A Two-Stage Algorithm of Locational Marginal Price Calculation Subject to Carbon Emission Allowance

To analyze the effect of carbon emission quota allocation on the locational marginal price (LMP) of day-ahead electricity markets, this paper proposes a two-stage algorithm. For the first stage of the algorithm, a multi-objective optimization model is established to simultaneously minimize the total costs and carbon emission costs of power systems. Hence, an evenly distributed Pareto optimal solution can be solved effectively by means of the normalized normal constraint method. For the second stage, a tracing model is built with the goal of minimizing the total costs of power systems and satisfying the constraints generated based on the Pareto optimal solution obtained from the first stage. Furthermore, the influence of carbon emission quota allocation on the LMP of electricity markets is analyzed, and different schemes to allocate carbon emission quotas are evaluated on a real 1560-bus and 52-unit system.

[1]  Fushuan Wen,et al.  An Experimental Study on Emission Trading Behaviors of Generation Companies , 2015, IEEE Transactions on Power Systems.

[2]  Zhao Yang Dong,et al.  Partial Carbon Permits Allocation of Potential Emission Trading Scheme in Australian Electricity Market , 2010, IEEE Transactions on Power Systems.

[3]  Kit Po Wong,et al.  A Multimarket Decision-Making Framework for GENCO Considering Emission Trading Scheme , 2013, IEEE Transactions on Power Systems.

[4]  Jing Qiu,et al.  Carbon-Oriented Operational Planning in Coupled Electricity and Emission Trading Markets , 2020, IEEE Transactions on Power Systems.

[5]  R. Marler,et al.  The weighted sum method for multi-objective optimization: new insights , 2010 .

[6]  Shiwei Yu,et al.  Carbon emission coefficient measurement of the coal-to-power energy chain in China , 2014 .

[7]  Boqiang Lin,et al.  Is emission trading scheme an opportunity for renewable energy in China? A perspective of ETS revenue redistributions , 2020 .

[8]  C. Chung,et al.  Optimal Fuel, Power and Load-Based Emissions Trades for Electric Power Supply Chain Equilibrium , 2012, IEEE Transactions on Power Systems.

[9]  Jinpeng Liu,et al.  Regional carbon emission evolution mechanism and its prediction approach driven by carbon trading – A case study of Beijing , 2018 .

[10]  Jinyu Wen,et al.  Power System Capacity Expansion Under Higher Penetration of Renewables Considering Flexibility Constraints and Low Carbon Policies , 2018, IEEE Transactions on Power Systems.

[11]  Natalia Alguacil,et al.  On the Solution of Revenue- and Network-Constrained Day-Ahead Market Clearing Under Marginal Pricing—Part I: An Exact Bilevel Programming Approach , 2017 .

[12]  Ming-Tse Kuo,et al.  Considering Carbon Emissions in Economic Dispatch Planning for Isolated Power Systems: A Case Study of the Taiwan Power System , 2018, IEEE Transactions on Industry Applications.

[13]  A. Messac,et al.  The normalized normal constraint method for generating the Pareto frontier , 2003 .

[14]  Mingbo Liu,et al.  Piecewise Normalized Normal Constraint Method Applied to Minimization of Voltage Deviation and Active Power Loss in an AC–DC Hybrid Power System , 2015, IEEE Transactions on Power Systems.

[15]  Xianggen Yin,et al.  A Model for Optimizing Spinning Reserve Requirement of Power System Under Low-Carbon Economy , 2014, IEEE Transactions on Sustainable Energy.

[16]  Zhen Yang,et al.  A Bi-Objective Reverse Logistics Network Design Under the Emission Trading Scheme , 2019, IEEE Access.

[17]  Lei Wu,et al.  Impacts of High Penetration Wind Generation and Demand Response on LMPs in Day-Ahead Market , 2014, IEEE Transactions on Smart Grid.

[18]  Gang Ding,et al.  A study on the classification of China’s provincial carbon emissions trading policy instruments: Taking Fujian province as an example , 2019, Energy Reports.

[19]  Yury Dvorkin,et al.  Optimal Carbon Taxes for Emissions Targets in the Electricity Sector , 2018, IEEE Transactions on Power Systems.

[20]  Kunfu Zhu,et al.  Border carbon adjustments for exports of the United States and the European Union: Taking border-crossing frequency into account , 2017 .