Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty

Bai, Linquan; Li, Fangxing; Cui, Hantao; Jiang, Tao; Sun, Hongbin; Zhu, Jinxiang

doi:10.1016/j.apenergy.2015.10.119

Cited by 359 publications

(165 citation statements)

References 26 publications

Supporting

Mentioning

164

Contrasting

Unclassified

Order By: Relevance

“…The dispatch problem of an IES studied in this paper conducts in 1-hour interval [10][11][12]25]. In order to compromise the competing benefits of the electricity network, gas network, and distributed DHCs, the power trade-offs among them are investigated in detail by means of optimizing the selected objectives simultaneously.…”

Section: Integrated Energy System Modeling 21 System Descriptionmentioning

confidence: 99%

“…The gas flow from node m to node n through the compressor j, f mn , is mathematically expressed as [11]:…”

Section: Constraintsmentioning

confidence: 99%

“…The objective of the upper-level problem is to minimize the operating cost of electricity network while the scheduling optimization problem of gas network is embedded within the lower-level problem. In [11], an interval optimization based operating strategy for gaselectricity integrated energy systems was proposed considering demand response and wind uncertainty. In most of the previous research, only the gas-fired generator has been considered as the linkage between the electricity network and gas network.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Many-objective optimization for coordinated operation of integrated electricity and gas network

Kou

Zheng

2017

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

This paper develops a many-objective optimization model, which contains objectives representing the interests of the electricity and gas networks, as well as the distributed district heating and cooling units, to coordinate the benefits of all parties participated in the integrated energy system (IES). In order to solve the many-objective optimization model efficiently, an improved objective reduction (IOR) approach is proposed, aiming at acquiring the smallest set of objectives. The IOR approach utilizes the Spearman's rank correlation coefficient to measure the relationship between objectives based on the Pareto-optimal front captured by the multi-objective group search optimizer with adaptive covariance and Lévy flights algorithm, and adopts various strategies to reduce the number of objectives gradually. Simulation studies are conducted on an IES consisting of a modified IEEE 30-bus electricity network and a 15-node gas network. The results show that the many-objective optimization problem is transformed into a bi-objective formulation by the IOR. Furthermore, our approach improves the overall quality of dispatch solutions and alleviates the decision making burden.

show abstract

Section: Integrated Energy System Modeling 21 System Descriptionmentioning

confidence: 99%

“…The gas flow from node m to node n through the compressor j, f mn , is mathematically expressed as [11]:…”

Section: Constraintsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Many-objective optimization for coordinated operation of integrated electricity and gas network

Kou

Zheng

2017

J. Mod. Power Syst. Clean Energy

View full text Add to dashboard Cite

show abstract

“…A stochastic-programming-based coordinative scheduling tool is presented in [16], in which wind power is described by scenarios. The model can also be formulated as interval [17] or robust optimization problems [18] by modeling the uncertainty using intervals or sets. Moreover, reference [19] shows that a strategic bidding strategy of GFUs can also be beneficial within the current market framework.…”

Section: Introduction Ccording To the Energy Information Administrmentioning

confidence: 99%

Clearing and Pricing for Coordinated Gas and Electricity Day-Ahead Markets Considering Wind Power Uncertainty

Chen

Wang

Sun

2018

IEEE Trans. Power Syst.

Self Cite

View full text Add to dashboard Cite

Abstract-Natural gas and electricity systems are becoming increasingly strongly coupled. Gas-fired units (GFUs) are replacing retired coal plants, and the power systems are more dependent on the flexibilities provided by GFUs. The GFUs' power generation capability relies on the availability of gas resources, which is jointly determined by the capacity of gas suppliers and pipeline networks. However, the gas and electricity markets are operated separately. Consequently, the GFUs are forced to "represent" the entire power system to bid on the gas market: they must make forecasts regarding future gas consumption and bear the risk of improper contracts or being unable to meet generation schedules due to occasional insufficient gas supply. When facing larger shares of renewable energies and more-frequent gas network congestions, the current market framework is particularly unreliable and inefficient, as well as economically unfriendly to the investors of the GFU assets. In this paper, we try to develop a framework that can combine the two markets. By properly pricing the scarce resources, e.g., gas transmission capacity, the joint market can help allocate the resources more efficiently while satisfying the demands. Moreover, a more forward-looking day-ahead market clearing framework is presented by considering the uncertainty brought by renewable energies. The formulation and algorithm of the proposed joint market model will be presented, as are some case studies.Index Terms-day-ahead market, gas and electricity coordination, wind power, unit commitment, stochastic programming. 1

show abstract

“…They concluded that the former requires a longer solution time but yields more robust results. Bai et al [39] applied interval optimization for optimization of gas-electricity integrated energy systems networks. They considered demand response and wind Please cite this publication at: Mahdi Sharifzadeh, Helena Lubiano-Walochik, Nilay Shah.…”

mentioning

confidence: 99%

Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies

Sharifzadeh

Lubiano-Walochik

Shah

2017

Renewable and Sustainable Energy Reviews

View full text Add to dashboard Cite

Renewable energies can play an important role in mitigating the emissions associated with electricity power generation and diversification of the energy supply. The challenge is that renewable resources such as wind and solar have intermittent production patterns and their incorporation into conventional electricity grids will increase the degree of uncertainty. The present research proposes a comprehensive framework in which design and operation of the electricity grid are considered simultaneously and the uncertainties in the wind and solar generation as well as demand are systematically taken into account. The case of retrofitting the current UK electricity grid to include 50% renewable power generation by 2030 was posed as the demonstrating example. The research problem was formulated as a piece-wise linear mixed integer optimization under uncertainty and solved using CPLEX v12.0 in GAMS. The results suggested that it is possible to retrofit the electricity grid using renewable generators while optimizing the overall profitability and ensuring the secure supply of electricity. It was also observed that at the price of higher computational costs, stochastic optimization generates more realistic and robust solutions for the design and operation of the smart electricity grid. KeywordsIntegrated renewable energy systems, wind power, solar energy, stochastic mixed-integer optimization, uncertainty. , , ( ) Power generated by i natural gas power plant in scenario s at node n at time t , , ( ) Power generated by k nuclear power plant in scenario s at node n at time t , ( ) Wind power generated in scenario s at node n at time t , ( ) Solar power generated in scenario s at node n at time t , ( ) Power pumped from storage to node n in scenario s at time t , ( ) Power pumped to storage from node n in scenario s at time t cite this publication at: Mahdi Sharifzadeh, Helena Lubiano-Walochik, Nilay Shah. Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and

show abstract

Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty

Cited by 359 publications

References 26 publications

Many-objective optimization for coordinated operation of integrated electricity and gas network

Many-objective optimization for coordinated operation of integrated electricity and gas network

Clearing and Pricing for Coordinated Gas and Electricity Day-Ahead Markets Considering Wind Power Uncertainty

Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies

Contact Info

Product

Resources

About