This paper presents research which seeks to assist distribution network operators in the adoption of real-time thermal rating systems. The exploitation of power system rating variations is challenging due to the complex nature of environmental conditions such as wind speed. The adoption of a realtime thermal rating system may overcome this challenge and offers perceived benefits such as increased distributed generation accommodation and avoidance of component damage or premature ageing. Simulations, using lumped parameter component models, are used to investigate the influence of environmental conditions on overhead line, electric cable and power transformer ratings. Key findings showed that the average rating of overhead lines, electric cables and power transformers ranged from 1.70 to 2.53, 1.00 to 1.06 and 1.06 to 1.10 times the static rating, respectively. Since overhead lines were found to have the greatest potential for rating exploitation, the influence of environmental conditions on four overhead line types was investigated and it was shown that the value of a real-time thermal rating system is location dependent. Furthermore, the additional annual energy yield from distributed generation that could be accommodated through a real-time thermal rating system deployment was quantified for a specific case and found to be 54%.
This paper presents candidate strategies for the coordinated output control of multiple distributed generation schemes. The proposed strategies are underpinned by power flow sensitivity factors and allow real-time knowledge of power system thermal ratings to be utilised. This could be of value in situations where distribution network power flows require management as a result of distributed generation proliferation. Through off-line open-loop simulations, using historical data from a section of the UK distribution network, the candidate strategies are evaluated against a benchmark control solution in terms of annual energy yields, component losses and voltages. Furthermore, the individual generator annual energy yields and generatorapportioned losses are used to assess the net present values of candidate control strategies to distributed generation developers. Nomenclature C 1,2,3 Variable costs (£M) C control Cost of the distributed generator output control system (£M) G id Unique identifier (id) of distributed generator, G 0,x,y G P Real power output of the generator at the initial (0), intermediate (x) and final (y) time-steps (MW) G P,m Real power output of distributed generator, G, at node m (MW) 'G P,m Real power output of distributed generator, G, at node m before control actions have been implemented (MW) "G P,m Real power output of distributed generator, G, at node m after control actions have been implemented (MW) ΣG P,m Total real power injection at node m from multiple distributed generators (MW) J Jacobian matrix of AC load flow K Proportionality factor M LIFO Matrix denoting the last-in first-off constraint order of distributed generation schemes M PFSF Matrix of power flow sensitivity factors 'S i,k Apparent power flowing from node i to node k before control actions are implemented (MVA) U i,k Utilisation of component between node i and node k U Tar Target utilisation of component after control actions have been implemented V Vector of nodal voltages (kV) dP i,k / dG P,m Power flow sensitivity factor representing the change in real power flow from node i to node k due to change in real power output of generator connected to node m i Busbar node k Busbar node m Busbar node n Number of stakeholder investors in real-time thermal rating system t Integration time-step (h) x Ranked order of constraint for a distributed generator ΔG P,m Required change in real power output of the generator, G, at node m (MW) ΔP i,k Required change in real power flowing from node i to node k for network power flow management (MW) Φ Egalitarian broadcast reduction signal (%)θ Vector of nodal voltage angles (rad) AuRA-NMS Autonomous regional active network management system AC Alternating current B Busbar C Component 5 CAISO Californian independent system operator DG Distributed generation DNO Distribution network operator GSP Grid supply point LIFO Last-in first-off PFSF Power flow sensitivity factor (defined as dP i,k / dG P,m ) ROC Renewables Obligation Certificate RTTR Real-time thermal rating (defined as S lim ) SCADA S...
This article describes research that aims to realize a real-time rating (RTR) system for power system components. The RTR technology is regarded with interest due to its potential to unlock network power transfer capacity, improve power flow congestion management flexibility, and facilitate the connection of distributed generation. The solution described in this work involves the use of a limited number of meteorological stations and a series of analytical models for estimating component ratings. The effect of data uncertainty is taken into account by an estimation algorithm based on the Monte Carlo method. Estimations of conductor temperature and environmental conditions have been validated against measured data in five different network locations. Average errors of −2.2, −1.9, −1.2, −1.9, and 1.4 • C were found for the five different network locations over a period of 71 days when comparing estimates to measured results. Results analysis identified that the models used were the main source of error. The estimation of wind direction and solar radiation was the most sensitive to errors in the models. Therefore, suggestions are made regarding the improvement of these models and the RTR estimation system. Overhead line real-time rating estimation algorithm 295 JPE859 Proc. IMechE Vol. 224 Part A: J. Power and Energy
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