Adjustable robust interval economic dispatch of integrated electricity and district heating systems under wind power uncertainty

Zhang, Rufeng; Chen, Yan; Li, Benxin; Jiang, Tao; Li, Xue; Chen, Houhe; Ning, Ruoxi

doi:10.1016/j.egyr.2022.09.086

Cited by 10 publications

(2 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, the solutions obtained through this method may fall outside of the specified range during parameter perturbations. References [16,17] introduce a bi-level interval robust scheduling optimization model that accounts for the unpredictable nature of wind power. This model is utilized to formulate wind power scheduling plans for the next few hours.…”

Section: Introductionmentioning

confidence: 99%

Bi-Level Inverse Robust Optimization Dispatch of Wind Power and Pumped Storage Hydropower Complementary Systems

Jing,

Ji,

Xie

2024

Processes

View full text Add to dashboard Cite

This paper presents a bi-level inverse robust economic dispatch optimization model consisting of wind turbines and pumped storage hydropower (PSH). The inner level model aims to minimize the total generation cost, while the outer level introduces the optimal inverse robust index (OIRI) for wind power output based on the ideal perturbation constraints of the objective function. The OIRI represents the maximum distance by which decision variables in the non-dominated frontier can be perturbed. Compared to traditional methods for quantifying the worst-case sensitivity region using polygons and ellipses, the OIRI can more accurately quantify parameter uncertainty. We integrate the grid multi-objective bacterial colony chemotaxis algorithm and the bisection method to solve the proposed model. The former is adopted to solve the inner level problem, while the latter is used to calculate the OIRI. The proposed approach establishes the relationship between the maximum forecast deviation and the minimum generation cost associated with each non-dominated solution in the optimal load allocation. To demonstrate its economic viability and effectiveness, we simulate the proposed approach using real power system operation data and conduct a comparative analysis.

show abstract

Section: Introductionmentioning

confidence: 99%

Bi-Level Inverse Robust Optimization Dispatch of Wind Power and Pumped Storage Hydropower Complementary Systems

Jing,

Ji,

Xie

2024

Processes

View full text Add to dashboard Cite

show abstract

“…Different energy conversions happen inside the hub and the optimal dispatch algorithms decide the levels of energy conversions. In [10], a nonlinear formulation of the scheduling problem with integrated electricity and district heating systems is discussed. An optimal scheduling algorithm using subsidy strategies is developed in [11], which mainly focuses on obtaining the subsidy signals to control the heating system.…”

Section: Introductionmentioning

confidence: 99%

Co-Optimization of Electrical and District Heating Networks: Bornholm case study

Polisetty,

Joseph,

Turk

et al. 2023

2023 62nd IEEE Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

With the growing energy demands, the interdependence among multiple energy domains is increasing rapidly. The optimal dispatch of the different energy sources, storage systems, and flexible loads in a multienergy system is a challenging problem. This paper focuses on the co-optimization of a multi-energy system consisting of electrical and district heating networks to address the challenge. The electric boilers and heaters act as interconnecting elements between the two systems. Utilizing the available flexibilities in both systems, the cooptimization focuses on energy management to achieve economical operation and reduction in renewable curtailment. The algorithm uses the day-ahead forecast of renewable generation as well as electrical and heating demands to determine the optimal schedule for the various generation, storage, and flexible loads in both systems. A case study based on the multi-energy system at Bornholm Island, Denmark is presented in this paper. The results show a significant reduction in renewable power curtailment and a reduction in CO2 emissions achieved via the interconnected systems.

show abstract

Damping technique empowered robust energy flow calculation for integrated energy systems

Huang

Sun

et al. 2023

Applied Energy

View full text Add to dashboard Cite

Adjustable robust interval economic dispatch of integrated electricity and district heating systems under wind power uncertainty

Cited by 10 publications

References 24 publications

Bi-Level Inverse Robust Optimization Dispatch of Wind Power and Pumped Storage Hydropower Complementary Systems

Bi-Level Inverse Robust Optimization Dispatch of Wind Power and Pumped Storage Hydropower Complementary Systems

Co-Optimization of Electrical and District Heating Networks: Bornholm case study

Damping technique empowered robust energy flow calculation for integrated energy systems

Contact Info

Product

Resources

About