ExtensiveCO2recycling in power systems via Power-to-Gas and network storage

Abstract The recycling of carbon dioxide ( CO 2 ) into synthetic fuels via Power-to-Gas (PtG) could represent an important instrument for achieving the complete decarbonization of the energy sector. To address such issue, this paper calculates the investments in PtG units, grid reinforcements and renewable installations that allow the almost complete recycling of the CO 2 emissions of a countrywide electric power system. Furthermore, this work evaluates the feasibility of gas and electric operations in the new system configuration. The analysis is enabled by coupled gas and electric network modelling. The necessary PtG station installations and overhead line reinforcements are identified via scenario-based cost optimization. Hourly operations of electric power plants are scheduled as a sequence of day-head security-constrained unit commitment problems. A transient gas flow model assesses the capability of the gas network to act as short- and long-term storage of synthetic gas. The developed framework is applied to the electric and gas transmission networks of Great Britain, whose investments and operations are investigated for increasing renewable capacity levels based on the 2030 Gone Green case. Results show that almost complete CO 2 recycling is achieved if the installed renewable capacity is approximately three times as large as the 2030 Gone Green estimates. The investments comprise 114 GW of PtG capacity and the construction of 23 electric parallel lines. Remarkably, gas network operations do not represent a limit to the storage of large amount of synthetic methane. Moreover, PtG stations are preferentially installed at locations with large RES capacity and foster large renewable penetration; only small curtailments occur even for large renewable capacity levels. These results support decision makers by quantifying the techno-economic implications of the presented extensive CO 2 recycling strategy.

[1]  Goran Strbac,et al.  Multi-time period combined gas and electricity network optimisation , 2008 .

[2]  Zimčík Jakub Power to Gas , 2017 .

[3]  Michael Sterner,et al.  Erneuerbares Methan: Analyse der CO2-Potenziale für Power-to-Gas Anlagen in Deutschland , 2012 .

[4]  Michael Chertkov,et al.  Cascading of Fluctuations in Interdependent Energy Infrastructures: Gas-Grid Coupling , 2014, ArXiv.

[5]  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.

[6]  Pierluigi Mancarella,et al.  Storing renewables in the gas network: modelling of power-to-gas seasonal storage flexibility in low-carbon power systems , 2016 .

[7]  M. Jentsch,et al.  Optimal Use of Power-to-Gas Energy Storage Systems in an 85% Renewable Energy Scenario , 2014 .

[8]  Goran Strbac,et al.  Efficacy of options to address balancing challenges: Integrated gas and electricity perspectives , 2017 .

[9]  Jianzhong Wu,et al.  Role of power-to-gas in an integrated gas and electricity system in Great Britain , 2015 .

[10]  Yuxuan Wang,et al.  Life cycle assessment of CO2 emissions from wind power plants: Methodology and case studies , 2012 .

[11]  Edward S. Rubin,et al.  On the climate change mitigation potential of CO2 conversion to fuels , 2017 .

[12]  Reinerus Benders,et al.  The application of power-to-gas, pumped hydro storage and compressed air energy storage in an electricity system at different wind power penetration levels , 2014 .

[13]  Lion Hirth,et al.  Carpe diem: A novel approach to select representative days for long-term power system modeling , 2016 .

[14]  Nilay Shah,et al.  The role of CO 2 capture and utilization in mitigating climate change , 2017 .

[15]  Jianzhong Wu,et al.  A sequential Monte Carlo model of the combined GB gas and electricity network , 2013 .

[16]  David M. Wall,et al.  The potential of power to gas to provide green gas utilising existing CO2 sources from industries, distilleries and wastewater treatment facilities , 2017 .

[17]  Zhinong WEI,et al.  Multi-period integrated natural gas and electric power system probabilistic optimal power flow incorporating power-to-gas units , 2017 .

[18]  Jianzhong Wu,et al.  Operating Strategies for a GB Integrated Gas and Electricity Network Considering the Uncertainty in Wind Power Forecasts , 2014, IEEE Transactions on Sustainable Energy.

[19]  Pierluigi Mancarella,et al.  Integrated electrical and gas network flexibility assessment in low-carbon multi-energy systems , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[20]  Michael I. Jordan,et al.  On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.

[21]  Jianzhong Wu,et al.  Impact of a large penetration of wind generation on the GB gas network , 2010 .

[22]  M. Shahidehpour,et al.  Allocation of Hourly Reserve Versus Demand Response for Security-Constrained Scheduling of Stochastic Wind Energy , 2013, IEEE Transactions on Sustainable Energy.

[23]  Russell Bent,et al.  Efficient dynamic compressor optimization in natural gas transmission systems , 2016, 2016 American Control Conference (ACC).

[24]  Andrea Antenucci,et al.  Adequacy and security analysis of interdependent electric and gas networks , 2017 .

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

[26]  R. Rudervall,et al.  High Voltage Direct Current ( HVDC ) Transmission Systems Technology Review Paper , 2000 .

[27]  Michael Chertkov,et al.  Coordinated Scheduling for Interdependent Electric Power and Natural Gas Infrastructures , 2017 .

[28]  Pierluigi Mancarella,et al.  Integrated Modeling and Assessment of the Operational Impact of Power-to-Gas (P2G) on Electrical and Gas Transmission Networks , 2015, IEEE Transactions on Sustainable Energy.

[29]  M Granger Morgan,et al.  Opinion: Climate policy needs more than muddling , 2016, Proceedings of the National Academy of Sciences.

[30]  Johannes Lindorfer,et al.  Evaluating CO2 sources for power-to-gas applications – A case study for Austria , 2015 .

[31]  P. Van Hentenryck,et al.  Joint Electricity and Natural Gas Transmission Planning With Endogenous Market Feedbacks , 2018, IEEE Transactions on Power Systems.

[32]  Giovanni Sansavini,et al.  Gas-Constrained Secure Reserve Allocation With Large Renewable Penetration , 2018, IEEE Transactions on Sustainable Energy.

[33]  Marc Goetschalckx,et al.  A stochastic programming approach for supply chain network design under uncertainty , 2004, Eur. J. Oper. Res..

[34]  Mohammad Shahidehpour,et al.  Day-Ahead Self-Scheduling of a Transmission-Constrained GenCo With Variable Generation Units Using the Incomplete Market Information , 2017, IEEE Transactions on Sustainable Energy.

[35]  Kosuke Kurokawa,et al.  Life-cycle analyses of very-large scale PV systems using six types of PV modules , 2010 .

[36]  William D'haeseleer,et al.  Effects of large-scale power to gas conversion on the power, gas and carbon sectors and their interactions , 2015 .

[37]  K. Lackner,et al.  Sustainable hydrocarbon fuels by recycling CO2 and H2O with renewable or nuclear energy , 2011 .

[38]  Andrea Lanzini,et al.  Greening the gas network - The need for modelling the distributed injection of alternative fuels , 2017 .

[39]  Jianzhong Wu,et al.  Benefits of demand-side response in combined gas and electricity networks , 2017 .

[40]  K. D. Vos Negative Wholesale Electricity Prices in the German, French and Belgian Day-Ahead, Intra-Day and Real-Time Markets , 2015 .

[41]  J. F. Benders Partitioning procedures for solving mixed-variables programming problems , 1962 .

[42]  André Faaij,et al.  A review at the role of storage in energy systems with a focus on Power to Gas and long-term storage , 2018 .

[43]  J. Kralik,et al.  Dynamic modeling of large-scale networks with application to gas distribution , 1988 .

[44]  Christian Breyer,et al.  North-East Asian Super Grid for 100% renewable energy supply: Optimal mix of energy technologies for electricity, gas and heat supply options , 2016 .

[45]  E. Rubin,et al.  The cost of CO2 capture and storage , 2015 .

[46]  Mohammad Shahidehpour,et al.  Robust Co-Optimization Scheduling of Electricity and Natural Gas Systems via ADMM , 2017, IEEE Transactions on Sustainable Energy.

[47]  Chongqing Kang,et al.  Effect of Natural Gas Flow Dynamics in Robust Generation Scheduling Under Wind Uncertainty , 2018, IEEE Transactions on Power Systems.