(Reliability Evaluation of Electric Power Systems Integrating Smart Grid Solutions Mohamed Galeela, The University of Manchester, Sep 2019) This thesis provides a novel dimension for DR in optimising network OHLs assetâs life considers operatorâs preferences regarding OHL ageing criticality and network reliability requirements. A probabilistic emergency DR model is provided defining the operatorsâ requirements of demand response power and duration participation considering network topology and componentsâ failures. It also proposes an advanced realistic DR restoration model that accounts for operatorsâ financial penalties for partial DR restoration. The outcomes of this study will assist the operators in structuring more credible and realistic DR contracts activated at network contingencies. It also informs the operators with a reduced emergency loading limit applied on critically aged lines having DR availability at their receiving ends. This model could assist the operators in enhancing their asset management platforms under the smart grid paradigm. When applying the method on the IEEE RTS 24-bus system, the results show improvements in expected energy not supplied and expected interruption costs reaches 30% with reduction in network ageing reaching 55% such that the ageing of long-term emergency rating of most critically aged lines is reduced with EDR by almost 24% and 38% depending on the ageing criticality. This work also explores an extra flexibility option generated from the BESS through developing a battery degradation model integrated with the standard reliability framework through a multi-year network analysis accounting for BESS degradation risks. This study informs operators with the techno-economic worth of accelerating battery degradation as well as its impact on the long-term network planning analysis in terms of altering the net present value and affecting the operatorsâ profits. The results show that the NPV is almost 18M$ higher when accelerated BESS degradation is considered. The work also examines the worth of investments in OHL time-varying thermal ratings (TVTR) to minimise the required storage investments. Hence, the cost constraints for grid-scale battery storage are handled economically allowing more grid-scale storage deployment. The results of a specific case study on the IEEE RTS 24-bus show that investing in TVTR with costs representing 1.8 % of the BESS capital cost displaces a BESS size worth 12.2% of BESS capital costs with preserving acceptable network reliability levels. In summary, this work is one step towards having a pool of smart grid technologies mix operated in economic way with optimised reliability levels and minimised smart grid technology risks.
|Date of Award||31 Dec 2019|
- The University of Manchester
|Supervisor||Jovica Milanovic (Supervisor) & Kostas Kopsidas (Supervisor)|