Transformation Of Energy System Research Articles

Coordinating the energy transition: Electrifying transportation in California and Germany

California and Germany share ambitious emission reduction targets. Yet California is ahead of Germany in electrifying transportation by several metrics, including the number of public charging stations. We show that variation in the politics of coordination in California and Germany explains the different outcomes. Transforming energy systems requires coordination across various complementary technologies and infrastructures—here between the supply of electric vehicles and the buildout of charging stations. In California, a strong electrification coalition emerged across automakers selling electric vehicles as well as utilities and third-party firms providing charging infrastructure. Power market rules made capital investments for charging infrastructure instantly profitable for California monopoly utilities. By contrast, in Germany's liberalized power market, investing in capital-intensive charging infrastructure was not profitable for electric utilities. As a result, utilities did not emerge as a political force in the electrification coalition. Instead, utilities and automakers were in gridlock, failing to coordinate electric vehicle rollout and public charging station buildout. Our findings highlight the limits of business-led coordination, raising the question which institutions help address coordination failures in clean energy transitions.

Zero-Trust Zero-Communication Defence against Hybrid Cyberattacks in Distributed Energy Resources Using Mean Field Reinforcement Leaning

As the evolution of smart grids accelerates, distributed energy resources (DERs) emerge as key elements in the transformation of global energy systems. However, the integration of these technologies introduces significant cybersecurity vulnerabilities, notably false data injection (FDI) and a direct load-altering attack (DLAA). Traditional load-altering attacks require a huge attack load and, thus, are not practical to implement. In contrast, in modern DER environments where households become “prosumers” with high-power energy generation, the implications of such attacks are substantially amplified. This paper considers a hybrid cyberattack that includes both FDI and a DLAA, and presents a hierarchical, optimal load adjustment framework that addresses these security concerns. A centralized optimizer first calculates the ideal load-shedding strategies for each substation, which are then securely broadcast to households. To address the complexities at the individual household level, we introduce a novel reinforcement learning algorithm termed Mean Field Deep Deterministic Policy Gradients (MF-DDPG). This algorithm employs mean-field game theory to enable decentrally coordinated decision-making among each household, making it particularly effective in zero-trust scenarios. Through this multifaceted approach, we offer a robust countermeasure against load-altering attacks, thereby enhancing the resilience and stability of advanced smart grids.

Energy system optimization based on fuzzy decision support system and unstructured data

To address the complex challenges in energy systems, this study proposes a novel optimization framework that integrates fuzzy decision support and unstructured data processing technologies. This framework aims to improve efficiency, reduce costs, decrease environmental impact, increase system flexibility, and enhance user satisfaction, thereby promoting sustainable development in the energy industry. The framework combines the innovative Energy Semantic Mapping Model (ESMM) and the advanced deep learning architecture ResNet to process textual and visual data effectively. ESMM enables accurate prediction of energy demand, while ResNet significantly reduces equipment maintenance costs and improves energy distribution efficiency. These advancements are critical as they address the limitations of existing approaches in handling large-scale unstructured data and making informed decisions under uncertainty. The Environmental Impact Assessment (EIA) confirms the model's effectiveness in reducing carbon emissions. A comprehensive economic analysis demonstrates substantial cost savings in energy procurement and operations and maintenance, with overall savings exceeding 25%. Enhanced user satisfaction and reduced system response times further validate the practical utility of the proposed approach. Additionally, a genetic algorithm is used to optimize the fuzzy rule base, enhancing the robustness and adaptability of the model. Experimental results show superior performance compared to traditional systems, providing strong empirical evidence for the intelligent transformation of energy systems. This research contributes to the field by offering a more sophisticated and flexible solution for managing energy systems, particularly in terms of leveraging unstructured data and improving decision-making processes.

The Benefits of Positive Energy Districts: Introducing Additionality Assessment in Évora, Amsterdam and Espoo

Positive Energy Districts (PEDs) are a promising approach to urban energy transformation, aiming to optimize local energy systems and deliver environmental, social and economic benefits. However, their effectiveness and justification for investment rely on understanding the additional value they provide (additionality) in comparison to current policies and planning methods. The additionality perspective is not used yet in current evaluations of PED demonstrations and pilots. Therefore, this paper introduces the concept of additionality in the evaluation of PEDs, focusing on the additional benefits they bring and the circumstances under which they are most effective. We discuss the additionality of PEDs in addressing the challenges of climate neutrality and energy system transformation in three European cities that are funded by the European Commission’s H2020 Programme. It should be noted that given the ongoing status of these projects, the assessment is mainly based on preliminary results, as monitoring is still ongoing and quantitative results are not yet available. The paper discusses the drivers and barriers specific to PEDs, and highlights the challenges posed by technical complexities, financing aspects and social and legal restrictions. Conclusions are drawn regarding the concept of additionality and its implications for the wider development of PEDs as a response to the challenges of climate neutrality and energy system transformation in cities. We conclude that the additionality perspective provides valuable insights into the impact and potential of PEDs for societal goals and recommend this approach for use in the final evaluation of R&I projects involving PEDs using actual monitored data on PEDs.

The Use of Fuzzy Modelling Based on Expert Knowledge to Determine Poland’s Energy Security Index Taking into Account Political Conditions

This article presents the results of research on the energy security index in Poland. Since the development of renewable energy sources forced by the transformation of the national energy system will require an increased supply of rare earth elements, the level of demand for these metals was taken into account when determining the energy security index. Furthermore, the development of renewable energy sources in Poland will directly depend on the volume of energy demand and, as the events of previous years have shown, on political and legal conditions, especially in the case of wind energy. Since some of these factors are qualitative, it was impossible to use a quantitative method. Therefore, fuzzy sets were used. Fuzzy modelling is based on expert knowledge. Using this method, the authors created three alternative scenarios for the development of Poland’s energy security index: pessimistic, optimistic, and the most probable.

Impact of different CO2 price paths on the development of the European electricity system

In energy system transformation studies, the assumption of linearly rising CO2 prices is common and based on the decreasing issued European allowances (EUA). The actual auction price for allowances is influenced by market dynamics, resulting in non-linear variations in CO2 prices due to the possibility of banking allowances. This study explores the impact of non-linear CO2 price trajectories on the European electricity market. Various scenarios, such as increasing prices with the market interest rate, early price peaks, collapse, or fluctuations, are examined until 2030. The study quantifies the effects on power plant investments, profitability, consumer costs, and government revenues. The findings reveal that early and high price signals lead to an earlier transition with 7 % more wind power plants but at 4 % higher costs. Conversely, lower initial prices delay power plant investments in wind power plants by 6 % and result in 21 % higher emissions. Compensation for climate impact costs can yield a positive cost-benefit analysis in scenarios with early and high price signals when emissions are avoided through mechanisms like the Market Stability Reserve (MSR).

A reflective analysis of China's energy policy from the perspective of systemic energy justice principles

The idea of energy justice has been reflected and implemented in China’s energy policy system over years. However, the existing normative basis of energy justice remains imperfect. China’s special political system and Confucian concept of justice, and its particular focus on energy security, have made its energy transition practices highly efficient but also prone to violating recognition, distributional and procedural justice, resulting in a victim structure that sacrifices the few for the well-being of the many. It is essential to introduce energy justice to achieve sustainable development of China’s energy system and policy transformation in the new era, as energy justice will provide insights for policy stakeholders regarding how to address complex and interrelated energy production and acquisition issues. In doing so, the first step is to comprehensively examine the existing energy injustice in China’s energy life cycle and then apply systemic energy justice to optimise China’s future energy policies. Specifically, policymakers should first reaffirm recognition justice by recognising energy rights, including the fundamental rights of energy vulnerable groups and the natural environment together with the rights of consumers as energy producers. Secondly, procedural justice should be strengthened from three perspectives, namely decision-making participation, information disclosure and judicial relief. Thirdly, distributive justice can be effectively promoted by establishing benefit-sharing mechanisms, setting fair, reasonable and non-discriminatory energy prices, and developing compensation mechanisms between regions.

Decentralized energy trading framework with personalized pricing for energy community embedded with shared energy storage

Decentralized energy trading techniques are promising to become the next-generation scheme for energy management with the transformation of energy systems. Influenced by the sharing economy principle, the deployment of shared energy storage (SES) can mitigate the investment of storage devices and facilitate the construction of decentralized energy trading. Under such circumstances, this paper proposes a comprehensive energy trading framework for the energy community constituted of SES, prosumers, and retail energy providers. A Stackelberg game method is utilized to depict the interactions between prosumers and SES, where SES is performed as a leader and prosumers are followers. Besides, prosumers participate in the market to optimize social welfare via peer-to-peer (P2P) energy sharing with other prosumers or energy trading with SES and the main grid. We prove the existence and the uniqueness of the Stackelberg equilibrium (SE). Considering the supply and demand ratio and market contribution, a personalized pricing approach is presented for prosumers and SES to promote market competitiveness. We leverage the fully decentralized algorithm based on the fast alternating direction method of multiplier (ADMM) to solve the model of prosumers. Finally, numerical simulation demonstrates that the proposed transactive framework is economically beneficial for all participants, including SES and prosumers.

Econometric Analysis of the Influence of Factors on the Share of Energy From Renewable Sources in the EU

The use of renewable energy is at the core of EU energy policy, reducing dependence on fossil fuels imported from non-EU countries, reducing greenhouse gas emissions and decoupling energy costs from oil prices. Currently, 22.5% of energy consumed in the EU comes from renewable sources. This increase over 2021 is due to strong growth in solar energy. This share is also increasing due to the consumption of non-renewable energy sources in 2022. According to expert forecasts, the share of renewable energy sources in Europe will continue to grow. Achieving the 42.5% target by 2030 will require a deep transformation of the European energy system. The very strong climate and energy policies pursued in the EU for about a dozen years and aimed at limiting emissions of harmful substances into the environment have led to a gradual abandonment of traditional energy sources. Increasing demand for energy while reducing its supply from traditional sources means that in order not to make the economy too dependent on energy imports, the dynamic development of renewable energy is necessary. The EU is therefore taking very extensive operational and strategic actions to use other sources for production, such as wind, solar energy, mechanical water energy, biomass and geothermal energy, as well as tidal waves, ocean heat, wave energy and sea currents. In this study, we assess the impact of energy, economic and environmental factors on the share of renewable energy in the EU. The aim of these studies was to identify the energy, economic and environmental indicators that have the greatest impact on the share of energy from renewable sources in the European Union. The study was conducted using the Statgraphics Centurion software package. The source data for the study was data from the official Eurostat website for the period from 2012 to 2022. The results of this study show that changes in gross domestic product in market prices per capita have a positive impact, as do changes in greenhouse gas emissions per capita negatively affect the share of energy from renewable sources in the EU in the period 2012-2022. This may most likely be due to the fact that EU countries are more likely to invest in renewable energy as they can afford to invest in the development of expensive renewable energy technologies and support subsidies for the promotion and regulation of renewable energy. The negative impact of per capita greenhouse gas emissions on renewable energy development is due to the high share of coal in the EU energy mix, meaning that coal not only has negative environmental impacts, but also negative environmental impacts. development of renewable energy.

A Fuzzy OLTC Controller: Applicability in the Transition Stage of the Energy System Transformation

This paper introduces a Fuzzy Logic Controller designed for an on-load tap changer within medium voltage distribution systems with bulk penetration of Distributed Energy Resources. As the on-load tap changer remains one of the most essential forms of voltage regulation in medium voltage distribution networks, improving its operation is a cost-effective response to the emerging voltage violations caused by intermittent generation during the early stages of the energy system transformation. Software-in-the-loop simulations were conducted to validate the effectiveness of the proposed algorithm compared to the conventional methods. A modified CIGRE Medium Voltage Distribution Network Benchmark in European Configuration was modelled while the controller code developed in Python 3.12 was running on a PC, both coupled in a real-time closed-loop environment. The analyses showed that the proposed algorithm managed to reduce overvoltage from 7.02% to 4.85% in the benchmark network, thus demonstrating that the algorithm is efficient and ready for on-field implementation.

INTEGRATING SOLAR POWER WITH EXISTING GRIDS: STRATEGIES, TECHNOLOGIES, AND CHALLENGES – A REVIEW

Integrating solar power into existing electrical grids is critical to realizing a sustainable and resilient global energy landscape. This review paper offers a thorough overview of solar power's significance and potential for transforming energy systems, emphasizing its benefits for grid stability, fossil fuel reduction, and environmental sustainability. It details essential strategies for successful solar integration, such as adopting both grid-tied and off-grid systems, advancements in energy storage to mitigate solar intermittency, and applying innovative grid technologies for enhanced energy management. Additionally, the paper navigates through the technological breakthroughs aiding solar power's incorporation into grids and confronts the challenges, including technical issues like grid scalability and economic barriers such as investment costs, regulatory complexities, and social-environmental impacts. Drawing on case studies from leading regions in solar integration, it distills lessons learned and identifies strategies and technologies that have surmounted these hurdles. The review also projects future trends and innovations in solar technology and grid management, underscoring the need for ongoing innovation and supportive policies to bolster solar power's role in energy systems. By collating insights into solar power integration's current state and prospects, this paper will guide policymakers, industry players, and researchers toward harnessing solar energy's full potential, highlighting its indispensable contribution to a sustainable energy future.

Exploring carbon emission accounting methods for typical public institutions: a case study of hospitals

Typical public institutions such as government offices, hospitals, and schools play important leading and exemplary roles in the green and low-carbon development of the whole society. This paper analyzes the business and energy consumption characteristics of public institutions, as well as the characteristics of personnel travel, and constructs a carbon accounting model for public institutions. It innovatively proposes a methodology for carbon accounting of personnel travel related to public institutions and validates and analyzes it using a comprehensive hospital as an example. The paper analyzes the carbon emission characteristics of various energy types, systems, and types of travelers in hospitals, provides schemes for the transformation of main energy systems, and corresponding emission reduction effects, thereby providing technical support for the full-chain carbon accounting of public institutions. Additionally, this paper explores the carbon reduction pathways for hospitals to support the peak carbon and carbon neutrality goals of public institutions, and promote the high-quality development of public institutions in China.

Rethinking Energy Geopolitics: Towards a Geopolitical Economy of Global Energy Transformation

ABSTRACT We are in the midst of a global energy system transformation (GEST) which is rewiring the world economy, opening new axes of political contestation, and revolutionising the energetic basis of human civilisation. Energy geopolitics has not yet reconciled itself to this challenge. The field has traditionally been preoccupied with the dependence of Western states on cross-border flows of fossil fuels. More recently, efforts have been made to prospectively map out what the geopolitics of a fully renewable world might look like. What both literatures miss, however, is the very fact of the GEST: that we are living through a changing and contested process of global transformation, across interacting high- and low-emissions systems, whose contours are open and actively constructed over time. In this paper, we start to develop a provisional framework to make sense of the GEST, that is able to capture the full scale of the transformation, and its dynamic, contingent, constructed nature. We attend to three areas of geopolitical economy: the wide-ranging material dimensions of the transformation, its geographical space-making, and its conflict-ridden political economy. We then apply this framework to two case studies, one looking at the fraught role of fossil gas as a ‘transition fuel’, the other at lithium-ion batteries.

Systematic Development of Application-Oriented Operating Strategies for the Example of an Industrial Heating Supply System

The ongoing challenge to ensure a sustainable and affordable energy supply forces industrial companies to transform their energy system. This transformation usually leads to an increase in topological complexity, which in turn results in increased operational complexity. Existing approaches from the field of supervisory and optimal control are capable of mastering complex operational problems. However, due to the complex and non-transparent implementation, there is still no industrial penetration, which hinders the necessary transformation of energy systems. This work aims at establishing trust in these control approaches and presents a procedure model for the systematic development of application-oriented operating strategies for industrial energy heating systems. It combines research approaches from the fields of sequencing control and approximate MPC to extract rule-based operating strategies, which are inherently easy to understand and implementable. By splitting the procedure model into five phases, expert knowledge can be integrated in a targeted manner. The procedure model is validated by the exemplary application to an industrial heating supply system. As part of an optimization study, the operating strategy developed is compared with both an MPC strategy and a baseline strategy. While the conventional MPC approach represents the upper limit of optimality, the operating strategy developed is able to achieve comparable results. Compared to the baseline strategy, a relative reduction in operating costs of 5.4% to 37.0% is achieved.

Implementing Smart Grid Technology in Developing Countries: Challenges, Opportunities, and Pathways to Sustainable Energy Solutions

The integration of smart grid technology is becoming crucial for developing countries to address the increasing energy demands and to transition towards sustainable and reliable electricity systems. This paper discusses the significant challenges these nations face, such as outdated infrastructure, high transmission and distribution losses, and limited access to electricity. With electricity consumption projected to grow by over 50% by 2030 in emerging markets and developing economies, smart grids offer benefits including enhanced reliability, reduced losses, and better integration of renewable energy sources. However, high upfront costs, lack of skilled personnel, inadequate regulatory frameworks, and resistance to change pose substantial barriers. This study explores the potential of smart grids to transform energy systems, presenting case studies of successful implementations and highlighting strategies for overcoming barriers. Emphasis is placed on innovative financing models, capacity building, technology leveraging, and stakeholder engagement as pathways to sustainable smart grid deployment.

Enhanced light-responsive supercapacitor utilizing BiVO4 and date leaves-derived carbon: A leap towards sustainable energy harvesting and storage

This study explores light-responsive supercapacitors, aiming to transform energy systems by enabling the simultaneous conversion and storage of light into electricity. The study introduces an innovative light-responsive supercapacitor, employing bismuth vanadate (BiVO4) as the photoactive material and date leaf-derived carbon (DLC) as the conductive electrode material. The device also incorporates fluorine-doped tin oxide (FTO) as the transparent current collector and Na2SO4 as the electrolyte. The constructed FTO/BiVO4/DLC//DLC/FTO asymmetric light-responsive supercapacitor showcased remarkable electrochemical performance, achieving a capacitance of ∼150 F/g at a current density of 0.5 A/g, thereby validating its effective charge transfer capacity during electrical activities. Further experimentation with varying photo-charging times resulted in a peak specific capacitance of ∼290 F/g. The device demonstrated an energy density of around ∼13 Wh/kg and a power density of ∼200 W/kg in the absence of light, with the energy density notably doubling to 26 Wh/kg upon extended photo-charging. Remarkably, the supercapacitor maintained ∼90% of its initial specific capacitance and ∼86% of its Coulombic efficiency following 12000 GCD cycles, underscoring its electrochemical stability and durability. The development of such a proficient and resilient light-responsive supercapacitor holds significant promise for the advancement of the energy-storage sector and offers valuable insights for renewable energy researchers.

Operating optimization of biomass direct-fired power plant integrated with carbon capture system considering the life cycle economic and CO2 reduction performance

Biomass direct-fired power plant integrated with carbon capture system can achieve negative CO2 emission during the power generation, which provides an important technology pathway for the transformation of energy system towards carbon neutrality. Understanding the economic competitiveness and CO2 reduction potential of the plant, and identifying the optimal operating mode are the key to fully exert the advantages of the technology. For this reason, this paper develops life cycle economic and CO2 emission assessment models for the biomass direct-fired circulating fluidized bed boiler power plant (BCFBP) integrated with solvent-based post-combustion carbon capture (PCC) system. The levelized cost and CO2 emission of energy indexes are then applied to evaluate the performance of the BCFBP-PCC system. Based on the life cycle assessment, a novel economy and CO2 reduction dual-objective operating optimization approach is proposed for the BCFBP-PCC to find the optimal hourly power generation and CO2 capture level of the plant under given market conditions. The static investment payback period is employed as a constraint in the optimization to narrow down the range of the solution set and provide clearer guidance for system operation. This paper provides the first work pioneered the economic and negative carbon operation optimization of the BCFBP-PCC system.

Study on the future development prospects of biomass energy in towns, townships, and subdistricts under multi-scenarios —A case study of Harbin City

Biomass energy is the most likely new energy source to replace fossil fuels. This study presents a prediction method for biomass energy supply-demand and changes in supply-demand patterns that connects the past and future. In the study, carbon peaking and carbon neutrality are taken as the time base. The FLUS model is used to simulate future land allocation in four basic scenarios: natural development scenario, agricultural development scenario, low-carbon development scenario and industrial development scenario; and townships, towns, and subdistricts are taken as the basic statistical unit. Based on this, we have examined the suitability of future development of biomass energy in rural and urban areas in each scenario, as well as its contribution to the future energy system transformation that substitutes for fossil energy. This method has been applied to the case study of townships, towns, and subdistricts in Harbin City in China. The study results show that: The degrees to which biomass energy potential can substitute for fossil energy in the four scenarios in 2030 reach 4.21%, 5.62%, 5.47%, and 3.82%, respectively. Under agricultural development scenario, the supply-demand balance areas account for 48.94%, meaning this scenario has the largest potential for energy development and transition; low-carbon development scenario sees the highest degree of spatial supply-demand match, and thus enjoys the most advantages in energy transportation. The degrees to which biomass energy potential can substitute for fossil energy under the four scenarios in 2060 reach 2.01%, 6.96%, 5.35%, and 1.26% respectively. Agricultural development scenario still has the largest development potential, with the proportion of supply-demand balance areas jumping to 50.46%; Finally, low supply-high demand mismatch clusters are mainly concentrated in the main urban area and the central areas of townships, towns, and subdistricts. The high supply-low demand mismatch clusters are mainly distributed in the northeast. Under low-carbon development scenario, the low supply-high demand mismatch ratio has been reduced to 0.92%, the lowest supply-demand mismatch among all scenarios. Therefore, low-carbon development scenario enjoys the most spatial match advantages. This study will serve as an assessment method to advance the spatial development of biomass, and provide a geospatial basis for optimizing the layout of future energy development. Compared with previous studies, it has more spatial attributes, better reflects the complexity of biomass energy changes and is more connected with the measurement results and future policy making. In future research, we will combine multiple types of clean energy into the comparison and combined use to form a more comprehensive and specific research framework for new energy conversion. Longer-term macro-planning will go beyond the application boundaries of this research.

Renewable energy penetration in Nordic and Baltic countries of the EU

The low carbon transition of the energy sector towards a greater penetration of renewable energy sources (RES) is one of the most impressive examples of political and economic change in the European Union. For nearly two decades, the European Union was rightly considered to be a frontrunner in RES development and deployment around the world. This culminated in March 2007 when the 20-20-20-targets were agreed under the European Council Conclusions. They aimed at creating a carbon neutral society by 2050 and replacing fossil fuels with renewables. This target requires huge transformations of energy systems and transformative shifts in economics and society. Even as renewables can provide numerous environmental, social, and economic benefits, their fast penetration may cause various societal challenges and encounter many barriers. Therefore, this paper aims to analyse the achievements of select EU countries in renewable energy development. For this purpose, an indicators framework is applied to monitor the RES drivers and achievements, RES penetration, and attained benefits of low carbon transformations. The case study focuses on Nordic and Baltic countries that are EU member states.

Quasi-dynamic modeling and simulation of district heating systems: A laplace transform-based approach

The technological development direction for China's green and low-carbon energy transformation is constructing a multi-energy collaborative smart integrated energy system. As an essential subsystem of energy systems in northern China, district heating system (DHS) plays a crucial role in ensuring people's livelihood. The energy system transformation and the development of the new generation of heating systems impose increasing demands on the simulation computations of regional heating systems. This paper establishes a quasi-dynamic model for heating systems based on the Laplace transform as the foundation. It transforms the continuous thermal dynamics in the time domain into the Laplace domain for quantitatively analyzing the heat transfer loss characteristics and transmission delay characteristics in the heat transport process. Furthermore, it converts the internal complex transmission processes of the system into equivalent source-load boundary conditions to obtain a thermal state analysis model with clear physical significance. This approach significantly reduces the computational complexity of network analysis while ensuring computational accuracy. The established quasi-dynamic model is applied to cases of different scales. The computational results are compared and validated against the commercial simulation software Apros and actual operational data. The urban DHS case study calculation results show a mass flow mean relative error of 3.02% and a supply/return water temperature mean relative error of 2.46%, supporting more refined dynamic scheduling.