<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Complex energy flows exist in integrated energy systems (IESs), and the optimal assignment of different energy sources has become a primary challenge in the initial stage of its construction. In addition, multiple uncertainties, such as wind power fluctuations and multiple energy load fluctuations, are not well-respected in IES planning. In order to solve the above problems, the generation expansion planning model in IES is proposed. In the model the uncertainties of renewable energy resources (RESs) are described by scenarios, while the power price and fuel price are described by intervals, and a stochastic/robust (S/R) optimization is established to minimize the sum of annual investment cost, operation cost and reliability cost. Based on duality theory, the proposed multi-level S/R optimization model is transformed into a mixed integer linear programming (MILP) model, which can be solved using the CPLEX solver. The proposed model is tested on the IEEE 33-node distribution system with an 11-node cold-heat system. The validity and effectiveness of the proposed model are illustrated by case studies.</p>
</abstract>

Complex energy flows exist in integrated energy systems (IESs), and the optimal assignment of different energy sources has become a primary challenge in the initial stage of its construction. In addition, multiple uncertainties, such as wind power fluctuations and multiple energy load fluctuations, are not well-respected in IES planning. In order to solve the above problems, the generation expansion planning model in IES is proposed. In the model the uncertainties of renewable energy resources (RESs) are described by scenarios, while the power price and fuel price are described by intervals, and a stochastic/robust (S/R) optimization is established to minimize the sum of annual investment cost, operation cost and reliability cost. Based on duality theory, the proposed multi-level S/R optimization model is transformed into a mixed integer linear programming (MILP) model, which can be solved using the CPLEX solver. The proposed model is tested on the IEEE 33-node distribution system with an 11-node cold-heat system. The validity and effectiveness of the proposed model are illustrated by case studies.

A Hybrid Stochastic/Robust Planning Model for Integrated Energy System Considering Multiple Uncertainties

Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Complex energy flows exist in integrated energy systems (IESs), and the optimal assignment of different energy sources has become a primary challenge in the...

A Hybrid Stochastic/Robust Planning Model for Integrated Energy System Considering Multiple Uncertainties

Pubblicato online: 02 giu 2023

Pagine: -

Ricevuto: 19 giu 2022

Accettato: 13 ott 2022

DOI: https://doi.org/10.2478/amns.2023.1.00147

Parole chiave
Dual theory, generation expansion planning, integrated energy system, stochastic/robust optimization

© 2023 Xiaolei Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

A Hybrid Stochastic/Robust Planning Model for Integrated Energy System Considering Multiple Uncertainties

Pubblicato online: 02 giu 2023

Pagine: -

Ricevuto: 19 giu 2022

Accettato: 13 ott 2022

DOI: https://doi.org/10.2478/amns.2023.1.00147

Parole chiaveDual theory, generation expansion planning, integrated energy system, stochastic/robust optimization

© 2023 Xiaolei Zhang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
Dual theory, generation expansion planning, integrated energy system, stochastic/robust optimization