Publications
541 results found
Huang W, Zhang X, Li K, et al., 2022, Resilience Oriented Planning of Urban Multi-Energy Systems With Generalized Energy Storage Sources, IEEE TRANSACTIONS ON POWER SYSTEMS, Vol: 37, Pages: 2906-2918, ISSN: 0885-8950
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- Citations: 25
Olympios AV, Aunedi M, Mersch M, et al., 2022, Delivering net-zero carbon heat: technoeconomic and whole-system comparisons of domestic electricity- and hydrogen-driven technologies in the UK, Energy Conversion and Management, Vol: 262, ISSN: 0196-8904
Proposed sustainable transition pathways for moving away from natural gas in domestic heating focus on two main energy vectors: electricity and hydrogen. Electrification would be implemented by using vapour-compression heat pumps, which are currently experiencing market growth in many countries. On the other hand, hydrogen could substitute natural gas in boilers or be used in thermally–driven absorption heat pumps. In this paper, a consistent thermodynamic and economic methodology is developed to assess the competitiveness of these options. The three technologies, along with the option of district heating, are for the first time compared for different weather/ambient conditions and fuel-price scenarios, first from a homeowner’s and then from a whole-energy system perspective. For the former, two-dimensional decision maps are generated to identify the most cost-effective technologies for different combinations of fuel prices. It is shown that, in the UK, hydrogen technologies are economically favourable if hydrogen is supplied to domestic end-users at a price below half of the electricity price. Otherwise, electrification and the use of conventional electric heat pumps will be preferred. From a whole-energy system perspective, the total system cost per household (which accounts for upstream generation and storage, as well as technology investment, installation and maintenance) associated with electric heat pumps varies between 790 and 880 £/year for different scenarios, making it the least-cost decarbonisation pathway. If hydrogen is produced by electrolysis, the total system cost associated with hydrogen technologies is notably higher, varying between 1410 and 1880 £/year. However, this total system cost drops to 1150 £/year with hydrogen produced cost-effectively by methane reforming and carbon capture and storage, thus reducing the gap between electricity- and hydrogen-driven technologies.
He W, Zheng Y, You S, et al., 2022, Case study on the benefits and risks of green hydrogen production co-location at offshore wind farms, ISSN: 1742-6588
Abstract Advances in large-scale green hydrogen production (LGHP) create commercial opportunities for enhancing rapid offshore wind farm (OWF) development. This study investigates whether LGHP co-location at OWF sites improves those OWF's economic outlooks under potential electrical grid capacity bottlenecks towards 2050. Eight cases have been studied using measured annual OWF power production series and cost estimation integrated with offshore engineering experience: i) two base cases: 2 GW OWFs with HVAC and HVDC transmission infrastructure showing that the levelized cost of electricity (LCOE) increases, and ii) six LGHP co-location cases demonstrating that the calculated levelized cost of hydrogen (LCOH) reduces when the LGHP capacity increases from 20% to 50%, and 100% of 2 GW. Furthermore, three economic improvement factors studied are: i) utilizing existing gas pipelines reducing LCOH by 7.5%, ii) hydrogen for offshore customers changing "no-go"projects to "go", and iii) scaling-up from 2 to 4 GW reduced the LCOH by 17%. This study shows that LGHP co-location is effective at maintaining OWF full production, but has higher risks including i) LGHP co-location safety at OWFs, ii) high costs to cover more operational conditions and iii) running LGHP operations using high, fluctuating OWF power. Further R&D of LGHP co-location are recommended.
Yuan Q, Ye Y, Tang Y, et al., 2022, A novel deep-learning based surrogate modeling of stochastic electric vehicle traffic user equilibrium in low-carbon electricity-transportation nexus, APPLIED ENERGY, Vol: 315, ISSN: 0306-2619
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- Citations: 4
Zhang X, Ameli H, Dong Z, et al., 2022, Values of latent heat and thermochemical energy storage technologies in low-carbon energy systems: whole system approach, Journal of Energy Storage, Vol: 50, ISSN: 2352-152X
Thermal energy storage (TES) is widely expected to play an important role in facilitating the decarbonization of the future energy system. Although significant work has been done in assessing the values of traditional sensible TES, less is known about the role, impact and value of emerging advanced TES at the system level. This is particularly the case of latent heat thermal energy storage (LHTES) and thermochemical energy storage (TCS). In this context, this paper is dedicated to evaluating the techno-economic values for the whole UK energy system of LHTES and TCS technology using an integrated whole energy system model. First, the key concepts of the whole system modelling framework are introduced. Unique to this work is that the economic benefits delivered by LHTES and TCS to different levels of theUK energy system infrastructure and various energy sectors through the deployment of TES are explicitly analyzed, which comprehensively demonstrates the values of selected TES technologies from the whole system perspective. A series of sensitivity studies are implemented to analyze the advantages and disadvantages of LHTES and TCS underdifferent conditions. The simulation results indicate that TES can benefit different sectors of the whole energy system and drive significant cost savings, but the whole system values of TES is closely dependent on the decarbonization requirement. Although LHTES is characterized by relatively low capital costs, when TES penetration is limited and carbon target is tight, the advantage of TCS is outstanding due to its high energy density.
Bellizio F, Bugaje A-ABL, Cremer J, et al., 2022, Verifying Machine Learning conclusions for securing Low Inertia systems, SUSTAINABLE ENERGY GRIDS & NETWORKS, Vol: 30, ISSN: 2352-4677
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- Citations: 4
Qiu D, Wang Y, Sun M, et al., 2022, Multi-service provision for electric vehicles in power-transportation networks towards a low-carbon transition: A hierarchical and hybrid multi-agent reinforcement learning approach, APPLIED ENERGY, Vol: 313, ISSN: 0306-2619
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- Citations: 9
Giannelos S, Borozan S, Strbac G, 2022, A Backwards Induction Framework for Quantifying the Option Value of Smart Charging of Electric Vehicles and the Risk of Stranded Assets under Uncertainty, ENERGIES, Vol: 15
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- Citations: 8
Al Kindi A, Aunedi M, Pantaleo A, et al., 2022, Thermo-economic assessment of flexible nuclear power plants in future low-carbon electricity systems: Role of thermal energy storage, Energy Conversion and Management, Vol: 258, ISSN: 0196-8904
The increasing penetration of intermittent renewable power will require additional flexibility from conventional plants, in order to follow the fluctuating renewable output while guaranteeing security of energy supply. In this context, coupling nuclear reactors with thermal energy storage could ensure a more continuous and efficient operation of nuclear power plants, while at other times allowing their operation to become more flexible and cost-effective. This study proposes options for upgrading a 1610-MWel nuclear power plant with the addition of a thermal energy storage system and secondary power generators. The total whole-system benefits of operating the proposed configuration are quantified for several scenarios in the context of the UK’s national electricity system using a whole-system model that minimises the total system costs. The proposed configuration allows the plant to generate up to 2130 MWel during peak load, representing an increase of 32% in nominal rated power. This 520 MWel of additional power is generated by secondary steam Rankine cycle systems (i.e., with optimised cycle thermal efficiencies of 24% and 30%) and by utilising thermal energy storage tanks with a total heat storage capacity of 1950 MWhth. Replacing conventional with flexible nuclear power plants is found to generate whole-system cost savings between £24.3m/yr and £88.9m/yr, with the highest benefit achieved when stored heat is fully discharged in 0.5 h. At an estimated cost of added flexibility of £42.7m/yr, the proposed flexibility upgrades to such nuclear power plants appears to be economically justified with net system benefits ranging from £4.0m/yr to £31.6m/yr for the examined low-carbon scenarios, provided that the number of flexible nuclear plants in the system is small. This suggests that the value of this technology is system dependent, and that system characteristics should be adequately considered when evaluating the benefits of diffe
Bellizio F, Xu W, Qiu D, et al., 2022, Transition to Digitalized Paradigms for Security Control and Decentralized Electricity Market, PROCEEDINGS OF THE IEEE, ISSN: 0018-9219
Davari MM, Ameli H, Ameli MT, et al., 2022, Impact of local emergency demand response programs on the operation of electricity and gas systems, Energies, Vol: 15, ISSN: 1996-1073
With increasing attention to climate change, the penetration level of renewable energy sources (RES) in the electricity network is increasing. Due to the intermittency of RES, gas-fired power plants could play a significant role in backing up the RES in order to maintain the supply–demand balance. As a result, the interaction between gas and power networks are significantly increasing. On the other hand, due to the increase in peak demand (e.g., electrification of heat), network operators are willing to execute demand response programs (DRPs) to improve congestion management and reduce costs. In this context, modeling and optimal implementation of DRPs in proportion to the demand is one of the main issues for gas and power network operators. In this paper, an emergency demand response program (EDRP) is implemented locally to reduce the congestion of transmission lines and gas pipelines more efficiently. Additionally, the effects of optimal implementation of local emergency demand response program (LEDRP) in gas and power networks using linear and non-linear economic models (power, exponential and logarithmic) for EDRP in terms of cost and line congestion and risk of unserved demand are investigated. The most reliable demand response model is the approach that has the least difference between the estimated demand and the actual demand. Furthermore, the role of the LEDRP in the case of hydrogen injection instead of natural gas in the gas infrastructure is investigated. The optimal incentives for each bus or node are determined based on the power transfer distribution factor, gas transfer distribution factor, available electricity or gas transmission capability, and combination of unit commitment with the LEDRP in the integrated operation of these networks. According to the results, implementing the LEDRP in gas and power networks reduces the total operation cost up to 11% and could facilitate hydrogen injection to the network. The proposed hybrid model is implem
Wang Y, Qiu D, Strbac G, 2022, Multi-agent deep reinforcement learning for resilience-driven routing and scheduling of mobile energy storage systems, APPLIED ENERGY, Vol: 310, ISSN: 0306-2619
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- Citations: 21
Ye Y, Yuan Q, Tang Y, et al., 2022, Decentralized Coordination Parameters Optimization in Microgrids Mitigating Demand Response Synchronization Effect of Flexible Loads, Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, Vol: 42, Pages: 1748-1759, ISSN: 0258-8013
Despite its scalability and privacy advantages over centralized coordination schemes, decentralized price-based coordination in microgrids suffers from the demand response concentration effect, transferring flexible loads to low-price periods and yielding new demand peak, which hampers the efficient and secure operation of the system. Previous works have introduced auxiliary coordination parameters beyond electricity price to mitigate this effect. However, uniform values of these coordination parameters have been applied to all flexible loads, despite the effects of network constraints. To this end, this paper proposed an auxiliary parameters optimization for decentralized coordination in microgrids, applying optimal value for flexible loads in different nodes to mitigate demand response synchronization effect and minimize the total operational cost of the microgrid. Firstly, the decentralized coordination optimization model of microgrid and the demand response model of flexible loads, i.e. electric vehicles and smart appliances were established. Then a DRL-based approach to select the optimal values of auxiliary parameters was proposed, posing the parameter optimization problem in multi- dimensional continuous state and action spaces. Finally, simulation results demonstrated the effectiveness of the proposed optimization method.
Ademovic Tahirovic A, Angeli D, Strbac G, 2022, Heterogeneous network flow and Petri nets characterize multilayer complex networks, Scientific Reports, Vol: 12, ISSN: 2045-2322
Interacting subsystems are commonly described by networks, where multimodal behaviour found in most natural or engineered systems found recent extension in form of multilayer networks. Since multimodal interaction is often not dictated by network topology alone and may manifest in form of cross-layer information exchange, multilayer network flow becomes of relevant further interest. Rationale can be found in most interacting subsystems, where a form of multimodal flow across layers can be observed in e.g., chemical processes, energy networks, logistics, finance, or any other form of conversion process relying on the laws of conservation. To this end, the formal notion of heterogeneous network flow is proposed, as a multilayer flow function aligned with the theory of network flow. Furthermore, dynamic equivalence is established with the framework of Petri nets, as the baseline model of concurrent event systems. Application of the resulting multilayer Laplacian flow and flow centrality is presented, along with graph learning based inference of multilayer relationships over multimodal data. On synthetic data the proposed framework demonstrates benefits of multimodal flow derivation in critical component identification. It also displays applicability in relationship inference (learning based function approximation) on multimodal time series. On real-world data the proposed framework provides, among others, multimodal flow interpretation of U.S. economic activity, uncovering underlying empirical steady state probability distribution, as well as inherent network (economic) robustness.
Hua W, Jiang J, Sun H, et al., 2022, Consumer-centric decarbonization framework using Stackelberg game and Blockchain, APPLIED ENERGY, Vol: 309, ISSN: 0306-2619
Qiu D, Dong Z, Zhang X, et al., 2022, Safe reinforcement learning for real-time automatic control in a smart energy-hub, APPLIED ENERGY, Vol: 309, ISSN: 0306-2619
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- Citations: 27
Borozan S, Giannelos S, Strbac G, 2022, Strategic network expansion planning with electric vehicle smart charging concepts as investment options, ADVANCES IN APPLIED ENERGY, Vol: 5, ISSN: 2666-7924
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- Citations: 22
Ye Y, Wang H, Tang Y, et al., 2022, Real-time Autonomous Optimal Energy Management Strategy for Residents Based on Deep Reinforcement Learning, Dianli Xitong Zidonghua/Automation of Electric Power Systems, Vol: 46, Pages: 110-119, ISSN: 1000-1026
Alongside the wide proliferation of distributed energy resources at the residential sector, how to meet the needs of real-time autonomous energy management while considering the heterogeneous operating characteristics of these resources so as to maximize the utility for residential end-users deserves significant research attention. In this area, conventional model-based optimization methods are generally burdened with inaccurate system modeling and inability to efficiently deal with uncertainties stemmed from multiple sources. In order to address these challenges, this paper proposes a model-free method based on deep reinforcement learning to achieve real-time autonomous energy management optimization. First, the user's resources are classified into different categories, their operating characteristics are then described using a unified 3-element tuple, and the associated energy management actions are also identified. Next, the long short-term memory neural network is employed to extract the future trends of multi-source sequential data from the environment states. Then, based on the proximal policy optimization algorithm,it enables efficient learning of the optimal energy management policies in the multi-dimensional continuous-discrete mixed action space, which can adaptively adjust to system uncertainties towards the user's electricity cost minimization objective. Finally, the effectiveness of the proposed method is verified by benchmarking its performance against several existing methods through case studies on an actual scenario.
Pang Q, De Paola A, Strbac G, et al., 2022, The impact of variable wind and demand levels on the flexible operation of interconnectors in Great Britain
This paper analyses the potential benefits for flexible operation of interconnectors in cross-border power systems. The underlying modelling approach enables the simultaneous cross-border exchange of power and inertia-dependent frequency response services through the interconnector. Two main operational paradigms are adopted. The first considers the interconnectors as centrally-operated assets; the latter envisages them as profit-seeking private entities. Furthermore, the proposed work adopts a sampling-based method to assess the impact of wind and demand variability on the short-term operation of the interconnectors, evaluating the sensitivities of relevant operational and economical metrics with respect to wind availability and demand levels. A comprehensive set of case studies is developed considering the Great Britain (GB)-France interconnected systems. The studies show significant value for interconnectors under a wide range of system conditions.
Amiri MM, Ameli H, Ameli MT, et al., 2022, Investigating the effective methods in improving the resilience of electricity and gas systems, Whole Energy Systems: Bridging the Gap via Vector-Coupling Technologies, Publisher: Springer, Cham, ISBN: 978-3-030-87652-4
Consumption of natural gas and the share of renewable energy in meeting global energy demand have grown significantly. Consequently, gas and electrical grids are becoming more integrated with fast responding gas-fired power stations, providing the primary backup source for renewable electricity in maintaining supply-demand balance. For an engineering system (e.g., gas and electricity systems infrastructure), many definitions of similar essence have been proposed, focusing on the ability to deal with disruptions. Taking the importance of actions prior, during, and afterward of an adverse event in mind, resilience is defined as a system’s ability to anticipate, resist, absorb, respond to, adapt to, and recover from a disturbance. Hence, in this chapter the importance of resiliency in the electricity and gas network’s cooperation is demonstrated, and different strategies and methods to increase resiliency are investigated.
Wang Y, Rousis AO, Strbac G, 2022, Resilience-driven optimal sizing and pre-positioning of mobile energy storage systems in decentralized networked microgrids, APPLIED ENERGY, Vol: 305, ISSN: 0306-2619
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- Citations: 30
Liu P, Wu Z, Gu W, et al., 2022, A Non-Convex and Non-Iterative Approach for Fast Vulnerability Analysis of Smart Grids
The computational burden of vulnerability analysis of power networks depends heavily on the management of non-convexities and N-k contingencies. In this paper, a novel spatial branch-and-cut is proposed for the fast screening of vulnerable components. To address the non-convexities in the form of conic equalities, a conic-specific spatial branching strategy is designed to prune the solutions which violate non-convex constraints. To accelerate the process of contingency screening, the modeling of post-contingency load restoration for each contingency is unified and explored through combinatorial cuts. The core idea of the proposed assessment approach is to manage both non-convexities and contingencies in a single spatial branch-and-cut search tree through callback functions, so that the screening for all possible contingencies can be conducted only once. The performance of the vulnerability analysis approach is evaluated on two testing systems. Numerical results show the effectiveness and efficiency of the proposed method.
Aunedi M, Strbac G, 2022, System Benefits of Residential Heat Storage for Electrified Heating Sector in the United Kingdom
Electrification of heat is a key element of the UK's decarbonisation strategy, however it risks significantly increasing network peak demand. Thermal energy storage (TES) provides an opportunity to introduce flexibility into the system and allow load to be shifted to off-peak periods, delivering a range of benefits in the decarbonised electricity system. This paper quantifies system-wide benefits of installing heat batteries alongside residential heat pump systems, using a whole-electricity system model. System value for a high uptake of TES is found to be between £1.5-1.7bn/in 2035 and £1.1-2.3bn/yr in 2050. Most of the system value is derived from savings in generation investment cost and reduced distribution network cost. Customer-level benefits in the long term are estimated at between £200 and £300 per customer annually, with highest values observed at low TES uptake levels (10%).
Bellizio F, Cremer JL, Strbac G, 2022, Machine-learned security assessment for changing system topologies, INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, Vol: 134, ISSN: 0142-0615
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- Citations: 6
Moreno R, Trakas DN, Jamieson M, et al., 2022, Microgrids Against Wildfires: Distributed Energy Resources Enhance System Resilience, IEEE POWER & ENERGY MAGAZINE, Vol: 20, Pages: 78-89, ISSN: 1540-7977
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- Citations: 7
Wang Y, Qiu D, Strbac G, 2022, Multi-agent reinforcement learning for electric vehicles joint routing and scheduling strategies, IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), Publisher: IEEE, Pages: 3044-3049, ISSN: 2153-0009
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- Citations: 1
Falugi P, O’Dwyer E, Zagorowska MA, et al., 2022, MPC and optimal design of residential buildings with seasonal storage: a case study, Active Building Energy Systems, Editors: Doyle, Publisher: Springer International Publishing, Pages: 129-160, ISBN: 9783030797416
Residential buildings account for about a quarter of the global energy use. As such, residential buildings can play a vital role in achieving net-zero carbon emissions through efficient use of energy and balance of intermittent renewable generation. This chapter presents a co-design framework for simultaneous optimisation of the design and operation of residential buildings using Model Predictive Control (MPC). The adopted optimality criterion maximises cost savings under time-varying electricity prices. By formulating the co-design problem using model predictive control, we then show a way to exploit the use of seasonal storage elements operating on a yearly timescale. A case study illustrates the potential of co-design in enhancing flexibility and self-sufficiency of a system operating on multiple timescales. In particular, numerical results from a low-fidelity model report approximately doubled bill savings and carbon emission reduction compared to the a priori sizing approach.
Borozan S, Giannelos S, Aunedi M, et al., 2022, Option Value of EV Smart Charging Concepts in Transmission Expansion Planning under Uncertainty, 21st IEEE Mediterranean Electrotechnical Conference (IEEE MELECON), Publisher: IEEE, Pages: 63-68, ISSN: 2158-8481
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- Citations: 3
Ademovic Tahirovic A, Angeli D, Strbac G, 2021, A complex network approach to power system vulnerability analysis based on rebalance based flow centrality, 2021 IEEE PES General Meeting, Publisher: IEEE
The study of networks is an extensively investigated field of research, with networks and network structure often encoding relationships describing certain systems or processes. Critical infrastructure is understood as being a structure whose failure or damage has considerable impact on safety, security and wellbeing of society, with power systems considered a classic example. The work presented in this paper builds on the long-lasting foundations of network and complex network theory, proposing an extension in form of rebalance based flow centrality for structural vulnerability assessment and critical component identification in adaptive network topologies. The proposed measure is applied to power system vulnerability analysis, with performance demonstrated on the IEEE 30-, 57-and 118-bus test system, out performing relevant methods from the state-of-the-art. The proposed framework is deterministic (guaranteed), analytically obtained (interpretable) and generalizes well with changing network parameters, providing a complementary tool to power system vulnerability analysis and planning.
Moreira A, Pozo D, Street A, et al., 2021, Climate-aware generation and transmission expansion planning: A three-stage robust optimization approach, EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, Vol: 295, Pages: 1099-1118, ISSN: 0377-2217
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- Citations: 13
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