Environmental economic dispatch of integrated regional energy system considering integrated demand response

Abstract To reduce the emissions of greenhouse gases and air pollutants, various low-emission measures have been taken in the power system, which are gradually intensifying the interdependency among different energy systems. Considering the carbon trading scheme and different air pollutant control technologies, this paper proposes an environmental economic dispatch model for the coordinated operation of an integrated regional energy system, which consists of a regional electricity supply network and a natural gas network, along with district energy hubs. Each energy hub contains a combined heat and power unit, a CO2-capture-based power to gas facility, a heat pump, a gas furnace and different energy storage facilities. To achieve an optimized balance between operational cost and emissions during the environmental economic dispatch of this integrated regional energy system, a price-based integrated demand response program is introduced in the energy hub. Then the proposed model is converted into a mixed-integer linear programming problem to find solutions efficiently. Case studies are carried out to demonstrate the effectiveness of proposed environmental economic dispatch model of the integrated regional energy system.

[1]  Abdullah Abusorrah,et al.  Coordination of Interdependent Natural Gas and Electricity Infrastructures for Firming the Variability of Wind Energy in Stochastic Day-Ahead Scheduling , 2015, IEEE Transactions on Sustainable Energy.

[2]  F. Schweppe Spot Pricing of Electricity , 1988 .

[3]  Chongqing Kang,et al.  Review and prospect of integrated demand response in the multi-energy system , 2017 .

[4]  Tao Yu,et al.  Decentralized optimal multi-energy flow of large-scale integrated energy systems in a carbon trading market , 2018 .

[5]  M. Shahidehpour,et al.  Hourly Electricity Demand Response in the Stochastic Day-Ahead Scheduling of Coordinated Electricity and Natural Gas Networks , 2016, IEEE Transactions on Power Systems.

[6]  Jiangfeng Zhang,et al.  Low-carbon economic dispatch for electricity and natural gas systems considering carbon capture systems and power-to-gas , 2018, Applied Energy.

[7]  D. Kirschen Demand-side view of electricity markets , 2003 .

[8]  Mohammad Shahidehpour,et al.  Optimal Stochastic Operation of Integrated Low-Carbon Electric Power, Natural Gas, and Heat Delivery System , 2018, IEEE Transactions on Sustainable Energy.

[9]  Hantao Cui,et al.  Day-ahead coordinated operation of utility-scale electricity and natural gas networks considering demand response based virtual power plants , 2016 .

[10]  Tao Feng,et al.  Robust economic/emission dispatch considering wind power uncertainties and flexible operation of carbon capture and storage , 2014 .

[11]  Carlos M. Correa-Posada,et al.  Integrated Power and Natural Gas Model for Energy Adequacy in Short-Term Operation , 2015, IEEE Transactions on Power Systems.

[12]  Chuangxin Guo,et al.  Linearized Stochastic Scheduling of Interconnected Energy Hubs Considering Integrated Demand Response and Wind Uncertainty , 2018, Energies.

[13]  Frode Rømo,et al.  Optimization Models for the Natural Gas Value Chain , 2007, Geometric Modelling, Numerical Simulation, and Optimization.

[14]  Shahab Bahrami,et al.  From Demand Response in Smart Grid Toward Integrated Demand Response in Smart Energy Hub , 2016, IEEE Transactions on Smart Grid.

[15]  Xue Li,et al.  Stochastic low-carbon scheduling with carbon capture power plants and coupon-based demand response , 2018 .

[16]  Hongbin Sun,et al.  Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty , 2016 .

[17]  Yusheng XUE,et al.  Optimal operation of electricity, natural gas and heat systems considering integrated demand responses and diversified storage devices , 2018 .

[18]  Xu Wang,et al.  Day-Ahead Dispatch of Integrated Electricity and Natural Gas System Considering Reserve Scheduling and Renewable Uncertainties , 2019, IEEE Transactions on Sustainable Energy.

[19]  Mahdi Samadi,et al.  A novel approach to multi energy system operation in response to DR programs; an application to incentive-based and time-based schemes , 2018, Energy.

[20]  Yi Ding,et al.  Economical flexibility options for integrating fluctuating wind energy in power systems: The case of China , 2018, Applied Energy.

[21]  F. Graf,et al.  Renewable Power-to-Gas: A technological and economic review , 2016 .

[22]  Chengzhu Gong,et al.  Multi-agent simulation of the time-of-use pricing policy in an urban natural gas pipeline network: A case study of Zhengzhou , 2013 .

[23]  M. P. Moghaddam,et al.  Demand response modeling considering Interruptible/Curtailable loads and capacity market programs , 2010 .

[24]  Tao Yu,et al.  A convex decentralized optimization for environmental-economic power and gas system considering diversified emission control , 2019, Applied Energy.

[25]  Tao Jiang,et al.  Optimal energy flow and nodal energy pricing in carbon emission-embedded integrated energy systems , 2018, CSEE Journal of Power and Energy Systems.

[26]  Hongbin Sun,et al.  Integrated energy systems , 2016 .

[27]  Zhi-gang Lu,et al.  Low-carbon emission/economic power dispatch using the multi-objective bacterial colony chemotaxis optimization algorithm considering carbon capture power plant , 2013 .

[28]  Shuping Dang,et al.  Unit Commitment Model in Smart Grid Environment Considering Carbon Emissions Trading , 2016, IEEE Transactions on Smart Grid.

[29]  Lei Wu,et al.  Distributionally Robust Scheduling of Integrated Gas-Electricity Systems With Demand Response , 2019, IEEE Transactions on Power Systems.

[30]  Antonio J. Conejo,et al.  Power generation scheduling considering stochastic emission limits , 2018 .

[31]  Jinyu Wen,et al.  Coordinated Regional-District Operation of Integrated Energy Systems for Resilience Enhancement in Natural Disasters , 2019, IEEE Transactions on Smart Grid.

[32]  Xifan Wang,et al.  An MILP-Based Optimal Power Flow in Multicarrier Energy Systems , 2017, IEEE Transactions on Sustainable Energy.

[33]  Chongqing Kang,et al.  Environmental Generation Scheduling Considering Air Pollution Control Technologies and Weather Effects , 2017, IEEE Transactions on Power Systems.

[34]  Chongqing Kang,et al.  Modeling Carbon Emission Flow in Multiple Energy Systems , 2019, IEEE Transactions on Smart Grid.

[35]  Abdeen Mustafa Omer,et al.  Power, people and pollutions , 2008 .