This study analyzes the production of green hydrogen using dedicated offshore wind power in the Dutch North Sea region. The analysis is based on a detailed techno-economic model that simulates physical flows and estimates the levelized cost of hydrogen (LCOH). However, the model’s outputs depend on user-provided inputs and evaluating all possible inputs is computationally infeasible. To this end, “optimization with constraint learning” is employed, where surrogate machine learning models are trained on simulation data and embedded in mixed-integer optimization problems. The surrogate models are trained on 4096 simulation runs and achieve a mean absolute percentage error of ≤[jls-end-space/]3% for physical flow-related outputs, and an error of ≈[jls-end-space/]10% for the LCOH-related outputs. Once trained, these surrogates enable one to solve stakeholder–specific problem instances in sub-second solve times, supporting rapid scenario analysis and trade-off exploration.

Vehicle-to-Grid (V2G) technology represents a key advancement in integrating electric vehicles with the power grid, enabling bidirectional energy flow to improve grid stability and optimise energy use and storage. Despite its technical feasibility, adoption remains hindered by social acceptance that evolves over time. The reviewed period from 2017 to 2025 has been marked by significant turbulence in sectors directly affecting V2G, including energy markets, mobility trends, and policy frameworks. Given that V2G has long been technically feasible yet struggled to achieve widespread acceptance, these disruptions present a unique window of opportunity. In light of this, rather than offering the usual snapshot perspective, this review focuses on the connections between its perception and trends influencing it. Aiming to identify the key drivers that could propel it toward widespread implementation. This review unconventionally combines academic literature with diverse grey literature, providing a broader perspective by incorporating industry developments and identifying trends. Factors are classified into three categories - emerging, persistent, and diminishing - capturing their changing significance over time. Our findings suggest that while financial incentives and lack of standardisation remain crucial, motivations for V2G acceptance are shifting, with sustainability and energy autonomy gaining importance. Some previously critical concerns, such as range anxiety and battery degradation, are diminishing as technology advances. Beyond identifying trends, we propose strategies to overcome key barriers, providing a deeper understanding of evolving consumer priorities and technological advancements.

Recent energy justice scholarship has argued for the need to reflect more explicitly on the normative assumptions that underpin claims to justice in energy systems. While such reflections increasingly inform energy policy, less attention has been paid to how these assumptions shape the design of algorithmic systems central to energy system planning and operations. This paper explores how normative assumptions in the design of algorithmic systems used to request flexibility from electricity consumers and producers to manage grid congestion may influence distributive justice outcomes. By systematically reviewing the scientific literature presenting such systems, we define two categories of assumptions: (1) scope assumptions , which set the boundaries of the justice analysis by determining which burdens and benefits, scale, subjects, and timeframe are considered relevant; and (2) design assumptions , which specify how these considerations are translated into the structure of algorithmic systems, such as allocation principles, technical problem framing, data availability and evaluation metrics. We find that the particular assumptions adopted within each category determine the distributive outcomes of these algorithmic systems. Recognizing their normative character, we propose that scope assumptions should be informed by context-specific risks of injustice identified by policymakers, while engineers should reflect on and validate their design assumptions in relation to these risks.

Hydrogen is increasingly recognized as a key solution for decarbonizing the Dutch energy system, particularly within the industrial sector. A national hydrogen network is under development to serve the five major industrial clusters in the Netherlands. However, meeting the hydrogen needs of the industries outside these clusters, which are collectively known as “Cluster 6”, remains difficult. Regulatory unclarity and ambiguity around the hydrogen distribution infrastructure, including restrictions on distribution system operators (DSOs), compound these challenges. This study investigates the complex and evolving regulatory landscape for hydrogen distribution across Cluster 6 in the Netherlands using a two-step approach of Institutional Network Analysis (INA) and stakeholder interviews. Findings outline possible pathways for delegating distribution responsibilities in current and future regulatory frameworks while stakeholders report structural and outcome uncertainty, limiting their willingness to invest in hydrogen distribution initiatives. The research findings highlight the need for a more coherent regulatory and technical framework to support more effective development of physical hydrogen systems. Policy recommendations include clarification of distributor roles, targeted support mechanisms, and flexible regulations that can adapt to the rapidly developing hydrogen market.

Ambitious offshore wind energy targets in the North Sea necessitate innovative solutions for efficiently delivering energy to onshore demand locations. Wind-to-hydrogen systems offer a promising pathway, with three archetypes of system configurations: centralized onshore electrolysis (C-ON), centralized offshore electrolysis (C-OFF), and decentralized offshore electrolysis at each wind turbine (D-OFF). This study introduces a high-resolution, time-dependent simulation framework capable of analyzing offshore wind-to-hydrogen systems with a focus on operational dynamics and comprehensive cost estimation. The framework enables detailed analysis of D-OFF, capturing its unique dynamics driven by direct connections to individual wind turbines, including the impacts of dynamic operation. A comprehensive system analysis, spanning from the wind farm to the hydrogen offtaker, reveals a wide cost range, with Levelized Cost of Hydrogen (LCOHs) ranging from 3.0 to 10.5€/kgH₂ post 2030. Among the different scenarios analyzed, C-OFF with proton exchange membrane electrolysis achieves the lowest LCOHs due to a reduced need for offshore electrical infrastructure, economies of scale, and efficient dynamic operating characteristics. D-OFF with alkaline electrolysis incurs the highest costs and faces operational challenges, such as electrolyzers shutting down when they occasionally fail to reach the minimum load thresholds, lowering hydrogen production. We illustrate the trade-offs between system configurations’ cost, production rate, and electrolyzer stack lifetime across configurations. Insights from this study can be utilized as a starting point for informed decision-making for large-scale wind-to-hydrogen deployment in the Dutch North Sea region.

Vehicle-to-grid (V2G) could help balance and regulate the electricity grid. While research papers have focused primarily on the technological potential of V2G services and consumer adaptation, the institutional barriers obstructing the industry from implementing V2G are hardly researched. This study, therefore, explored these institutional barriers using grounded theory and stakeholder interviews. The results showed an array of barriers related to communication standard ambiguity, non-harmonised and undefined network codes, charging standard ambiguity resulting in uncertainties and financial risks, and conflicting stakeholder needs about who should control V2G operations. We conclude that large-scale adoption of V2G in Europe is hindered because it is unclear to the actors involved how to become ”V2G-ready”. This lack of clarity results in an innovation that is in a wait-and-see phase. We give practical recommendations to potentially become V2G-ready and for further research.

Multi-energy networks facilitate the interactions of multiple energy carriers such as electricity, heat, cooling, and natural gas for manifold benefits in the construction and operation of energy systems. They also provide a unified platform to integrate and utilize various advanced energy technologies such as renewables, cogeneration, power-to-X, electric vehicles, and energy storage. The problem scale of multi-energy networks is increasing rapidly with the accelerated expansion and integration of regional and urban energy systems. For these reasons, the analysis and optimization of multi-energy networks are faced with significant challenges. New methods are urgently required to address the basic computational challenges in multi-energy networks such as the multi-temporal-spatial scales, nonlinearity, uncertainty, combinatorial property of mixed continuous and discrete variables, and the solving of large-scale systems in a multi-stakeholder context. This special issue mainly covers papers on the computational theories and methods that can be applied in multi-energy networks. The aim is to present a state-of-the-art collection of innovative models, algorithms, approaches, and tools for the control, operation, design, simulation, and analysis of multi-energy networks. The special issue provides an opportunity for researchers and practicing engineers to share their latest discoveries and best practices in these areas.

As renewable energy and electrification expand rapidly, many electrical distribution grids experience grid congestion. This situation leads to long waiting lists for parties seeking a new grid connection or aiming to expand their existing grid connection. In addition to traditional grid enforcements, distribution system operators are developing ways to manage congestion by steering electricity supply and demand. As grid congestion limits the previously abundant resource of grid capacity, the challenge of how to fairly distribute this now-scarce resource raises new questions about nondiscrimination and broader notions of justice. This study, grounded in energy justice, explores the distributive and procedural injustices people experience with increasing grid congestion. Our research focuses on The Netherlands, where more than 10,000 parties await new grid connections. Through 16 semi-structured interviews with people either affected by or involved in mitigating grid congestion, our thematic analysis reveals three key categories: (1) injustices arising from legacy policies, legislation, and social norms; (2) injustices due to unclear regulations, inconsistent policies, and policy gaps; and (3) injustices related to changing relationships between DSOs and affected parties. These findings highlight that grid congestion is fundamentally sociotechnical; while congestion is both constrained and addressed by technical factors, institutional and social factors such as legacy policies, social norms and communication, significantly influence perceptions of injustice. Our findings call for a comprehensive integration of justice principles within the institutional (e.g. regulation, policy, markets, social norms), technical (e.g. grid infrastructure, IT systems), and social (e.g. community engagement, communication) components of grid infrastructure.

Fairness has recently gained significant attention in the scientific literature on algorithmic control systems for congestion management. However, many diverse conceptualizations of fairness have been presented. This paper aims to categorize these varying conceptualizations by reviewing existing literature on congestion management. It examines how researchers approach decisions concerning the scoping of fairness problems, the selection of fairness principles, and the choice of evaluation metrics. Findings highlight a need for more justification of fairness conceptualizations in literature as well as a need for standardized evaluation metrics and more empirical grounding and validation. The insights provided can help researchers and practitioners consider fairness comprehensively in the design of algorithmic control systems for congestion management.

Hydrogen is becoming increasingly popular as a clean, secure, and affordable energy source for the future. This study develops an approach for designing a PV–battery–electrolyzer–fuel cell energy system that utilizes hydrogen as a long-term storage medium and battery as a short-term storage medium. The system is designed to supply load demand primarily through direct electricity generation in the summer, and indirect electricity generation through hydrogen in the winter. The sizing of system components is based on the direct electricity and indirect hydrogen demand, with a key input parameter being the load sizing factor, which determines the extent to which hydrogen is used to meet seasonal imbalance. Technical and financial indicators are used to assess the performance of the designed system. Simulation results indicate that the energy system can effectively balance the seasonal variation of renewable generation and load demand with the use of hydrogen. Additionally, guidelines for achieving self-sufficiency and system sustainability for providing enough power in the following years are provided to determine the appropriate component size. The sensitivity analysis indicates that the energy system can achieve self-sufficiency and system sustainability with a proper load sizing factor from a technical perspective. From an economic perspective, the levelized cost of energy is relatively high because of the high costs of hydrogen-related components at this moment. However, it has great economic potential for future self-sufficient energy systems with the maturity of hydrogen technologies.

Electric vehicles have penetrated the Dutch market, which increases the potential for decreased local emissions, the use and storage of sustainable energy, and the roll-out and use of electric car-sharing business models. This development also raises new potential issues such as increased electricity demand, a lack of social acceptance, and infrastructural challenges in the built environment. Relevant stakeholders, such as policymakers and service providers, need to align their values and prioritize these aspects. Our study investigates the prioritization of 11 Dutch decision-makers in the field of public electric vehicle charging. These decision-makers prioritized different indicators related to measurements (e.g., EV adoption rates or charge point profitability), organization (such as fast- or smart-charging), and developments (e.g., the development of mobility-service markets) using the best-worst method. The indicators within these categories were prioritized for three different scenario's in time. The results reveal that priorities will shift from EV adoption and roll-out of infrastructure to managing peak demand, using more sustainable charging techniques (such as V2G), and using sustainable energy towards 2030. Technological advancements and autonomous charging techniques will become more relevant in a later time period, around 2040. Environmental indicators (e.g., local emissions) were consistently valued low, whereas mobility indicators were valued differently across participants, indicating a lack of consensus. Smart charging was consistently valued higher than other charging techniques, independent of time period. The results also revealed that there are some distinct differences between the priorities of policymakers and service providers. Having a systematic overview of what aspects matter supports the policy discussion around EVs in the built environment.

Charging infrastructure in neighborhoods is essential for inhabitants who use electric vehicles. The development of public charging infrastructure can be complex because of its dependency on local grid conditions, the responsibility to prepare for anticipated fleet growth policies, and the implicit biases that may occur with the allocation of charging resources. How can accessible EV charging be ensured in the future, regardless of energy infrastructure and socio-economic status of the neighborhood? This study aims to represent the decision-making in the allocation of public charging infrastructure and ensure that various key issues are accounted for in the short-term and long-term decision making. The paper first identifies these issues, then describes the decision-making process, and all of these are summarized in a visual overview describing the short-term and long-term decision loop considering various key indicators. A case study area is identified by comparing locally available data sources in the City of Amsterdam for future simulation.

This study aims to investigate the consumer acceptance of Vehicle-to-Grid (V2G) charging of electric vehicle (EV) drivers. To the best of the authors’ knowledge, this is the first V2G acceptance study that is based on actual users’ experience of V2G charging. A test set up with a V2G charge point at a solar carport was constructed at the Delft University of Technology. Seventeen participants in the study were given access to a V2G-compatible Nissan LEAF and the constructed V2G charging facilities, after which they were interviewed. Clear communication of the impacts of V2G charging cycles on EV batteries, financial compensation covering these impacts, real-time insight on the battery state-of-charge and the ability to set operational parameters through a user-friendly interface were all found to foster acceptance. The main barriers for acceptance were the uncertainty associated with battery state-of-charge, the increased need for planning charging and trips, the increased anxiety about the ability of the vehicle to reach its destination, economic and performance-related effects on the EV’s battery and the restriction of the freedom that users associated with their personal vehicles. The participants were found to be divided across high, conditional and low acceptance of V2G charging. The use of V2G charging over the trial period was found to inform their opinions: tangible factors such as range anxiety and the user interface were given more importance than abstract concepts such as lack of standards that were discussed by users without experience of V2G charging. Our study indicates that V2G charging in its current form is acceptable to a section of current EV users. The discussion provides insights on extending the relevance of our findings across other user groups and over further developments in the field.

The pursuing of inter-regional power transmission to address renewable power curtailment in China has resulted in disappointing gains. This paper evaluates the case of local green ammonia production to address this issue. An improved optimization-based simulation model is applied to simulate lifetime green manufacturing, and the impacts of main institutional incentives and oxygen synergy on investment are analysed. Levelized cost of ammonia is estimated at around 820 USD/t, which is about twice the present price. The operating rate, ammonia price, the electrical efficiency of electrolysers and the electricity price are found to be the key factors in green ammonia investment. Carbon pricing and value-added tax exemption exert obvious influences on the energy transition in China. A subsidy of approximately 450 USD/t will be required according to the present price; however, this can be reduced by 100 USD/t through oxygen synergy. Compared to inter-regional power transmission, green ammonia production shows both economic and environmental advantages. Therefore, we propose an appropriate combination of both options to address renewable power curtailment and the integration of oxygen manufacturing into hydrogen production. We consider the findings and policy implications will contribute to addressing renewable power curtailment and boosting the hydrogen economy in China.

Natural gas for heating is widespread in the built environment of The Netherlands, where the government aims at limiting heat demand and reducing natural gas consumption over the coming decades. In the owner-occupied residential sector, this transition is complex and requires cooperation and coordination of individuals and groups that make investment decisions. We use agent-based modelling to explore the effect that various financial policies could have in an illustrative neighbourhood, given that households make multi-criteria and group decisions. In the scientific literature, this type of energy model seldom focuses on the adoption of competing technologies by households as individual and collective agents grouped in homeowner associations in multi-family buildings. To address the problem and knowledge gaps, we model individual preferences with a multi-criteria perceived lifetime utility submodel, and decisions as outcomes of individual preferences and a threshold voting system. We explore energy taxes (natural gas and electricity), regulated price of heat from networks, and subsidies (insulation and heat pumps). Under our assumptions, we found that combinations of fiscal policies, regulated heat prices, and subsidies can sometimes create incentives for households to disconnect from natural gas, but that steering the transition mainly with financial policies could prove ineffective. We also found that, in terms of collective CO2 reduction, some transitions in which only some households phase out natural gas could have results similar to some scenarios in which households only improve their dwellings’ insulation levels.

This paper discusses the development of future green ammonia supply chains in China with the theory of complex system engineering, taking account of technical system, actors and institutions in future energy systems featured socio-technical systems as a whole. The energy condition in China identified features a spatial imbalance between renewable energy supply and demand, which cannot be fully addressed by the current power system-centric solution. This calls for hydrogen to make a concerted effort in the energy transition. By comparing major hydrogen delivery options, we argue that green ammonia can play a feasible role for large-scale energy distribution and long-term energy storage. The development of green ammonia supply chains and direct use of ammonia are proposed to avoid large uncertainties and initial investment in the early stage. The market creation will be key in the supply chain development. A long-term bilateral contract between buyer and seller and a joint investment in an integrated supply chain by several stakeholders are advised to share risks and ensure capital recovery. In addition, government participation is crucial in the early development phase by setting regulatory and financial institutions to support the market creation and supply chain development.

The Netherlands aims at reducing natural gas consumption for heating in the housing sector. Although homeowners are responsible for replacing their heating systems and improving dwelling insulation, they are not always able to make individual decisions. Some projects require group decisions within and between buildings. We use an agent-based modelling and simulation approach to explore how these individual and group decisions would influence natural gas consumption and heating costs in an illustrative neighbourhood, under a set of assumptions. We model individual household preferences over combinations of insulation and heating systems as a lifetime cost calculation with implicit discount rates, and we use quorum constraints to represent group decisions. We model three fiscal policies and a policy to disconnect all dwellings from the natural gas network. Results show that the disconnection policy was the only necessary and sufficient condition to incentivize households to replace their heating systems and that group decisions influenced the alternatives that were chosen. Since results were influenced by group decisions within buildings and by the market discount rate, we recommend further research regarding policies around these topics. Future work can apply our approach to case studies, incorporate new empirical knowledge, and explore group decisions in other contexts.

Vehicle-to-grid (V2G) technology could turn electric vehicles (EVs) into a potentially valuable solution to the problem of increased load demand caused by large-scale EV integration. Successful market penetration of V2G relies not only on developing the technology itself, but also on EV drivers' willingness to participate in this technology. This paper aims to explore Dutch EV drivers' preferences for participating in V2G contracts. In particular, we conduct a context-dependent stated choice experiment to examine the impact of EV recharging technology on the V2G contract preferences. Two contexts have been designed: the current EV recharging time and fast recharging. Our results show that in the context of current recharging time, Dutch EV drivers in general prefer not to participate in V2G contracts, while the opposite is true in the context of fast recharging. With regard to specific V2G contract attributes, Dutch EV drivers are most concerned about ‘discharging cycles’. Also important to them is ‘the guaranteed minimum battery level’, but its importance drops significantly in the fast charging context. In addition, ‘monthly remuneration’ and ‘plug-in time’ also influence people's preferences for adopting V2G. From these findings, we draw the implications for the aggregator and policy makers.

Global climate agreements call for action and an integrated perspective on mobility, energy and overall consumption. Municipalities in dense, urban areas are challenged with facilitating this transition with limited space and energy resources, and with future uncertainties. One important aspect of the transition is the adoption of electric vehicles, which includes the adequate design of charging infrastructure. Another important goal is a modal shift in transportation. This study investigated over 80 urban mobility policy measures that are in the policy roadmap of two of the largest municipalities of the Netherlands. This analysis consists of an inventory of policy measures, an evaluation of their environmental effects and conceptualizations of the policy objectives and conditions within the mobility transitions. The findings reveal that the two municipalities have similarities in means, there is still little anticipation of future technology and policy conditions could be further satisfied by introducing tailored measures for specific user groups.

This work analyses the effectiveness of an off-grid solar photovoltaic system for the charging of electric vehicles (EVs) in a long-term parking lot. The effectiveness of charging is investigated through analysis of the states of charge (SoC) at departure of EVs plugged in at the parking lot over the simulated year. Although the share of vehicles leaving with inadequate charge over the entire year is small, this share is relatively high during low irradiance winter months. We show that an increase in efficiency of the solar modules used in the system and an increase in the minimum duration of time spent at the parking lot are effective within limits at improving charging adequacy. We then formulate three strategies to allocate the available energy in the system with the objective of reducing the number of vehicles leaving at lower SoCs: 1) curtailment of charging beyond 80% state of charge, 2) prioritised charging of vehicles at low SoCs and 3) prioritised charging based on both SoC and time before departure. We identify the strategy prioritising vehicles with low state of charge to be most effective, but performance in the worst month remains a challenge for the location considered.