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Research On Optimal Operation Of Regional Integrated Energy Systems

Posted on:2020-08-17Degree:MasterType:Thesis
Country:ChinaCandidate:H SongFull Text:PDF
GTID:2392330623460103Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
In the context of the Energy Internet,integrated energy systems undertake the role of a physical carrier and is recognized as a future-oriented energy system.Developing regional integrated energy system(RIES)is the key to utilizing renewable energy on a large scale,improving overall energy efficiency,and achieving sustainable development of energy utilization.RIES is an integrated coordination and optimization of diversified energy subsystems such as electricity,gas,cooling/heating,and hydrogen.It complements multiple energy advantages and meet the diversified energy needs of end users.The optimal operation problem has fundamental implications for studying other issues in RIES.Addressing the current lack of research on power-to-gas(P2G)process and uncertainties in RIES optimal operation problem,research work of this paper is carried out as follows:(1)Establish the typical physical framework of RIES and build mathematical models of wind turbine,combined heat and power(CHP)unit,energy storage equipment,auxiliary equipment and P2 G equipment.The concept of energy hub(EH)is introduced to facilitate the analysis of the coupling relationship between multi-energy flows in subsequent chapters.In this paper,the CHP unit adopts a thermo-electric coupling convex operating domain model which can better reflect the internal operation constraints of CHP unit.P2 G process is viewed as an effective way to utilize surplus wind power generation and increase system economic benefits.After analyzing the characteristics and benefits of different P2 G utilization methods,a twostage combined hydrogen and methane production P2 G model is proposed according to actual features of the RIES studied in this paper.Hydrogen produced via P2 G process is to supply hydrogen fuel cell vehicle,which is economically and environmentally advantageous.(2)A RIES day-ahead economic scheduling model involving P2 G process,wind power generation and various loads(electricity,heat,gas,hydrogen)is proposed.The objective function consists of the power purchase fee,gas purchase fee and wind abandonment cost.Model constraints are built based on the energy hub theory and related unit models.Carried out in 4 scenarios,the case study shows that the proposed two-stage combined hydrogen and methane production P2 G model has obvious effects on reducing the wind abandonment and improving the economic efficiency of the RIES.Differences in unit commitment of the RIES devices when the loads have different thermo-electric ratios are also discussed.Compared with existing related research,this paper innovatively combines the adjustable thermo-electric operation mechanism of the CHP unit with P2 G technology.The case study also reveals that RIES can coordinate multiple energy subsystems,and thus operate flexibly in an optimal way.(3)A two-stage robust optimization model for RIES day-ahead scheduling problem with uncertainties is proposed.Current research on the uncertainty of RIES operation majorly discuss the randomness of renewable energy,but the uncertainty of multiple energy-carrier loads lacks investigation.The uncertainties considered in this paper include the predicted power of wind generation and various loads(electricity,heat,gas,hydrogen).The cardinal uncertainty set is employed to describe their uncertainties.Sub-problem of the proposed two-stage robust model is transformed by dual theory,and then solved by the C&CG algorithm.The case study shows that the proposed robust optimization selects a more conservative operation schedule to cope with uncertainties;the robust optimization result is more economical than the worst case in deterministic optimization;selecting reasonable budgets of uncertainty can coordinate the robustness and economic benefits of RIES operation.
Keywords/Search Tags:RIES, combined heat and power, power-to-gas, optimal operation, robust optimization
PDF Full Text Request
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