Electricity distribution system planning considering incentive reliability regulations

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School of Electrical Engineering | Doctoral thesis (monograph) | Defence date: 2020-08-17
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Aalto University publication series DOCTORAL DISSERTATIONS, 105/2020
Electricity distribution systems are dynamically expanded in anticipation of new demands. Cost and reliability are the most important factors in finding the optimal plans for the network expansion. Recently, implementation of incentive reliability regulations has accentuated the role of reliability considerations in distribution systems studies. This is because such incentive schemes create a direct link between distribution companies' revenues and their service reliability. Thus, these schemes have changed the role of reliability from a technical constraint to an economic factor. In this occasion, distribution companies require new techniques to incorporate the effects of incentive reliability regulations in their planning studies to get the most benefits. Motivated by these points, in this dissertation, various mathematical models are developed to incorporate the incentive reliability regulations into the planning studies of electricity distribution networks. Due to the rapid pace of technological advances in distribution systems, the proposed models consider a wide range of possible scenarios for future networks such as energy hubs, preventive maintenance scheduling, interconnection with natural gas distribution networks, and integration of various distributed generation technologies. In this respect, mathematical models for co-expansion planning of integrated electricity and natural gas networks, optimal scheduling of preventive maintenance actions, and optimal energy hub planning are devised. In addition, various frameworks are proposed to investigate the impacts of parameters of the incentive reliability schemes on distribution companies performance and potential outcomes of the implementation of the incentive regulations. In order to incorporate the reliability regulations into the panning studies, reliability indices must be quantified. Nonetheless, conventional reliability assessment techniques are not applicable due to their limitations. Novel reliability evaluation techniques are proposed in this thesis to address this issue. The proposed reliability models are cast as mixed-integer linear programming expressions which facilitates their integrations into standard mathematical programming models for distribution system planning and operation. It is worth mentioning that the reliability assessment models developed in this thesis can be applied to both passive and active distribution networks.
A doctoral dissertation completed for the degree of Doctor of Science (Technology) to be defended, with the permission of the Aalto University School of Electrical Engineering. Remote connection link https://aalto.zoom.us/j/64761320104, on 17 August 2020 at 12:15. Zoom Quick Guide: https://www.aalto.fi/en/services/zoom-quick-guide Electronic online display version of the doctoral thesis is available by email by request from aaltodoc-diss@aalto.fi
Supervising professor
Lehtonen, Matti, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland; Abbaspour-Tehranifard, Ali, Prof., Sharif University of Technology, Iran; Fotuhi-Firuzabad, Mahmud, Prof., Sharif University of Technology, Iran
Thesis advisor
Lehtonen, Matti, Prof., Aalto University, Department of Electrical Engineering and Automation, Finland
distributed generation, electricity power distribution system, electricity distribution system planning, energy hub, expansion co-planning, expansion planning, incentive reliability regulations, mixed-integer linear programming
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