Future Energy Systems Research Articles

Sustainable Energy Planning and Modelling for Global South: A Case Study of the Federal Republic of Nigeria.

This paper reviews the literature regarding the inherent limitations of Modeling practices for sustainable energy planning in the Global South (GS).GS is undergoing economic changes in its energy-setting socio-economic policies such as liberalisation, financial sourcing, and climate change implications of energy projects. Long-term energy planning lays the foundations for effective policies, investment strategies, and targets at the national or regional level. An astute and up-to-date master plan for energy development fosters predictable investment conditions. This makes it an essential prerequisite for scaling up renewable energy technologies. Active energy planning, built on quantitative setting Modeling and stakeholder consultations, allows policymakers to understand and explore the complexities and uncertainties of future energy system evolution. Modeling and simulation (M&S) is a well-known scientific technique that could analyse a system or predict its behaviour before physical construction. Despite being an established methodical tool in engineering, only a few review articles discussing emerging topics in M&S are available in the open literature, especially for renewable and sustainable energy systems. The International Renewable Energy Agency (IRENA) offers energy planning Support, as a guide, with a view to enhancing institutional capacity at the country level and strengthening each country’s ownership of the planning process. The capacity to interpret key energy data into strong energy planning enables nations to develop all-inclusive national energy master plans and to frequently update these as the basis for comprehensive policies and investments. This paper examines the current Modeling and simulation of the energy sector with insights into the approaches, challenges, and prospects of certain selected and suitable energy systems. Additionally, it reveals the limitations of traditional planning tools such as optimisation, econometric, and general simulation models. The paper posits that traditional approaches are inadequate for SED in the GS due to its inherent weakness in guiding future policy decisions. In this work, the 7th SDG: Affordable and Clean Energy, is brought into focus. The paper addresses the Planning approaches, tools, framework, and techniques as revealed in the literature on energy Modeling and policy formulation. The aim is to enhance the country's capacity to analyse energy data and develop scenarios using Modeling tools for long-term energy planning. The additional tools to support energy planning may be selected according to each country’s needs and existing Modeling expertise. Finally, areas that need further research and development in sustainable energy Modeling are highlighted. Keywords: Sustainability, Energy Planning, Modelling, Global South. Proceedings Citation Format Abraham Rasheed Adeyemi (2023): Sustainable Energy Planning and Modelling for Global South: A Case Study of the Federal Republic of Nigeria.. Proceedings of the 37th iSTEAMS Multidisciplinary Cross-Border Conference. 30th October – 1st November, 2023. Academic City University College, Accra, Ghana. Pp 93-106. dx.doi.org/10.22624/AIMS/ACCRACROSSBORDER2023V2P8

Experimenting with co-ownership of energy storage facilities - A case study of the Netherlands

This article discusses how shared ownership of energy storage facilities between grid managers (Distribution System Operators and Transmission System Operators) and third-party market participants may help to resolve congestion issues. The article uses the Netherlands as a case study on how congestion issues may lead to a stalemate: increasing energy storage capacity may help to resolve grid congestion but may cause additional congestion if used to trade in profitable markets. As a result, it is not installed, or installation is delayed until the grid is fortified. The article discusses how shared ownership may lead to the co-optimization of investment decisions by different stakeholders and of the operation of the storage facility. It also discusses how the exemption to unbundling obligations under art. 36 (2) of Directive 2019/944 can be used to allow for these ownership constructions. The article argues that national regulatory authorities can use regulatory experimentation to find the desirable conditions and uses of the exemption and to stimulate regulatory learning. The use of experimentation can help to resolve congestion issues in certain localities in the short term and help to develop principles for regulation of the future energy system in the long-term.

Performance evaluation of a moonbase energy system using in-situ resources to enhance working time

The solar energy resources of the Moon are far more prosperous than those of the Earth. Therefore, energy systems driven by solar energy are more suitable for application on the Moon. Ensuring the safe operation of the energy system under solar energy (or other variable-temperature heat sources) has become a focal point issue that constrains the construction of the moonbase. In this paper, based on the closed Brayton cycle-organic Rankine cycle (CBC-ORC) system and considering the dryness of the outlet of the evaporator of ORC, a scheme is proposed to raise the temperature of the heat source by using a heat storage heat exchanger (HSHEX). Thus increase the dryness of the organic working fluid side of the evaporator. With the introduction of HSHEX, ORC can work for up to 13.3 days at a mass flow rate of 0.6 kg/s, nearly one time more than the case without HSHEX. The maximum total system thermal efficiency can reach 28.74 %. By stopping the CBC and adjusting the ORC mass flow rate, the average power generation gets 5.69 kW, doubling the working time during the lunar nighttime. This paper aims to solve the problem of improving the working time of the moonbase energy system and provide theoretical guidance for constructing the future lunar base energy system.

Attractiveness of Photovoltaic Prosumerism in the European Electricity Market

The current energy crisis calls for a rapid transition to renewables. Solar photovoltaics (PV) is the key component of the future energy system and a majority of PV systems are installed on rooftops in Europe. This article studies the business case of prosumers, i.e., consumers who produce part or all of their electricity with PV. The levelized cost of PV electricity is compared with the average value of PV electricity for the prosumers in residential, commercial, and industrial installations in Finland, Germany, France, Italy, and Spain with different self‐consumption (SC) and weighted average cost of capital rates. Prosumer business cases are positive in every studied market segment and country, especially for industrial PV systems with 100% SC where a payback time of less than 4 years can be achieved. The sensitivity of payback time on key input parameters is also studied. Reasonable cost of capital and adequate SC of PV generation remain the key elements for attractive prosumerism.

Hydrogen storage capacity of salt caverns and deep aquifers versus demand for hydrogen storage: A case study of Poland

Geological structures in deep aquifers and salt caverns can play an important role in large-scale hydrogen storage. However, more work needs to be done to address the hydrogen storage demand for zero-emission energy systems. Thus the aim of the article is to present the demand for hydrogen storage expressed in the number of salt caverns in bedded rock salt deposits and salt domes or the number of structures in deep aquifers. The analysis considers minimum and maximum hydrogen demand cases depending on future energy system configurations in 2050. The method used included the estimation of the storage capacity of salt caverns in bedded rock salt deposits and salt domes and selected structures in deep aquifers. An estimation showed a large hydrogen storage potential of geological structures. In the case of analyzed bedded rock salt deposits and salt domes, the average storage capacity per cavern is 0.05–0.09 TWhH2 and 0.06–0.20 TWhH2, respectively. Hydrogen storage capacity in analyzed deep aquifers ranges from 0.016 to 4.46 TWhH2. These values indicate that in the case of the upper bound for storage demand, there is a need for the 62 to 514 caverns, depending on considered bedded rock salt deposits and salt domes or the 9 largest analyzed structures in deep aquifers. The results obtained are relevant to the discussion on the global hydrogen economy, and the methodology can be used for similar considerations in other countries.

Beyond dollars and cents: why socio-political factors matter in energy system modeling

Traditional energy system modeling (ESM) has predominantly focused on techno-economic factors such as costs and efficiency. However, this narrow perspective fails to capture the intricate interplay between energy systems and socio-political dynamics that significantly influence their real-world impact. This piece underlines the importance of incorporating socio-political factors into ESM and highlights the need for a more comprehensive approach. We identify several reasons why socio-political factors are often overlooked in ESM, including technical bias, complexity, data standardization challenges, time and resource constraints, and societal biases. These factors must be addressed to improve the relevancy of ESM, reduce social injustice, and promote innovation in the design of future energy systems. Incorporating socio-political factors into ESM offers several benefits. To achieve these benefits, the paper suggests a shift towards a more comprehensive and value-driven approach and offers several options for improving ESM including: (I) recognizing that socio-political factors are just as important as techno-economic factors (II) improving the structure of the modeling process (III) developing new and innovative metrics for socio-political factors (IV) linking different types of models (V) emphasizing the need for interdisciplinarity in ESM. By prioritizing the aspects of the energy system that concern people to the same degree we prioritize cost, we can derive value-driven insights to assist in creating a more sustainable future for all.

Chemical physics of electrochemical energy materials.

Probing the chemistry and materials science of electrochemical energy materials is a central topic in both chemical physics and energy chemistry due to the increasingly important role of energy devices in the current and future energy system and industry. Especially, understanding the chemical physics of electrochemical energy materials is the key to enhance the performance of energy storage and conversion devices such as batteries, fuel cells, electrolyzers, and supercapacitors. This special topic focuses on the fundamental understanding of electrochemical energy applications, including electrochemistry fundamentals, structural dynamics and degradation mechanism of materials, optimization strategies for improving electrochemical performance of energy devices, and emerging simulation and characterization methods applied to advanced energy materials.

Fault Diagnosis for PV Modules Based on AlexNet and Symmetrized Dot Pattern

Faults in solar photovoltaic (PV) modules often result from component damage, leading to voltage fluctuations and decreased stability in the power system. In this study, the original voltage signals of different PV modules show little variation. Therefore, a solution that combines symmetrized dot pattern (SDP) and AlexNet for fault detection in PV modules was proposed. This solution investigates three common faults: poor welding, cracking, and bypass diode failure, which can be applied to fault-free modules. First, a high-frequency signal was input into the PV module, and the raw signal was captured using an NI PXI-5105 high-speed data acquisition card. Next, we used SDP to process the signal and create images with specific snowflake-like features. These images were used as a basis for fault diagnosis. Finally, deep-learning algorithms were used to perform status detection on the PV module. This research also used 3200 training samples and 800 test samples (200 for each type) to evaluate a new method for diagnosing faults in PV modules. The results show that the accuracy of the new method reached 99.8%, surpassing traditional convolutional neural networks (CNN) and extension neural networks (ENN), whose accuracies were 99.5% and 91.75%, respectively. Furthermore, this study compares the proposed method with more traditional numerical fault diagnosis methods. SDP effectively extracts fault signals and presents them as images. With AlexNet used for fault identification, the method excels in accuracy, training time, and testing time, thereby enhancing the stability and reliability of future energy systems.

Electricity demand forecasting with hybrid classical statistical and machine learning algorithms: Case study of Ukraine

This article presents a novel hybrid approach using classic statistics and machine learning to forecast the national demand of electricity. As investment and operation of future energy systems require long-term electricity demand forecasts with hourly resolution, our mathematical model fills a gap in energy forecasting. The proposed methodology was constructed using hourly data from Ukraine’s electricity consumption ranging from 2013 to 2020. To this end, we analysed the underlying structure of the hourly, daily and yearly time series of electricity consumption. The long-term yearly trend is evaluated using macroeconomic regression analysis. The mid-term model integrates temperature and calendar regressors to describe the underlying structure, and combines ARIMA and LSTM “black-box” pattern-based approaches to describe the error term. The short-term model captures the hourly seasonality through calendar regressors and multiple ARMA models for the residual. Results show that the best forecasting model is composed by combining multiple regression models and a LSTM hybrid model for residual prediction. Our hybrid model is very effective at forecasting long-term electricity consumption on an hourly resolution. In two years of out-of-sample forecasts with 17520 timesteps, it is shown to be within 96.83% accuracy.

Economic assessment and optimization of low-carbon biomass-based power, methane, and methanol production

Fuel synthesis through CO2 hydrogenation is receiving much attention to decarbonizing the transport sector of future energy systems. In this study, an integrated system is proposed and investigated from a thermo-economic point of view to produce power and synthetic methane and methanol. The proposed system includes an externally fired gas turbine, Rankine cycle, organic Rankine cycle, proton exchange membrane electrolyzer, molten carbonate fuel cell and methane and methanol synthesis units. CO2 hydrogenated under three different scenarios to produce methane-only, methanol-only and dual-production assuming various operating loads of electrolyzer. The influence of the key parameters on the system performance is assessed via response surface method and finally, the system performance is optimized. Under the base conditions, overall exergy efficiency, levelized cost of electricity, methanol and methane is estimated to be 36.8 %, 37.6, 92.8 and 79.4 $/MWh, respectively. Under the optimized conditions for the methane-only scenario, the overall exergy efficiency, levelized cost of electricity and methane is found to be 34.8 %, 36.7 $/MWh and 77.3 $/MWh, respectively.

Digitalisation without detriment: A research agenda for digital inclusion in the future energy system

Digitalisation without detriment: A research agenda for digital inclusion in the future energy system

Achievable load shifting potentials for the European residential sector from 2022–2050

This paper develops quantitative predictions for residential electricity demand and the potential for load shifting for Europe at a fine spatial scale for years 2022–2050. To date only theoretical and spatially coarse measurements of this potential exist for a subset of technologies used in the residential sector. As the EU moves towards an ‘Energy Union’, it will be increasingly necessary to consider the whole integrated energy system across the EU and thereby databases with large spatial coverage are needed. To fill this need, we generate hourly load profiles for the residential sector for key electricity consuming devices that take into account the most recent empirical studies of usage patterns, and of the cost and willingness of households to participate in load shifting programs. Additionally, we extend the list of investigated technologies by the important classes of electric mobility and heat pumps for electric space heating. Predictions and insights provided in our article serve multiple use cases, i. they can be used in energy system models to assess the value of load shifting for the future energy system including system costs, ii. they enable infrastructure planners and grid operators to calibrate their expectations of the future role of load shifting in the electricity systems and iii. enable policy makers and to include load shifting in their considerations of future market designs.

Experimental Validation for Distributed Control of Energy Hubs

As future energy systems become more decentralised due to the integration of renewable energy resources and storage technologies, several autonomous energy management and peer-to-peer trading mechanisms have been recently proposed for the operation of energy hub networks based on optimization and game theory. However, most of these strategies have been tested either only in simulated environments or small prosumer units as opposed to larger energy hubs. This simulation reality gap has hindered large-scale implementation and practical application of these method. In this paper, we aim to experimentally validate the performance of a novel multi-horizon distributed model predictive controller for an energy hub network by implementing the controller on a complete network of hubs comprising of a real energy hub inter-faced with multiple virtual hubs. The experiments are done using two different network topologies and the controller shows promising results in both setups.

Optihood – a multi-objective analysis and optimization framework for building energy systems at neighborhood scale

Strategic planning of future energy systems in a district is essential to fully exploit the benefits from sector coupling. In particular, new solutions may arise when a group of buildings is considered rather than individual buildings. Therefore, in order to identify optimal production and storage technologies within a district, new tools are needed. In this paper we present the open-source software framework optihood, which allows for multi-objective optimization and analysis of energy systems for neighborhoods. The tool assists researchers and, in a future stage, energy planners in the design of energy systems as well as in optimizing their operation strategy. After introducing the tool, its applicability is demonstrated with a case study, wherein we investigated the supply of a small neighborhood of four residential buildings with space heat, domestic hot water and electricity demands. The optimizer was allowed to consider heat pumps (geothermal/air-source), PV, batteries and hot water storage tanks as available technologies. We show comparisons between optimal solutions in terms of total annualized cost for the buildings considered (a) together as a group and (b) individually.

Carbon trading-based layered operation optimization of the electric–thermal multi-energy-flow coupling system with photothermal power stations

With the increasing development of low-carbon economy, the coupling degree of electric thermal gas system is deepening day by day. The operation mode of traditional energy supply system using electric heating separation mode and hierarchical dispatching of transmission and distribution network has been difficult to mine the whole network resources and realize the global optimal operation strategy. In order to increase the consumption of new energy and solve the multi-energy current coupling system, this paper puts forward a layered optimization operation strategy for the electric-thermal multi-energy current coupling system with Concentrated solar power (CSP) plant and carbon trading mechanism. The upper layer is the solution layer of multi-energy coupled flow system. In order to solve the matrix values of complex multi-energy coupled flow system, Newton's method, improved Newton’s method and improved second-order cone collaborative solution methods are proposed. The lower layer is the multi-energy flow optimization layer. According to the system solution values obtained from the upper layer, the lower layer optimization aims at economic minimization of the total user cost. The carbon trading mechanism model is introduced to optimize the time sequence output of the electric thermal unit under different scenarios, and the mixed integer linear programming method is adopted. Finally, the validity is verified by a simulation example. The results show that this method can optimize the operation of the system, improve the accuracy and rapidity of the system, and “carbon trading and CSP power station” method can better constrain the carbon emission of the multi-energy flow coupling system, reduce the energy pressure of the device, and improve the economy of the total cost of the user.If this method is adopted, it can be used for reference in the future energy management and system decision of multi-energy flow coupling system.

Who will keep the lights on? Expertise and inclusion in cyber security visions of future energy systems

Increasing internet connectivity in smart energy systems poses serious cyber security concerns. Using a lens of “sociotechnical imaginaries”, we explored how experts envision the future(s) of cyber security governance in the energy sector. The three imaginaries identified present cyber security issues as a matter of design, as a support function, and as public trust. We argue that while each vision prioritises a different set of actions, none of them adequately considers the interplay between inclusivity and expertise. By exploring what each of these potential futures enables, hinders, or assumes, as well as how they compete or complement each other, we derive a number of recommendations to ensure cyber security expertise becomes more inclusive, democratic and participatory. The paper contributes to energy social science debates by furthering the understanding of how energy experts conceptualise future computing systems for security and sustainability.

In-situ controllable electrodeposition of NiSx nanostructures coupled with polypyrrole for enhanced hydrogen evolution reaction

The development of effective and inexpensive electrocatalysts for hydrogen evolution reaction (HER) plays a key role in future energy system. Herein, we report a series of NiSx composited with polypyrrole (PPy) hollow nanospheres on carbon papers (CPs) to promote the HER performance. The crystal phase and lattice configuration of the in-situ grown NiSx can be tuned through unipolar pulse electrodeposition. The PPy with high conductivity is conducive to prevent the NiSx from collapse and improve the stability of the HER. As a result, the optimized Ni3S2/PPy/CP electrode manifests a low overpotential of 149 mV (vs. RHE) at 10 mA cm−2, an exceptional long-term stability over 100 h, and a large electrochemically active surface area of 1173.75 cm2. Furthermore, it is found that the exposure of (110), (122) and (300) planes of Ni3S2 facilitates to increase the number of active sites. The precise lattice regulation contributes to achieve high HER performance.

The role of hydrogen in the energy transition

The role of hydrogen in the energy transition Professor Sara Walker, Professor of Energy at Newcastle University, is Director of the Hub on Hydrogen Integration for Accelerated Energy Transitions HI-ACT, and here, she explores the role of hydrogen in the energy transition. Across the globe, we continue to see the impacts of climate change. As I write, devastating fires in Hawaii are the most recent example, but there are many. Globally, energy use is estimated to contribute more than three-quarters of greenhouse gas emissions. So, mitigation of climate change often focuses on energy efficiency, transition away from fossil fuels to renewables, and electrification of demand. At HI-ACT, our vision is to ensure that hydrogen and hydrogen-based alternative liquid fuels are appropriately integrated into a future equitable energy system through holistic multi-disciplinary research.

A methodological framework for geospatial modelling of hydrogen demand in cities

Urban energy system planning is vital for cities shifting towards a more sustainable and integrated energy system. Hydrogen is considered one of the most promising solutions in future energy systems. Previous work on hydrogen energy systems predominantly analysed hydrogen models on a national level or only parts of the mobility sector. This indicates a research gap for geospatial models that include multiple sectors in which hydrogen can be used. These models can be used to support decision-making processes around the hydrogen economy in cities. This study presents a holistic model addressing the geospatial modelling of hydrogen demand in urban areas. It proposes a method that integrates a variety of open source data, including geodata, earth observation data and energy data to estimate hydrogen demand top down for the industrial feedstock (steel, ammonia, organic chemistry), process heating, and mobility (buses, trucks, trains, airplanes, ships) sectors. The proposed method can also be extended to different sectors. The method is validated by modelling the hydrogen demand in all German cities and benchmarking it with national studies. This study’s results are within the same range as the results of national studies. For this paper, the method is applied for two case studies in Freiburg im Breisgau and Frankfurt am Main. Applying this method in urban areas shows potential hydrogen demand hotspots in these areas. The model’s results help policymakers and industry stakeholders make informed decisions about the development of hydrogen infrastructure and facilitate the adoption of hydrogen as a low-carbon energy carrier. Future research could explore the temporal aspects of hydrogen demand and the spatial influence of hydrogen demand on future hydrogen production facilities such as electrolysers.

Experts, stakeholders, technocracy, and technoeconomic input into energy scenarios

This paper confronts the broad question of the nature and quality of the contributions of experts, stakeholders, and the wider public to the development of detailed techno economical inputs used in scenario analyses used for discussions and decisions on the green energy transition and science, technology and innovation (STI) policies in general. The study focuses on stakeholder inclusion in developing the Danish Energy Agency's technology catalogues. The technology catalogues forecasts technoeconomic data up to 2050. The study reviews some well-recognised issues related to the inclusion of experts and stakeholders. The study contributes three new insights. First, a better understanding is developed of how expert and stakeholder inclusion in developing front-end inputs for energy models and scenarios aligns expectations and builds a shared understanding of detailed technoeconomic data. This shared understanding establishes a level playing field for wider public debate on visions for the future energy system. Second, a pragmatic approach is demonstrated for stakeholder inclusion in contexts – such as developing technology catalogues – with limited resources and only a few actors available for consultation. Third, the paper presents the argument that the concept of technocracy can bring useful insights for analysing expert and stakeholder inclusion in longterm energy planning.