-optimal investment and operation of the energy system vs. private building owner and address possible mismatch between the two. End-use flexibility was seen as a techno-economic investment that improved the match between local PV production and demand, reducing the need for grid expansion. The cost-optimal choice for heating technologies often favoured heat pumps over district heating, highlighting a mismatch between individual building choices and the energy system perspective. Solar PV installation was found to be cost-optimal when combined with end-use flexibility, significantly reducing the need for batteries. Objective 3: Assess the impacts of different power tariffs on both end-user and the energy system. The type of power tariff had a significant impact. A tariff with a power fee component, in addition to an energy fee, enabled more cost-effective peak load management by setting caps on peak demand. Objective 4: Asses the value of end-use flexibility for easing the power grid reinforcement. End-use flexibility had the potential to reduce peak loads at the single building level by 20-50%, with smaller effects at the aggregate level, around 16-20% at market area level. The high level of solar PV installations raised questions about grid challenges in areas dominated by single-family houses. Objective 5: Investigate how end-use flexibility may change the role of Norwegian hydropower and investment in wind and solar in the national and European power system. End-use flexibility was shown to accelerate solar PV adoption in Norway, increasing total capacity and electricity production. While hydropower production remained relatively stable, there were slight reductions in power prices. Future work should include modelling distribution grids and ancillary markets, with an emphasis on stochastic demand profiles rather than archetype buildings for more robust representations. In summary, Flexbuild generated knowledge on end-use flexibility, its modelling and its potential impacts on the Norwegian energy system. It emphasized the importance of grid tariffs, the cost-effectiveness of end-use flexibility, and its role in promoting solar PV adoption while reducing the need for grid expansion.publishedVersio