Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments

Li Hui; Liu Siwei; Wu Lei; Qi Qingru; Zhang Mingli; Shu Jun

doi:10.1109/EI2.2018.8582336

Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments

Li Hui
, Liu Siwei
, Wu Lei
, Qi Qingru
, Zhang Mingli
, Shu Jun

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper presents a new approach for solving the multi-year co-optimized generation and transmission expansion planning problem with renewable energy resources in geographic information systems (GIS). The proposed optimization model is to determine when (which year), where (which cell), and what (which type) generators and transmission lines will be built for minimizing the sum of investment costs, operation costs (including energy and emission costs), and load shedding costs during the planning horizon. Prevailing constraints include power balance requirements, branch limits, power limits of generators, and construction limits of cells. A two-step approach to combine Dijkstra's algorithm and mixed-integer linear programming (MILP) is introduced for solving the large-scale optimization problem. The effectiveness of the proposed approach is validated by numerical case studies on a 9-bus system.

Original language	English
Title of host publication	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings
ISBN (Electronic)	9781538685495
DOIs	https://doi.org/10.1109/EI2.2018.8582336
State	Published - 19 Dec 2018
Event	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Beijing, China Duration: 20 Oct 2018 → 22 Oct 2018

Publication series

Name	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings

Conference

Conference	2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018
Country/Territory	China
City	Beijing
Period	20/10/18 → 22/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Dijkstra's algorithm
Long-term planning
co-optimized generation and transmission expansion planning
geographic information systems
mixed-integer linear programming
optimal line routing
renewable generation planning

Access to Document

10.1109/EI2.2018.8582336

Cite this

Hui, L., Siwei, L., Lei, W., Qingru, Q., Mingli, Z., & Jun, S. (2018). Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments. In 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings Article 8582336 (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings). https://doi.org/10.1109/EI2.2018.8582336

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title = "Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments",

abstract = "This paper presents a new approach for solving the multi-year co-optimized generation and transmission expansion planning problem with renewable energy resources in geographic information systems (GIS). The proposed optimization model is to determine when (which year), where (which cell), and what (which type) generators and transmission lines will be built for minimizing the sum of investment costs, operation costs (including energy and emission costs), and load shedding costs during the planning horizon. Prevailing constraints include power balance requirements, branch limits, power limits of generators, and construction limits of cells. A two-step approach to combine Dijkstra's algorithm and mixed-integer linear programming (MILP) is introduced for solving the large-scale optimization problem. The effectiveness of the proposed approach is validated by numerical case studies on a 9-bus system.",

keywords = "Dijkstra's algorithm, Long-term planning, co-optimized generation and transmission expansion planning, geographic information systems, mixed-integer linear programming, optimal line routing, renewable generation planning",

author = "Li Hui and Liu Siwei and Wu Lei and Qi Qingru and Zhang Mingli and Shu Jun",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 ; Conference date: 20-10-2018 Through 22-10-2018",

year = "2018",

month = dec,

day = "19",

doi = "10.1109/EI2.2018.8582336",

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Hui, L, Siwei, L, Lei, W, Qingru, Q, Mingli, Z & Jun, S 2018, Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments. in 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings., 8582336, 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings, 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018, Beijing, China, 20/10/18. https://doi.org/10.1109/EI2.2018.8582336

Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments. / Hui, Li; Siwei, Liu; Lei, Wu et al.
2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings. 2018. 8582336 (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments

AU - Hui, Li

AU - Siwei, Liu

AU - Lei, Wu

AU - Qingru, Qi

AU - Mingli, Zhang

AU - Jun, Shu

PY - 2018/12/19

Y1 - 2018/12/19

N2 - This paper presents a new approach for solving the multi-year co-optimized generation and transmission expansion planning problem with renewable energy resources in geographic information systems (GIS). The proposed optimization model is to determine when (which year), where (which cell), and what (which type) generators and transmission lines will be built for minimizing the sum of investment costs, operation costs (including energy and emission costs), and load shedding costs during the planning horizon. Prevailing constraints include power balance requirements, branch limits, power limits of generators, and construction limits of cells. A two-step approach to combine Dijkstra's algorithm and mixed-integer linear programming (MILP) is introduced for solving the large-scale optimization problem. The effectiveness of the proposed approach is validated by numerical case studies on a 9-bus system.

AB - This paper presents a new approach for solving the multi-year co-optimized generation and transmission expansion planning problem with renewable energy resources in geographic information systems (GIS). The proposed optimization model is to determine when (which year), where (which cell), and what (which type) generators and transmission lines will be built for minimizing the sum of investment costs, operation costs (including energy and emission costs), and load shedding costs during the planning horizon. Prevailing constraints include power balance requirements, branch limits, power limits of generators, and construction limits of cells. A two-step approach to combine Dijkstra's algorithm and mixed-integer linear programming (MILP) is introduced for solving the large-scale optimization problem. The effectiveness of the proposed approach is validated by numerical case studies on a 9-bus system.

KW - Dijkstra's algorithm

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KW - co-optimized generation and transmission expansion planning

KW - geographic information systems

KW - mixed-integer linear programming

KW - optimal line routing

KW - renewable generation planning

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ER -

Hui L, Siwei L, Lei W, Qingru Q, Mingli Z, Jun S. Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments. In 2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings. 2018. 8582336. (2nd IEEE Conference on Energy Internet and Energy System Integration, EI2 2018 - Proceedings). doi: 10.1109/EI2.2018.8582336

Long-Term Co-Optimized Generation and Transmission Expansion Planning with Renewables in Complicated Environments

Abstract

Publication series

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UN SDGs

Keywords

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