Multi-objective Optimization Dispatch for Regional Integrated Power and Heat Energy System Considering Adjustable Heat Load

Yongjie, Zhong; Li, Yuping; Hu, Bing; Wei, Zhang; Chen, Dong; Sun, Yonghui

doi:10.1109/ispec53008.2021.9735669

Cited by 2 publications

(3 citation statements)

References 8 publications

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“…Apart from the maximum injection/retrieval rate of the HWT, it must be ensured that either the charging or discharging of the HWT takes place at any instant. Additional constraints are specified as given by (6). Here, x HW T _out t is a binary variable that equals 1, if extraction from the storage is active, otherwise, the…”

Section: B District Heating Systemmentioning

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)

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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.

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Section: B District Heating Systemmentioning

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

show abstract

“…In [5], it constructed a collaborative planning model which considers electricity storage, gas storage, electricity network topology, gas network topology, and P2G. In [6] to [9], they constructed and studied the system optimization regulation model, which considers the coupling of various energy types of electricity-gas, electricity-heat, and electricity-heat-gas, and aims at economic optimization. In [6], it established optimization models in different load conditions, multi-period, and different operation modes in multiple scenario based on energy hubs.…”

Section: Introductionmentioning

confidence: 99%

“…In [6] to [9], they constructed and studied the system optimization regulation model, which considers the coupling of various energy types of electricity-gas, electricity-heat, and electricity-heat-gas, and aims at economic optimization. In [6], it established optimization models in different load conditions, multi-period, and different operation modes in multiple scenario based on energy hubs. In [7], it further analyzed the complementary characteristics and collaborative optimization potential of each energy subsystem and established an energy flow comprehensive solution model.…”

Section: Introductionmentioning

confidence: 99%

Multi-operating state traction control of the regionally integrated energy system

Chen

Wang

Wan

et al. 2023

J. Phys.: Conf. Ser.

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The regionally integrated energy system consists of multi-type energy production units, energy conversion units, and energy consumption units. This form is of great importance in the area of regenerative energy consumption and multi-type energy optimization. The optimal regulation of the regionally integrated energy system with a high percentage of regenerative energy is the key to the consumption of regenerative energy and the optimal utilization of multi-type energy. The paper presents a method which adopts multi-operating state traction control and considers both system-level and unit-level. Firstly, according to the function of each equipment, the system is classified as various units. Then the state of each unit and the system are determined by the operation data of each unit. The system allocates the unbalanced power regulation task according to the regulation ability of each unit. Finally, each unit completes the traction control according to its control parameters. In the example, the particle swarm optimization computation algorithm is applied to solve the above multi-operating state model. The results indicates that for the regionally integrated energy system, the optimal regulation can achieve the regulation effect of promoting regenerative energy consumption and reducing operation costs.

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Multi-objective Optimization Dispatch for Regional Integrated Power and Heat Energy System Considering Adjustable Heat Load

Cited by 2 publications

References 8 publications

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

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

Multi-operating state traction control of the regionally integrated energy system

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