A Multi-objective Scheduling Optimization Model for Hybrid Energy System Connected with Wind-Photovoltaic-Conventional Gas Turbines, CHP Considering Heating Storage Mechanism

Yao Wang, Yan Lu, Liwei Ju, Ting Wang, Qingkun Tan, Jiawei Wang and Zhongfu Tan
Additional contact information
Yao Wang: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Yan Lu: State Grid Jibei Electric Economic Research Institute, Beijing 100095, China
Liwei Ju: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Ting Wang: Department of Power Engineering, Shanxi University, Taiyuan 030000, China
Qingkun Tan: School of Economics and Management, North China Electric Power University, Beijing 102206, China
Jiawei Wang: Economic and Electrical Research Institute of Shanxi Electrical Power Company of SGCC, Taiyuan 030002, China
Zhongfu Tan: School of Economics and Management, North China Electric Power University, Beijing 102206, China

Energies, 2019, vol. 12, issue 3, 1-28

Abstract: In order to meet the user’s electricity demand and make full use of distributed energy, a hybrid energy system (HES) was proposed and designed, including wind turbines (WTs), photovoltaic (PV) power generation, conventional gas turbines (CGTs), incentive-based demand response (IBDR), combined heat and power (CHP) and regenerative electric (RE) boilers. Then, the collaborative operation problem of HES is discussed. First, the paper describes the HES’ basic structure and presents the output model of power sources and heating sources. Next, the maximum operating income and minimum load fluctuation are taken as the objective function, and a multi-objective model of HES scheduling is proposed. Then an algorithm for solving the model is proposed that comprises two steps: processing the objective functions and constraints into linear equations and determining the optimal weight of the objective functions. The selected simulation system is a microgrid located on an eastern island of China to comparatively analyze the influence of RE-heating storage (RE-HS) and price-based demand response (PBDR) on HES operation in relation to four cases. By analyzing the results, the following three conclusions are drawn: (1) HES can comprehensively utilize a variety of distributed energy sources to meet load demand. In particular, RE technology can convert the abandoned energy of WT and PV into heat during the valley load time, to meet the load demand combined with CHP; (2) The proposed multi-objective scheduling model of HES operation not only considers the maximum operating income but also considers the minimum load fluctuation, thus achieving the optimal balancing operation; (3) RE-HS and PBDR have a synergistic optimization effect, and when RE-HS and PBDR are both applied, an HES can achieve optimal operation results. Overall, the proposed decision method is highly effective and applicable, and decision makers could utilize this method to design an optimal HES operation strategy according to their own actual conditions.

Keywords: hybrid energy system; multi-objective model; heating storage; optimization scheduling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/3/425/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/3/425/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:3:p:425-:d:201753

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().