Risk–constrained stochastic economic dispatch and demand response with maximal renewable penetration under renewable obligation

dc.contributor.advisorNaidoo, Robin
dc.contributor.coadvisorBansal, Ramesh C.
dc.contributor.coadvisorZhang, Jiangfeng
dc.contributor.emailgreg.hlalele@gmail.comen_ZA
dc.contributor.postgraduateHlalele, Thabo Gregory
dc.date.accessioned2022-04-06T12:41:02Z
dc.date.available2022-04-06T12:41:02Z
dc.date.created2021
dc.date.issued2020
dc.descriptionThesis (PhD (Electrical Engineering))--University of Pretoria, 2020.en_ZA
dc.description.abstractIn the recent years there has been a great deal of attention on the optimal demand and supply side strategy. The increase in renewable energy sources and the expansion in demand response programmes has shown the need for a robust power system. These changes in power system require the control of the uncertain generation and load at the same time. Therefore, it is important to provide an optimal scheduling strategy that can meet an adequate energy mix under demand response without affecting the system reliability and economic performance. This thesis addresses the following four aspects to these changes. First, a renewable obligation model is proposed to maintain an adequate energy mix in the economic dispatch model while minimising the operational costs of the allocated spinning reserves. This method considers a minimum renewable penetration that must be achieved daily in the energy mix. If the renewable quota is not achieved, the generation companies are penalised by the system operator. The uncertainty of renewable energy sources are modelled using the probability density functions and these functions are used for scheduling output power from these generators. The overall problem is formulated as a security constrained economic dispatch problem. Second, a combined economic and demand response optimisation model under a renewable obligation is presented. Real data from a large-scale demand response programme are used in the model. The model finds an optimal power dispatch strategy which takes advantage of demand response to minimise generation cost and maximise renewable penetration. The optimisation model is applied to a South African large-scale demand response programme in which the system operator can directly control the participation of the electrical water heaters at a substation level. Actual load profile before and after demand reduction are used to assist the system operator in making optimal decisions on whether a substation should participate in the demand response programme. The application of these real demand response data avoids traditional approaches which assume arbitrary controllability of flexible loads. Third, a stochastic multi-objective economic dispatch model is presented under a renewable obligation. This approach minimises the total operating costs of generators and spinning reserves under renewable obligation while maximising renewable penetration. The intermittency nature of the renewable energy sources is modelled using dynamic scenarios and the proposed model shows the effectiveness of the renewable obligation policy framework. Due to the computational complexity of all possible scenarios, a scenario reduction method is applied to reduce the number of scenarios and solve the model. A Pareto optimal solution is presented for a renewable obligation and further decision making is conducted to assess the trade-offs associated with the Pareto front. Four, a combined risk constrained stochastic economic dispatch and demand response model is presented under renewable obligation. An incentive based optimal power dispatch strategy is implemented to minimise generation costs and maximise renewable penetration. In addition, a risk-constrained approach is used to control the financial risks of the generation company under demand response programme. The coordination strategy for the generation companies to dispatch power using thermal generators and renewable energy sources while maintaining an adequate spinning reserve is presented. The proposed model is robust and can achieve significant demand reduction while increasing renewable penetration and decreasing the financial risks for generation companies.en_ZA
dc.description.availabilityUnrestricteden_ZA
dc.description.degreePhD (Electrical Engineering)en_ZA
dc.description.departmentElectrical, Electronic and Computer Engineeringen_ZA
dc.identifier.citation*en_ZA
dc.identifier.otherA2021en_ZA
dc.identifier.urihttp://hdl.handle.net/2263/84811
dc.language.isoenen_ZA
dc.publisherUniversity of Pretoria
dc.rights© 2021 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subjectUCTDen_ZA
dc.subjectBattery energy storageen_ZA
dc.subjectdynamic economic dispatchen_ZA
dc.subjectincentive based demand response programmeen_ZA
dc.subjectmulti-objective optimisationen_ZA
dc.subjectPareto optimal solutionen_ZA
dc.titleRisk–constrained stochastic economic dispatch and demand response with maximal renewable penetration under renewable obligationen_ZA
dc.typeThesisen_ZA

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