Publications
40 results found
Few S, Djapic P, Strbac G, et al., 2020, Assessing local costs and impacts of distributed solar PV using high resolution data from across Great Britain, Renewable Energy, Vol: 162, Pages: 1140-1150, ISSN: 0960-1481
Highly spatially resolved data from across Great Britain (GB) are combined with a distribution network modelling tool to assess impacts of distributed photovoltaic (PV) deployment up to 2050 on local networks, the costs of avoiding these impacts, and how these depend upon context. Present-day deployment of distributed PV, meter density, and network infrastructure across GB are found to be highly dependent on rurality, and data on these are used to build up three representative contexts: cities, towns, and villages. For each context, distribution networks are simulated, and impacts on these networks associated with PV deployment and growth in peak load up to 2050 calculated. Present-day higher levels of PV deployment in rural areas are maintained in future scenarios, necessitating upgrades in ambitious PV scenarios in towns and villages from around 2040, but not before 2050 in cities. Impacts of load growth are more severe than those of PV deployment, potentially necessitating upgrades in cities, towns, and villages from 2030. These are most extensive in cities and towns, where long feeders connect more customers, making networks particularly susceptible to impacts. Storage and demand side response are effective in reducing upgrade costs, particularly in cities and towns.
Strbac G, Pudjianto D, Aunedi M, et al., 2020, Role and value of flexibility in facilitating cost-effective energy system decarbonisation, PROGRESS IN ENERGY, Vol: 2
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- Citations: 15
Giannelos S, Djapic P, Pudjianto D, et al., 2020, Quantification of the energy storage contribution to security of supply through the F-factor methodology, Energies, Vol: 13, Pages: 826-826, ISSN: 1996-1073
The ongoing electrification of the heat and transport sectors is expected to lead to a substantial increase in peak electricity demand over the coming decades, which may drive significant investment in network reinforcement in order to maintain a secure supply of electricity to consumers. The traditional way of security provision has been based on conventional investments such as the upgrade of the capacity of electricity transmission or distribution lines. However, energy storage can also provide security of supply. In this context, the current paper presents a methodology for the quantification of the security contribution of energy storage, based on the use of mathematical optimization for the calculation of the F-factor metric, which reflects the optimal amount of peak demand reduction that can be achieved as compared to the power capability of the corresponding energy storage asset. In this context, case studies underline that the F-factors decrease with greater storage power capability and increase with greater storage efficiency and energy capacity as well as peakiness of the load profile. Furthermore, it is shown that increased investment in energy storage per system bus does not increase the overall contribution to security of supply.
Greenwood DM, Djapic P, Sarantakos I, et al., 2020, Pragmatic method for assessing the security of supply in future smart distribution networks, Pages: 221-224
Future distribution networks will be able to provide security of supply through a combination of conventional and smart solutions. This has the potential to require complex and time-consuming assessments using cost-benefit analysis and probabilistic, risk-based methods. The key goal of this project is to create a method for evaluating the security of supply from a combination of conventional and smart solutions which is rigorous enough to provide robust answers, but simple enough that it can be used routinely by planning engineers without in-depth knowledge of risk, statistics, probability, or reliability theory. This will be accomplished through an iterative, data-driven approach and validated via established risk analysis methods. This study presents underpinning analysis for the development of that method, including in-depth risk studies and sensitivity analysis of real distribution networks.
Pudjianto D, Djapic P, Strbac G, et al., 2020, DER reactive services and distribution network losses, CIRED 2020 Berlin Workshop (CIRED 2020), Publisher: Institution of Engineering and Technology (IET), Pages: 541-544, ISSN: 2515-0855
Managing synergies and conflicts between voltage support services and network losses is essential for the cost-effective integration of distributed energy resources (DERs). This study presents the results of studies investigating the impact of using DER reactive power services on distribution network losses. By using year-round optimal power flow analysis, a spectrum of studies on a number of distribution network areas in the southeast of Great Britain was performed to calculate distribution losses under different control scenarios. The studies demonstrate that the use of DERs to provide reactive services to the transmission system may increase distribution network losses. On the other hand, DER reactive services can also be optimised to minimise distribution losses. The studies also analysed the impact of optimising tap changing transformer settings on the distribution network losses reduction.
Sun M, Djapic P, Aunedi M, et al., 2019, Benefits of smart control of hybrid heat pumps: an analysis of field trial data, Applied Energy, Vol: 247, Pages: 525-536, ISSN: 0306-2619
Smart hybrid heat pumps have the capability to perform smart switching between electricity and gas by employing a fully-optimized control technology with predictive demand-side management to automatically use the most cost-effective heating mode across time. This enables a mechanism for delivering flexible demand-side response in a domestic setting. This paper conducts a comprehensive analysis of the fine-grained data collected during the world’s first sizable field trial of smart hybrid heat pumps to present the benefits of the smart control technology. More specifically, a novel flexibility quantification framework is proposed to estimate the capability of heat pump demand shifting based on preheating. Within the proposed framework, accurate estimation of baseline heat demand during the days with interventions is fundamentally critical for understanding the effectiveness of smart control. Furthermore, diversity of heat pump demand is quantified across different numbers of households as an important input into electricity distribution network planning. Finally, the observed values of the Coefficient of Performance (COP) have been analyzed to demonstrate that the smart control can optimize the heat pump operation while taking into account a variety of parameters including the heat pump output water temperature, therefore delivering higher average COP values by maximizing the operating efficiency of the heat pump. Finally, the results of the whole-system assessment of smart hybrid heat pumps demonstrate that the system value of smart control is between 2.1 and 5.3 £ bn/year.
Sun M, Strbac G, Djapic P, et al., 2019, Preheating quantification for smart hybrid heat pumps considering uncertainty, IEEE Transactions on Industrial Informatics, Vol: 15, Pages: 4753-4763, ISSN: 1551-3203
The deployment of smart hybrid heat pumps can introduce considerable benefits to electricity systems via smart switching between electricity and gas while minimizing the total heating cost for each individual customer. In particular, the fully-optimized control technology can provide flexible heat that redistributes the heat demand across time for improving the utilization of low-carbon generation and enhancing the overall energy efficiency of the heating system. To this end, accurate quantification of preheating is of great importance to characterize the flexible heat. This paper proposes a novel data-driven preheating quantification method to estimate the capability of heat pump demand shifting and isolate the effect of interventions. Varieties of fine-grained data from a real-world trial are exploited to estimate the baseline heat demand using Bayesian deep learning while jointly considering epistemic and aleatoric uncertainties. A comprehensive range of case studies are carried out to demonstrate the superior performance of the proposed quantification method and then, the estimated demand shift is used as an input into the whole-system model to investigate the system implications and quantify the range of benefits of rolling-out the smart hybrid heat pumps developed by PassivSystems to the future GB electricity systems.
Strbac G, Pudjianto D, Aunedi M, et al., 2019, Cost-effective decarbonization in a decentralized market the benefits of using flexible technologies and resources, IEEE Power and Energy Magazine, Vol: 17, Pages: 25-36, ISSN: 1540-7977
Papadaskalopoulos D, Moreira R, Strbac G, et al., 2018, Quantifying the potential economic benefits of flexible industrial demand in the European power system, IEEE Transactions on Industrial Informatics, Vol: 14, Pages: 5123-5132, ISSN: 1551-3203
The envisaged decarbonization of the European power system introduces complex techno-economic challenges to its operation and development. Demand flexibility can significantly contribute in addressing these challenges and enable a cost-effective transition to the low-carbon future. Although extensive previous work has analyzed the impacts of residential and commercial demand flexibility, the respective potential of the industrial sector has not yet been thoroughly investigated despite its large size. This paper presents a novel, whole-system modeling framework to comprehensively quantify the potential economic benefits of flexible industrial demand (FID) for the European power system. This framework considers generation, transmission and distribution sectors of the system, and determines the least-cost long-term investment and short-term operation decisions. FID is represented through a generic, process-agnostic model, which however accounts for fixed energy requirements and load recovery effects associated with industrial processes. The numerical studies demonstrate multiple significant value streams of FID in Europe, including capital cost savings by avoiding investments in additional generation and transmission capacity and distribution reinforcements, as well as operating cost savings by enabling higher utilization of renewable generation sources and providing balancing services.
Pudjianto D, Papadaskalopoulos D, Moreira R, et al., 2018, Flexibility Potential of Industrial Electricity Demand: Insights from the H2020 IndustRE project, The 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion
Zhang X, Strbac G, Teng F, et al., 2018, Economic assessment of alternative heat decarbonisation strategies through coordinated operation with electricity system - UK case study, APPLIED ENERGY, Vol: 222, Pages: 79-91, ISSN: 0306-2619
Zhang X, Strbac G, Djapic P, et al., 2017, Optimization of Heat Sector Decarbonization Strategy through Coordinated Operation with Electricity System, Energy Procedia, Vol: 142, Pages: 2858-2863, ISSN: 1876-6102
Konstantelos I, Djapic P, Strbac G, et al., 2017, Contribution of energy storage and demand-side response to security of distribution networks, CIRED 2017, Publisher: IEEE, Pages: 1650-1654, ISSN: 2515-0855
The smart grid paradigm envisages the wide penetration of distributed energy resources, such as demand-side response (DSR) schemes and energy storage (ES). Despite their potential to improve security of supply at the distribution level, existing design standards in most jurisdictions consider solely conventional assets; conceptual and methodological gaps prevent DSR and ES from being embedded into formal network design practices. As such, the crucial question that arises is how to assess the security contribution of these technologies so as to level the playing field and encourage the transition to a smart grid. Here, the authors introduce two capacity metrics: equivalent firm capacity and equivalent load-carrying capability. The authors describe their application to DSR and ES, showcase results from the UK Power Networks' Smarter Network Storage and Low Carbon London projects, and provide suggestions on the incorporation of smart assets in future design standards.
Djapic P, Strbac G, 2017, Economically efficient distribution network design, 24th International Conference & Exhibition on Electricity Distribution (CIRED) 12-15 June 2017, Publisher: IET, Pages: 2241-2245
Decarbonisation of electricity sector, potential increase in electricity demand driven by incorporation of segments of heat and transport sectors, and conditional asset replacement drive the desire for cost-effectiveness of the use of existing assets and use of non-network solutions. A Working Group is tasked to review present and, if needed, propose a new security of supply standard. This study reports on the part of work carried within review. It describes drivers and objective for review, used analytical methodology, and relevant drivers. The results of case studies carried out on illustrative high-voltage networks topology show breakeven value of lost load and economically efficient degree of redundancy for different values of drivers. The study concludes with the key findings of the study.
Djapic P, Strbac G, 2017, Value of load transfer capacity in distribution network design, IET International Conference on Resilience of Transmission and Distribution Networks (RTDN 2017), Publisher: Institution of Engineering and Technology
A fundamental review of the philosophy of distribution network operation and design is carried out to inform the industry, consumers, regulator and government, and facilitate a cost effective delivery of the UK Government energy policy objectives. Within the review potential benefit of load transfer capacity used to improve the reliability performance of the system is quantified. This is the subject addressed within this paper, showing used methodology and analysed case studies. The cost-benefit analysis is used to establish the reliability and cost performance of various network designs and emergency operation strategies. Potential benefit of load transfer capacity is calculated for different drivers: network loading, topology, voltage level, construction, and assets failure rate. It is found that the value of LTC is higher in low reliable networks and in systems with higher load. The value of LTC is less sensitive towards the number of supplied substations.
Djapic P, Strbac G, McKenna R, et al., 2017, Assessing the implications of socioeconomic diversity for low carbon technology uptake in electrical distribution networks, Applied Energy
Djapic P, Tindemans S, Strbac G, 2015, Comparison of Approaches for Quantifying Demand Side Response Capacity Credit for the Use in Distribution Network Planning, IET International Conference on Resilience of Transmission and Distribution Networks (RTDN 2015), Publisher: IET
The present UK distribution network planning standard,Engineering Recommendation P.2/6 (P2/6), defines theacceptable durations of supply outages following first andsecond circuit outage conditions as function of group demand.In addition, P2/6 specifies a capacity value for distributedgeneration (DG) to be used in future circuit capacity planning.The approach does not consider other elements of thedistribution network. This paper analyses the reliabilityperformance of distribution system when DSR is used todefer network upgrades driven by load growth. The analysisuses actual DSR performance data from trials that wereexecuted as part of the Low Carbon London project. The DSRcontribution to security of supply is assessed using aprobabilistic risk modelling framework to further inform anumber of topics (i) reliability contribution of DSRtechnologies in a network context, (ii) strengths andweaknesses of P2/6 in estimating contribution to security ofsupply, (iii) benefits of contractual redundancy, (iv) impact ofDSR coincidence in delivery (common mode failures) oncontribution to security, and (v) impact of DSR scale andmagnitude on contribution to security of supply.
Ustinova T, Woolf M, Ortega Calderon JE, et al., 2015, Analysis of Customers' Performance in Industrial & Commercial Demand Side Response Trials, 23rd International Conference on Electricity Distribution (CIRED 2015)
Tindemans S, Djapic P, Schofield J, et al., 2014, Resilience performance of smart distribution networks, Report D4 for the “Low Carbon London” LCNF project
Gan CK, Pudjianto D, Djapic P, et al., 2014, Strategic Assessment of Alternative Design Options for Multivoltage-Level Distribution Networks, IEEE TRANSACTIONS ON POWER SYSTEMS, Vol: 29, Pages: 1261-1269, ISSN: 0885-8950
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- Citations: 13
Pudjianto D, Aunedi M, Djapic P, et al., 2014, Whole-systems assessment of the value of energy storage in low-carbon electricity systems, IEEE Transactions on Smart Grid, Vol: 5, Pages: 1098-1109, ISSN: 1949-3061
Energy storage represents one of the key enabling technologies to facilitate an efficient system integration of intermittent renewable generation and electrified transport and heating demand. This paper presents a novel whole-systems approach to valuing the contribution of grid-scale electricity storage. This approach simultaneously optimizes investment into new generation, network and storage capacity, while minimising system operation cost, and also considering reserve and security requirements. Case studies on the system of Great Britain (GB) with high share of renewable generation demonstrate that energy storage can simultaneously bring benefits to several sectors, including generation, transmission and distribution, while supporting real-time system balancing. The analysis distinguishes between bulk and distributed storage applications, while also considering the competition against other technologies, such as flexible generation, interconnection and demand-side response.
Pudjianto D, Djapic P, Aunedi M, et al., 2013, Smart control for minimizing distribution network reinforcement cost due to electrification, ENERGY POLICY, Vol: 52, Pages: 76-84, ISSN: 0301-4215
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- Citations: 98
Strbac G, Djapić P, Bopp T, et al., 2012, Benefits of Active Management of Distribution Systems, Wind Power in Power Systems, Second Edition, Pages: 935-950, ISBN: 9780470974162
Castro M, Pudjianto D, Djapic P, et al., 2011, Reliability-driven transmission investment in systems with wind generation, IET GENERATION TRANSMISSION & DISTRIBUTION, Vol: 5, Pages: 850-859, ISSN: 1751-8687
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- Citations: 5
Pudjianto D, Gan CK, Stanojevic V, et al., 2010, Value of Integrating Distributed Energy Resources in the UK Electricity System, IEEE-Power-and-Energy-Society General Meeting, Publisher: IEEE, ISSN: 1944-9925
Mohamed S, Mohammed K, Rebic J, et al., 2009, Alternative investment strategies for improving distribution system reliability by using representative networks
The regulation of distribution network monopolies has been shifted from asset-based to performance-based, and continues to encourage performance improvement in terms of quality of service provided to customers. In addition to improving the quality of service, such a shift should be carried out in a cost-effective way. In order to achieve this, a general methodology is needed to compare the reliability performance with alternative investment strategies. Therefore, the last years have witnessed increasing interest towards development of analysis capability and tools that enables to adequately assess network performance and to evaluate benefits of alternative distribution network investment strategies. The enormous diversity of topologies, customer densities, and protection levels of the feeders in real distribution systems has been a major obstacle for strategic planning activities. In order to simplify the decision-making processes needed for distribution network planning, a specific model has been previously implemented. Within this model, a large number of real feeders are grouped by similar characteristics into a simplified network. More specifically, so-called Representative Networks (RNs) are calculated using easily manageable and accessible high-level information that is extracted from real feeders' databases reflecting reliability performance of group of real feeders with a great accuracy. This work illustrates how RNs can be used to assess the impact that performance-driven investment strategies will have in terms of reliability improvement at a strategic level. The representative network parameters are quantified based on the different investment scenarios (or a combination of investment scenarios). The methodology has been validated using real data from several Distribution Network Operators.
Lopes JAP, Hatziargyriou N, Mutale J, et al., 2007, Integrating distributed generation into electric power systems: A review of drivers, challenges and opportunities, ELECTRIC POWER SYSTEMS RESEARCH, Vol: 77, Pages: 1189-1203, ISSN: 0378-7796
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- Citations: 843
Pudjianto D, Castro MJ, Djapic P, et al., 2007, Transmission Investment and Pricing in Systems with Significant Penetration of Wind Generation, IEEE Power Engineering Society General Meeting, Pages: 1-3
Djapic P, Ramsay C, Pudjianto D, et al., 2007, Taking an active approach, IEEE POWER & ENERGY MAGAZINE, Vol: 5, Pages: 68-77, ISSN: 1540-7977
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- Citations: 66
Pudjianto D, Castro M, Djapic P, et al., 2007, Transmission investment and pricing in systems with significant penetration of wind generation, IEEE-Power-Engineering-Society General Meeting, Publisher: IEEE, Pages: 4563-+, ISSN: 1932-5517
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