Energy Systems Research Articles

Pathways to a sustainable electricity sector in Kenya: Challenges and transformational factors

Which factors may enable a secure, affordable, and sustainable development of the Kenyan energy system? The present study aims to understand how the country's energy system could be structured in 2050, to unravel the main challenges, and to identify critical leverage points for policy action. To this end, we designed energy scenarios for Kenya using cross-impact balance and succession analysis, drawing extensively from expert judgments. The results highlight the importance of improving the quality of the grid, further reforming the electricity market structure, encouraging more competition, and promoting decentralization as the main leverage points for ensuring a secure and sustainable energy future.

Enhancing Cybersecurity in Energy IT Infrastructure Through a Layered Defense Approach to Major Malware Threats

This study examines the cybersecurity vulnerabilities of energy IT infrastructure in the context of rapid digital transformation and network expansion. While these advancements have improved efficiency, they have also increased susceptibility to cyber threats, particularly from malware such as Industroyer, Triton, NotPetya, and BlackEnergy3. By analyzing these malware threats, this research identifies key weaknesses in energy systems and highlights the need for enhanced anomaly detection, network segmentation, and system integrity checks. To address these vulnerabilities, this study proposes a layered security architecture in which each layer—physical, control, network, application, and security—provides independent protection while integrating into a unified defense strategy. This research emphasizes the necessity of combining technical-, organizational-, and policy-based responses to bolster cybersecurity across all levels of energy infrastructure. Key recommendations include immediate vulnerability patching, improved international cooperation, stronger legal frameworks, enhanced cybersecurity education, and the establishment of a unified command structure. This study provides practical insights and strategies for strengthening the cybersecurity of energy systems through a comprehensive, integrated approach.

Adaptable and Generic Methods for Monitoring and Prognostics of Energy Assets

Monitoring and prognostics of energy assets are crucial for maintaining their reliability and efficiency. Effective monitoring ensures that potential issues are identified early, preventing unexpected failures and optimizing maintenance schedules. However, several challenges complicate this process in real-world scenarios, including poor data quality, low-fidelity and sparse data, the influence of external environmental factors, and diverse operating conditions and asset types. These challenges highlight the need for adaptable and generic solutions that can handle variability and complexity across different energy systems. This Ph.D. project aims to address these challenges by developing scalable, data-driven approaches for monitoring and prognostics. By focusing on creating adaptable and generic frameworks, the research seeks to provide robust solutions for real-world monitoring and prognostic problems for energy assets.

A bi-objective optimization framework for configuration of battery energy storage system considering energy loss and economy

To address a bi-objective optimization configuration problem of battery energy storage system (BESS) in distributed energy system (DES) considering energy loss and economy, a perturbation and observation approach (P&O) is proposed in this article. First, in a DES, the configuration model of BESS is established. Then, a novel way is designed that transforming a bi-objective optimization problem into a single objective optimization problem with variable conditions. And the P&O process of the proposed method is presented. Finally, in a simulation case, compared with a single optimization objective of energy loss or economy, the P&O method improves 5.71-fold or 2.94-fold in each direction, respectively and effectively balances the contradiction between them. In addition, with the efficiency and electricity cost of BESS increasing, the rated capacity of BESS changes by approximately 10%. And the location is a key factor affecting the configuration scheme of BESS in DES.

Regional Framework Towards Establishing Treatment, Storage, and Disposal (TSD) Facilities for PV Waste Management in the Philippines: A Case Study of Laguna Province

Abstract. The accelerated adoption of photovoltaic (PV) systems for renewable power generation in the Philippines will yield a tremendous amount of PV waste. However, the country lacks a comprehensive framework for understanding PV module waste volume growth and optimally siting Treatment, Storage, and Disposal (TSD) facilities for PV waste management based on minimum siting factor. The study aims to develop a regional framework that utilizes a geographic information system (GIS)-based approach to find the potential sites and optimal locations of TSD facilities in Laguna, Philippines, based on the estimated PV module waste growth of solar energy systems with service contracts and minimum siting criteria under Department of Environment and Natural Resources (DENR) Administrative Order 2013-22. By 2060, the projected amount of PV module waste in Laguna province will be around 162,230 metric tons based on the waste projection results. The suitable sites cover around 19,720.5 hectares or 11.21% of the total land area of Laguna, which were determined by various siting factors that encompass social, economic, and environmental factors and obtained using binary suitability analysis and vector overlay analysis. The optimal locations of the two TSD facilities were identified using strategic positioning based on hotspot analysis, clustering algorithm, and proximity analysis. Consequently, the distance and GHG emissions of the two optimal locations were calculated. Indeed, the approach will serve as a guide for policymakers and other stakeholders in understanding PV module waste growth and strategically and optimally position TSD facilities on suitable sites for efficient and effective PV waste management.

An agile life cycle assessment for the deployment of photovoltaic energy systems in the built environment

An agile life cycle assessment for the deployment of photovoltaic energy systems in the built environment

Life cycle environmental impact assessment of the “Sindhuja-I” wave energy converter

The life cycle assessment (LCA) is an inevitable part of ocean wave energy systems. This paper presents an LCA of the Sindhuja-I ocean wave energy converter (WEC). The WEC is a point absorber type WEC tested at the Tuticorin port in India. This study utilized the ISO 14044 standard and SimaPro LCA software to assess the environmental impact of the WEC in comparison to a coal power plant, offshore wind, and tidal energy devices. The functional unit considered is the generation of 1 kWh of electricity. The WEC has a global warming potential of 174 gCO2-eq/kWh, showcasing an impressive 81.9% reduction in emissions compared to coal power plants. Stainless steel contributes significantly to emissions, accounting for 93.7%, 94.6%, 99.4%, and 94.1% of total CO2, NOx, SO2, and PM2.5 emissions, respectively. The paper emphasizes the potential environmental benefits of recycling WEC materials at the end of their lifespan. Furthermore, the study suggests that the longevity of a point absorber device can positively impact its overall environmental footprint, given its minimal moving parts and low maintenance requirements. The WEC has a promising environmental footprint of ocean wave energy conversion, particularly compared to traditional fossil fuel-based power generation.

THE POTENTIAL FOR PEER-TO-PEER ELECTRICITY TRADING IN GEORGIA

The global energy transition is fundamentally reshaping electricity markets, moving from centralized systems reliant on fossil fuels to decentralized, renewable energy solutions. Distributed energy resources such as solar panels and storage batteries are empowering consumers to become active participants in the energy market. Peer-to-peer (P2P) electricity trading, enabled by blockchain technology, presents a new model for consumers to trade surplus energy directly with one another, bypassing traditional suppliers. This article explores the potential of P2P electricity trading in Georgia, a country with significant renewable energy resources but limited experience with decentralized energy systems. As Georgia aligns its energy policies with European regulations, the development of a P2P trading market could enhance energy security, empower prosumers, and drive local economic development. Through an analysis of global trends, technological innovations, and the current Georgian energy landscape, this article assesses the opportunities and challenges in implementing P2P trading. By building the necessary infrastructure and fostering public participation, Georgia has the potential to transform its energy market and contribute to a more resilient and sustainable energy future.

Financial subsidy optimization to promote renewable energy development for sustainable development goal

Enhancing the efficacy of financial subsidies holds paramount significance in fostering sustainable development due to their influence on energy utilization, installation scalability, and the crucial pursuit of decarbonization. Despite a surge in scholarly interest surrounding financial subsidies for renewable energy, the literature studies fall short in comprehensively addressing the factors that impact on the accuracy and reliability of the model for identifying optimal financial subsidies. This paper introduces a robust approach to optimize financial subsidies to achieve the predefined target for renewable energy installation, considering the equilibrium between investor remuneration and government subsidy outlay. Center to this approach is the integration of a forward-looking price forecasting model and the establishment of an economic evaluation approach based on empirical data encompassing weather patterns, technical factors, investor expectations, subsidy disbursements, market risk assessments, and other pertinent parameters. The case study of Taiwan is conducted, and the results indicate that, in the baseline scenario, the financial subsidy is only effective in the risk-neutral market with a small solar system; in the mix scenario, the benefit of energy system increased at least 4.5%, however, the mix scenario is still ineffective to encourage the renewable energy development; and in the optimal scenario, by providing accurate recommendations for optimal financial subsidies, government can achieve the predefined target, even with reduced subsidies due to declining installation costs.

Improved hydrogen detection in SnO2-based materials using CuxPd bimetallic catalyst

Hydrogen (H2) holds promise as a replacement for conventional fossil fuels in future energy systems. However, developing a rapid, highly sensitive, and cost-effective H₂ sensor remains a significant challenge. This study first uses a low-cost-oriented CuxPd binary alloy for SnO2 for H2 sensing, and the corresponding properties are evaluated comprehensively. The results of H2 sensitivity demonstrate that our bimetallic CuxPd significantly enhances the sensitivity of SnO2, which is attributed to the synergistic effect of CuxPd bimetallic catalysts Our CuxPd/SnO2 nanocomposite materials not only exhibit high response (401 @ 1000 ppm at 100 °C), rapid response/recovery time (1/12 s @ 1000 ppm at 100 °C) and still maintains good response (1.42) to 1 ppm H2 gas. The introduction of Cu effectively stabilizes Pd and creates more oxygen vacancies, which provides a more catalytic effect than monometallic Pd. Therefore, this work provides a scenario for low-cost catalysis of H2 detection.

How to Assess and Predict Electrical Double Layer Properties. Implications for Electrocatalysis.

The electrical double layer (EDL) plays a central role in electrochemical energy systems, impacting charge transfer mechanisms and reaction rates. The fundamental importance of the EDL in interfacial electrochemistry has motivated researchers to develop theoretical and experimental approaches to assess EDL properties. In this contribution, we review recent progress in evaluating EDL characteristics such as the double-layer capacitance, highlighting some discrepancies between theory and experiment and discussing strategies for their reconciliation. We further discuss the merits and challenges of various experimental techniques and theoretical approaches having important implications for aqueous electrocatalysis. A strong emphasis is placed on the substantial impact of the electrode composition and structure and the electrolyte chemistry on the double-layer properties. In addition, we review the effects of temperature and pressure and compare solid-liquid interfaces to solid-solid interfaces.

A Multi-Objective Energy Optimization Model for Renewable Energy Systems with Hybrid Energy Storage

Building a Renewable Energy System (RES) is a viable way to address resource depletion and accomplish decarbonization. This study presents a hybrid power system that combines wind, solar, battery, and thermal energy storage. It also examines the co-optimization of scheduling and operation for multiple objectives. The hybrid system combines the affordability of thermal energy storage (TES) with the adaptability of batteries to effectively address the issue of intermittent RES. A new approach for integrated operation is offered, which relies on the electrical block's operation limit. The planning-operation co-optimization system considers minimizing the Net Present Cost (NPC) and reducing power supply likelihood todetermine the best operation limit and sizing decision factors. The co-optimization issue is addressed using novel multi-objective decision-making (MO-DM). This approach incorporates the Decision-Maker (DM) preferences data to direct the evolutionary process toward the desired area. In addition, a data-driven prediction model captures the risks and losses associated with wind generation. The case study's findings indicate the following: (1) The data-driven system has a higher level of precision in wind power projection when compared with commonly used physical simulations. (2) The suggested MO-DM exhibits superior integration, variety, and robustness achievement in the DMchosen area compared to others. (3) The combined battery-thermal energy storing structure achieves improved economy and dependability through the optimum organized operation approach, in contrast to using a single energy storage system under various testing constraints.

Progress in Improving Photovoltaics Longevity

With the increase of photovoltaic (PV) penetration in the power grid, the reliability and longevity of PV modules are important for improving their payback period and reducing recycling needs. Although the performance of PV systems has been optimized to achieve a multi-fold increase in their electricity generation compared to ten years ago, improvements in lifespan have received less attention. Appropriate operation and maintenance measures are required to mitigate their aging. PV cells and modules are subject to various degradation mechanisms, which impact their long-term performance and reliability. Understanding these degradation processes is crucial for improving the lifetime and sustainability of solar energy systems. In this context, this review summarizes the current knowledge on key degradation mechanisms (intrinsic, extrinsic, and specific) affecting PV modules, as well as on-site and remote sensing methods for detecting PV module defects and the mitigation strategies employed for enhancing their operational lifetime under different climatic conditions in the global environment.

A comprehensive scheme for power management of FC/SC/battery, and solar-roof PV source in electric vehicle systems.

This paper proposes a new energy management system to combine Fuel Cells (FC) and photovoltaic (PV) panels as primary power sources. Also, battery and Super Capacitor (SC) banks are considered as secondary energy systems. The high power density and the fast dynamics of SCs combined with the high energy density and medium dynamics of batteries would be an ideal combination for FC vehicles. The high step-up DC/DC converter is used along with the implementation of the maximum power point tracking algorithm (MPPT) to adapt the low power of PV panels with the high power of DC-Link. Also, an evolutionary optimization algorithm is proposed along with the FOPI controller to improve the output of the energy management algorithm and control the sources more efficiently. The simulation results are validated for a standard urban driving cycle. It indicates for the case of the sustained presence of a PV source during a typical driving cycle, the source delivers about 55% of its maximum power.

Latent Information in the Evolving Energy Structure

Recent studies indicate that Artificial Intelligence (AI) technology, characterized by its integration of information and communication technology attributes, exerts a multifaceted influence on the energy system. The authors employ Difference-in-Differences (DID) and Triple-Difference (DDD) models to investigate the effects of AI. The research initially demonstrates that AI may exhibit dual attributes of constraining energy structure. Specifically, the rapid development of AI tends to increase the proportion of fossil fuel-based electricity generation while optimizing the consumption of renewable energy. Furthermore, the degradation of energy structure stems from the surge in electricity consumption by AI, which the renewable energy consumption capacity is unable to satisfy. Lastly, industrial agglomeration effects and the construction of the digital economy have positive impacts on development of renewable energy; technological innovation aids in mitigating the negative shocks to the energy structure. This study provides a new perspective on the role of AI technology in energy transition.

Comparative Approaches to Energy Transition: Policy Guideline for Enhancing Thailand’s Path to a Low-Carbon Economy

Thailand’s transition to a low-carbon economy faces significant challenges, including a dependency on fossil fuels, fluctuating energy costs, and limited policy clarity. This study conducts a comparative analysis of energy transition policies in Germany, Japan, Australia, Malaysia, and Singapore to derive actionable lessons that can be adapted to Thailand’s socio-economic and energy contexts. Using the Integrated National Energy Planning (INEP) framework and Network Governance Theory, the research identifies key strategies, such as setting clear and achievable renewable energy targets, establishing robust legal frameworks, fostering multi-stakeholder engagement, and encouraging decentralized governance. The findings highlight the importance of long-term vision, inclusive governance, and targeted investments in renewable technologies to accelerate energy transitions. This paper presents policy guidelines to enhance Thailand’s energy security and contribute to its climate goals by promoting public awareness and strengthening institutional capacities. By adapting these strategies, Thailand can align with global energy trends, reduce its reliance on fossil fuels, and advance toward a resilient and sustainable energy system, aligned with global energy trends while addressing its unique socio-economic context.

Sensitivity Analysis of a Nuclear Hybrid Energy System With Thermal Energy Storage in Deregulated Electricity Markets Considering Time Series Uncertainty in Electricity Price

ABSTRACTAdding thermal energy storage to nuclear power plants has been proposed as a way to allow nuclear plants to operate more flexibly and potentially be more competitive in deregulated electricity markets. The economics of these systems in deregulated markets are subject to uncertainties in capital costs, operating costs, and revenue. This study quantifies the uncertainty in the net present value of a nuclear power plant with integrated thermal energy storage in three U.S. deregulated electricity markets considering these sources of uncertainty and quantifies, for the first time, the relative contributions each source makes to the overall uncertainty. To accomplish this, a computationally efficient block bootstrap method is introduced to quantify uncertainty contributions from the stochastic time series of electricity prices, achieving a two order of magnitude decrease computational time compared to the model‐based methods used in previous works while also relaxing several strict assumptions made by the model‐based approach. Up to 18.5% of the overall variance in net present value is attributable to variance in the electricity price stochastic process, with this sensitivity varying significantly across markets.

Electric Vehicles for a Flexible Energy System: Challenges and Opportunities

As the adoption of Electric Vehicles (EVs) accelerates, driven by increasing urbanization and the push for sustainable infrastructure, the need for innovative solutions to support this growth has become more pressing. Vehicle-to-Grid (V2G) technology presents a promising solution by enabling EVs to engage in bidirectional interactions with the electrical grid. Through V2G, EVs can supply energy back to the grid during peak demand periods and draw power during off-peak times, offering a valuable tool for enhancing grid stability, improving energy management, and supporting environmental sustainability. Despite its potential, the large-scale implementation of V2G faces significant challenges, particularly from a technological and regulatory standpoint. The success of V2G requires coordinated efforts among various stakeholders, including vehicle manufacturers, infrastructure providers, grid operators, and policymakers. In addition to the technical barriers, such as battery degradation due to frequent charging cycles and the need for advanced bidirectional charging systems, regulatory frameworks must evolve to accommodate this new energy paradigm. This review aims to provide a comprehensive analysis of V2G technology, focusing on different perspectives—such as those of users, vehicles, infrastructures, and the electricity grid. This study will also explore ex ante, ex post, and ongoing assessment studies, alongside the experiences of pioneer cities in implementing V2G.

Research on Joint Forecasting Technology of Cold, Heat, and Electricity Loads Based on Multi-Task Learning

The cooperative optimization and dispatch operation of the integrated energy system (IES) depends on accurate load forecasts. A multivariate load, joint prediction model, based on the combination of multi-task learning (MTL) and dynamic time warping (DTW), is proposed to address the issue of the prediction model’s limited accuracy caused by the fragmentation of the multivariate load coupling relationship and the absence of future time series information. Firstly, the MTL model, based on the bidirectional long short-term memory (BiLSTM) neural network, extracts the coupling information among the multivariate loads and performs the preliminary prediction; secondly, the DTW algorithm clusters and splices the load data that are similar to the target value as the input features of the model; finally, the BiLSTM-attention model is used for secondary prediction, and the improved Bayesian optimization algorithm is applied for adaptive selection of optimal hyperparameters. Based on the game-theoretic view of Shapley’s additive interpretation (SHAP), a model interpretation technique is introduced to determine the validity of the liquidity indicator and the asynchronous relationship between the significance of the indicator and its actual contribution. The prediction results show that the joint prediction model proposed in this paper has higher training speed and prediction accuracy than the traditional single-load prediction model.

Multi-Objective Optimization of Insulation Thickness with Respect to On-Site RES Generation in Residential Buildings

This paper investigates the optimization of insulation thickness with respect to the integration of renewable energy systems in residential buildings in order to improve energy efficiency, maximize the contribution of renewables and reduce life cycle costs. Using the DesignBuilder and EnergyPlus software, this study models a representative two-story residential building located in Athens, Greece. The building envelope features extruded polystyrene thermal insulation and windows with unplasticized polyvinyl chloride frames and low-e glazing. Six scenarios with hybrid renewable energy systems are analyzed, including air- and ground-source heat pumps, solar thermal systems and a biomass fired boiler, so as to assess energy consumption, economic feasibility and internal air temperature conditions. A Pareto-fronts-based optimization algorithm is applied to determine the optimal combination of insulation thicknesses for the walls, the roof and the floor, focusing on minimizing the life cycle cost and maximizing the percentage of renewable energy utilized. The results demonstrate that scenarios involving biomass boilers and solar thermal systems, both for heating and cooling, when combined with reasonable thermal protection, can effectively meet the recent European Union’s directive’s goal, with renewable energy systems contributing more than 50% of the total energy requirements, whilst maintaining acceptable internal air temperature conditions and having a life cycle cost lower than contemporary conventional buildings.