Integrated Expansion Planning of Electricity, Heat, and Gas in Presence of Demand and Wind Uncertainty
| dc.contributor.advisor | Rosehart, William | |
| dc.contributor.author | Mozafari Jovein, Yasaman | |
| dc.contributor.committeemember | Bergerson, Joule | |
| dc.contributor.committeemember | Westwick, David | |
| dc.contributor.committeemember | Zinchenko, Yuriy | |
| dc.contributor.committeemember | Yanushkevich, Svetlana | |
| dc.contributor.committeemember | Gokaraju, Ramakrishna | |
| dc.date | 2022-11 | |
| dc.date.accessioned | 2022-07-07T13:57:25Z | |
| dc.date.available | 2022-07-07T13:57:25Z | |
| dc.date.issued | 2022-06-22 | |
| dc.description.abstract | Recent shift towards higher renewable penetration in power systems, has resulted in increasing gas-fired generation capacity in power systems, implying electricity and gas infrastructure interdependency. Furthermore, highly efficient combined heat and power (CHP) units lead to heat and electricity interdependency. It is crucial to consider these interdependencies in the expansion planning of energy systems for an effective and reliable investment planning and policy design. In this thesis, the problem of integrated expansion planning of electricity, heat, and gas in presence of demand and wind uncertainty is addressed. A comprehensive multi-area planning model including generation, CHPs, boilers, transmission network, and gas pipeline expansion is proposed. The advantages of integrated approach versus the non-integrated approaches in terms of cost and emission is illustrated through simulations on a simplified Alberta energy system model. Representative operating scenario selection method is used to model wind and demand uncertainties, and to address computational complexity of a central planning model. Load duration curve technique is compared with k-means and k-means++ clustering, the impact of initialization is investigated, and the impact of spatial data correlation on the solution is analyzed. To overcome drawbacks of k-means clustering, application of algebraic multi-grid clustering in scenario selection for integrated energy system expansion planning is explored. The simulation results on a modified IEEE-118 bus test system and a 14-node gas network shows that the algebraic multi-grid clustering outperforms the classical methods such as k-means by following the benchmark case more closely. Finally, to ensure robustness of the obtained investment plan, an adaptive robust optimization model including electricity demand, heat demand, and wind uncertainty is proposed. The model ensures reliability targets in both electricity and heat sector are met. The simulation results on the IEEE-118 bus test system verify the effectiveness of the proposed model in dealing with uncertainties and meeting future electricity and heat demand reliably. | en_US |
| dc.identifier.citation | Mozafari Jovein, Y. (2022). Integrated Expansion Planning of Electricity, Heat, and Gas in Presence of Demand and Wind Uncertainty (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. | en_US |
| dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/39880 | |
| dc.identifier.uri | http://hdl.handle.net/1880/114810 | |
| dc.publisher.faculty | Schulich School of Engineering | en_US |
| dc.publisher.institution | University of Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | en_US |
| dc.subject | Power systems expansion planning | en_US |
| dc.subject | Integrated energy systems | en_US |
| dc.subject | Wind and demand uncertainty | en_US |
| dc.subject | Clustering | en_US |
| dc.subject | Robust optimization | en_US |
| dc.subject.classification | Energy | en_US |
| dc.subject.classification | Engineering--Electronics and Electrical | en_US |
| dc.title | Integrated Expansion Planning of Electricity, Heat, and Gas in Presence of Demand and Wind Uncertainty | en_US |
| dc.type | doctoral thesis | en_US |
| thesis.degree.discipline | Engineering – Electrical & Computer | en_US |
| thesis.degree.grantor | University of Calgary | en_US |
| thesis.degree.name | Doctor of Philosophy (PhD) | en_US |
| ucalgary.item.requestcopy | true | en_US |