40 results found
Deinum EE, Tindemans SH, Lindeboom JJ, et al., 2017, How selective severing by katanin promotes order in the plant cortical microtubule array, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol: 114, Pages: 6942-6947, ISSN: 0027-8424
Konstantelos I, Jamgotchian G, Tindemans SH, et al., 2017, Implementation of a Massively Parallel Dynamic Security Assessment Platform for Large-Scale Grids, IEEE TRANSACTIONS ON SMART GRID, Vol: 8, Pages: 1417-1426, ISSN: 1949-3053
Tindemans SH, Deinum EE, 2017, corticalsim: cortical microtubule simulator
Cortical microtubule simulator [C++ code]
Tindemans SH, Strbac G, 2017, Robust estimation of risks from small samples, Philosophical Transactions A: Mathematical, Physical and Engineering Sciences, Vol: 375, ISSN: 1471-2962
Data-driven risk analysis involves the inference of probability distributions from measured or simulated data. In the case of a highly reliable system, such as the electricity grid, the amount of relevant data is often exceedingly limited, but the impact of estimation errors may be very large. This paper presents a robust nonparametric Bayesian method to infer possible underlying distributions. The method obtains rigorous error bounds even for small samples taken from ill-behaved distributions. The approach taken has a natural interpretation in terms of the intervals between ordered observations, where allocation of probability mass across intervals is well-specified, but the location of that mass within each interval is unconstrained. This formulation gives rise to a straightforward computational resampling method: Bayesian Interval Sampling. In a comparison with common alternative approaches, it is shown to satisfy strict error bounds even for ill-behaved distributions.
Trovato V, Tindemans S, Strbac G, 2017, Understanding the Aggregate Flexibility of Thermostatically Controlled Loads, IEEE Manchester PowerTech, Publisher: IEEE
Calvo JL, Tindemans SH, Strbac G, 2016, Incorporating failures of System Protection Schemes into power system operation, SUSTAINABLE ENERGY GRIDS & NETWORKS, Vol: 8, Pages: 98-110, ISSN: 2352-4677
Schofield JR, Tindemans SH, Strbac G, 2016, A baseline-free method to identify responsive customers on dynamic time-of-use tariffs
Dynamic time-of-use tariffs incentivise changes in electricity consumption.This paper presents a non-parametric method to retrospectively analyseconsumption data and quantify the significance of a customer's observedresponse to a dynamic price signal without constructing a baseline demandmodel. If data from a control group is available, this can be used to infercustomer responsiveness - individually and collectively - on an absolute scale.The results are illustrated using data from the Low Carbon London project,which included the UK's first dynamic time-of-use pricing trial.
Sheehy S, Edwards G, Dent CJ, et al., 2016, Impact of High Wind Penetration on Variability of Unserved Energy in Power System Adequacy, International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), Publisher: IEEE
Sun M, Konstantelos I, Tindemans S, et al., 2016, Evaluating Composite Approaches to Modelling High-Dimensional Stochastic Variables in Power Systems, 19th Power Systems Computation Conference (PSCC), Publisher: IEEE
Tindemans SH, Strbac G, 2016, Nondisruptive decentralized control of thermal loads with second order thermal models, IEEE-Power-and-Energy-Society General Meeting (PESGM), Publisher: IEEE, ISSN: 1944-9925
Trovato V, Tindemans SH, Strbac G, 2016, Leaky storage model for optimal multi-service allocation of thermostatic loads, IET GENERATION TRANSMISSION & DISTRIBUTION, Vol: 10, Pages: 585-593, ISSN: 1751-8687
Yang Y, Tindemans S, Strbac G, 2016, An Implicit Switching Model for Distribution Network Reliability Assessment, 19th Power Systems Computation Conference (PSCC), Publisher: IEEE
Calvo JL, Tindemans SH, Strbac G, 2015, Managing risks from reverse flows under distribution network outage scenarios
Distribution networks have been traditionally conceived for transporting electricity downstream into low voltage demand nodes. However, the connection of significant amounts of distributed generation may reverse this condition, resulting in distribution nodes exporting power to other parts of the network. The current planning standard of the UK distribution networks (Engineering recommendation P2/6) requires making available sufficient capacity and redundancy for downstream flows under peak demand levels. However, it does not explicitly consider the implications of DG-mediated flow reversals that may cause flow constraints under circuit outage conditions. Relying on a Monte Carlo approach to sample wind and demand with adjustable correlations, this paper provides insights into the risks associated with an increase of variable distributed generation to the point where reverse flows may exceed the connection capacity under circuit outage conditions. Remote tripping schemes that disconnect distributed generators upon occurrence of a fault are explored to mitigate outage related costs. The latter strategy carries benefits but also novel risks in the form of a reliance on real-time communication and control, which may malfunction. It is shown that even unreliable corrective actions convey significant benefits to system reliability.
Djapic P, Tindemans S, Strbac G, 2015, Comparison of approaches for quantifying demand side response capacity credit for the use in distribution network planning
The present UK distribution network planning standard, Engineering Recommendation P.2/6 (P2/6), defines the acceptable durations of supply outages following first and second circuit outage conditions as function of group demand. In addition, P2/6 specifies a capacity value for distributed generation (DG) to be used in future circuit capacity planning. The approach does not consider other elements of the distribution network. This paper analyses the reliability performance of distribution system when DSR is used to defer network upgrades driven by load growth. The analysis uses actual DSR performance data from trials that were executed as part of the Low Carbon London project. The DSR contribution to security of supply is assessed using a probabilistic risk modelling framework to further inform a number of topics (i) reliability contribution of DSR technologies in a network context, (ii) strengths and weaknesses of P2/6 in estimating contribution to security of supply, (iii) benefits of contractual redundancy, (iv) impact of DSR coincidence in delivery (common mode failures) on contribution to security, and (v) impact of DSR scale and magnitude on contribution to security of supply.
Schofield J, Carmichael R, Tindemans S, et al., 2015, Experimental validation of residential consumer responsiveness to dynamic time-of-use pricing, 23rd International Conference on Electricity Distribution (CIRED)
This paper describes the first analysis from the LowCarbon London (LCL), residential dynamic time-of-use(dToU) pricing trial that took place in the London areaduring 2013. High price induced peak reductions fornetwork constraint management are investigatedalongside the temporal availability of demand responsefor supply balancing. By examining both these use caseswe identify potential conflicts between network andsystem objectives. Demand response results are stratifiedby a ranking metric for engagement with the dToU tariffas well as household occupancy and socio-economicclassification.
Tindemans SH, Strbac G, 2015, Visualising risk in generating capacity adequacy studies using clustering and prototypes, General Meeting of the IEEE-Power-and-Energy-Society, Publisher: IEEE, ISSN: 1944-9925
Tindemans SH, Trovato V, Strbac G, 2015, Decentralized Control of Thermostatic Loads for Flexible Demand Response, IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, Vol: 23, Pages: 1685-1700, ISSN: 1063-6536
Tindemans SH, Trovato V, Strbac G, 2015, Frequency control using thermal loads under the proposed ENTSO-E Demand Connection Code, PowerTech, 2015 IEEE Eindhoven, Publisher: IEEE
Trovato V, Tindemans SH, Strbac G, 2015, Designing effective frequency response patterns for flexible thermostatic loads, IEEE 15th International Conference on Environment and Electrical Engineering (EEEIC), Publisher: IEEE, Pages: 1003-1008
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)
de Miguel JLC, Ramirez PJ, Tindemans SH, et al., 2015, Cost-Benefit Analysis of Unreliable System Protection Scheme Operation, PowerTech, 2015 IEEE Eindhoven, Publisher: IEEE
Schofield J, Carmichael R, Tindemans S, et al., 2014, Residential consumer responsiveness to time-varying pricing, Report A3 for the “Low Carbon London” LCNF project
Tindemans S, Djapic P, Schofield J, et al., 2014, Resilience performance of smart distribution networks, Report D4 for the “Low Carbon London” LCNF project
Tindemans SH, Deinum EE, Lindeboom JJ, et al., 2014, Efficient event-driven simulations shed new light on microtubule organization in the plant cortical array, Frontiers of Physics, Vol: 2, Pages: 1-15, ISSN: 2095-0462
© 2014 Tindemans, Deinum, Lindeboom and Mulder. The dynamics of the plant microtubule cytoskeleton is a paradigmatic example of the complex spatiotemporal processes characterizing life at the cellular scale. This system is composed of large numbers of spatially extended particles, each endowed with its own intrinsic stochastic dynamics, and is capable of non-equilibrium self-organization through collisional interactions of these particles. To elucidate the behavior of such a complex system requires not only conceptual advances, but also the development of appropriate computational tools to simulate it. As the number of parameters involved is large and the behavior is stochastic, it is essential that these simulations be fast enough to allow for an exploration of the phase space and the gathering of sufficient statistics to accurately pin down the average behavior as well as the magnitude of fluctuations around it. Here we describe a simulation approach that meets this requirement by adopting an event-driven methodology that encompasses both the spontaneous stochastic changes in microtubule state as well as the deterministic collisions. In contrast with finite time step simulations this technique is intrinsically exact, as well as several orders of magnitude faster, which enables ordinary PC hardware to simulate systems of ~103 microtubules on a time scale ~103 faster than real time. In addition we present new tools for the analysis of microtubule trajectories on curved surfaces. We illustrate the use of these methods by addressing a number of outstanding issues regarding the importance of various parameters on the transition from an isotropic to an aligned and oriented state.
Trovato V, Tindemans SH, Strbac G, 2014, Security constrained economic dispatch with flexible thermostatically controlled loads, IEEE PES ISGT Europe 2014
Thermostatically controlled loads (TCLs) such as refrigerators and air conditioners are natural candidates for short term demand response. In this paper we quantify the value associated with the TCLs' ability to provide system security and transmission constraint management services. The analysis builds on recent results that enable the aggregate control of TCLs as a leaky storage unit. We incorporate this model in a security constrained economic dispatch (SCED) that minimizes the system operational cost of a two bus-bar system, subject to frequency response and transmission constraints. Further sensitivity studies assess the impact of different penetration levels of controllable loads and transmission flow constraints.
Lindeboom JJ, Lioutas A, Deinum EE, et al., 2013, Cortical Microtubule Arrays Are Initiated from a Nonrandom Prepattern Driven by Atypical Microtubule Initiation, PLANT PHYSIOLOGY, Vol: 161, Pages: 1189-1201, ISSN: 0032-0889
Trovato G, Tindemans SH, Strbac G, 2013, Demand Response Contribution to Effective Inertia for System Security in the GB 2020 Gone Green Scenario, IEEE Innovative Smart Grid Technologies (ISGT) Europe 2013
Trovato V, Tindemans SH, Strbac G, 2013, Controlling the synchronization and payback associated with the provision of frequency services by dynamic demand, 22nd International Conference on Electricity Distribution (CIRED 2013)
Deinum EE, Tindemans SH, Mulder BM, 2011, Taking directions: the role of microtubule-bound nucleation in the self-organization of the plant cortical array, PHYSICAL BIOLOGY, Vol: 8, ISSN: 1478-3975
Hawkins RJ, Tindemans SH, Mulder BM, 2010, Model for the orientational ordering of the plant microtubule cortical array, PHYSICAL REVIEW E, Vol: 82, ISSN: 1539-3755
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