Operation optimization and income distribution model of park integrated energy system with power-to-gas technology and energy storage

Abstract Power-to-gas (P2G) technology is considered as a new approach for clean energy consumption and energy conversion. However, because this technology must be combined with other energy systems to build a stable energy system, a reasonable income distribution method is necessary to guarantee this integration. Firstly, the operation optimization model of the park integrated energy system (PIES) and park independent energy system (PINES) with P2G are constructed for the first stage optimization, with the objective of maximizing net income. Secondly, the energy system performance evaluation indicators are developed to assess the system quantitatively in terms of the economic and environmental aspects. Thereafter, the income distribution models based on Shapley value and the improved Shapley value with operational risk factor are created, and the total income is optimally distributed at the second stage based on the first-stage optimization results. Finally, an industrial park in a province of China is selected for case analysis. The results show that (1) PIES can complement different systems, integrate the demands in heat, electricity, and gas, while realizing the electricity-gas-heat/electricity conversion and heat-electricity complementarity. (2) Income distribution using an improved Shapely value method is proposed, it overcomes the one-sidedness of transaction volume and lack of differences among participants, reflects the actual operational risk and the degree of contribution of participants to the whole system, and promotes the incentives of cooperation. (3) Based on the improved income distribution model, the income of the PS, P2G, and HS are redistributed. The income of P2G increased by ¥7,450, which reflects the important collaborative value of P2G. The willingness of system cooperation increased by 742.392%. Therefore, the proposed operation optimization and income distribution model can enhance the incentives of participants want to cooperate under the premise of ensuring the maximum net income of the PIES. Moreover, it can be used as reference for the formulation of an optimal operation plan and income distribution of the complex energy system and it can provide a way to promote clean energy production.

[1]  Zhongfu Tan,et al.  A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response , 2016 .

[2]  Zixuan Peng,et al.  An Improved Shapley Value Method for a Green Supply Chain Income Distribution Mechanism , 2018, International journal of environmental research and public health.

[3]  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.

[4]  Hongyu Lin,et al.  An Income Distributing Optimization Model for Cooperative Operation among Different Types of Power Sellers Considering Different Scenarios , 2018, Energies.

[5]  Fushuan Wen,et al.  Optimal Dispatch of Electric Vehicles and Wind Power Using Enhanced Particle Swarm Optimization , 2012, IEEE Transactions on Industrial Informatics.

[6]  William D'haeseleer,et al.  Possible role of power-to-gas in future energy systems , 2015, 2015 12th International Conference on the European Energy Market (EEM).

[7]  Matteo C. Romano,et al.  Power-to-gas plants and gas turbines for improved wind energy dispatchability: Energy and economic assessment , 2015 .

[8]  Tapan Kumar Saha,et al.  Benefit-based expansion cost allocation for large scale remote renewable power integration into the Australian grid , 2014 .

[9]  Rui Zhao,et al.  Allocation of carbon emissions among industries/sectors: An emissions intensity reduction constrained approach , 2017 .

[10]  Meng Wang,et al.  Research on project post-evaluation of wind power based on improved ANP and fuzzy comprehensive evaluation model of trapezoid subordinate function improved by interval number , 2019, Renewable Energy.

[11]  Shaojun Li,et al.  On the use of risk-based Shapley values for cost sharing in interplant heat integration programs , 2018 .

[12]  B. Hobbs,et al.  A cooperative game theoretic analysis of incentives for microgrids in regulated electricity markets , 2016 .

[13]  Sadegh Vaez-Zadeh,et al.  Optimal planning of energy hubs in interconnected energy systems: a case study for natural gas and electricity , 2015 .

[14]  Song Yihan,et al.  An Optimization Model Combining Generation Side and Energy Storage System With Demand Side to Promote Accommodation of Wind Power , 2014 .

[15]  Yi Wang,et al.  Logistic-based network stability study of industrial coupling symbiosis applied to oil-gas-based eco-industrial parks , 2019, Journal of Cleaner Production.

[16]  Detlef Stolten,et al.  Power to Gas: Technological Overview, Systems Analysis and Economic Assessment , 2015 .

[17]  Hongbin Sun,et al.  Storage-like devices in load leveling: Complementarity constraints and a new and exact relaxation method , 2015 .

[18]  Denny K. S. Ng,et al.  An optimization-based negotiation framework for energy systems in an eco-industrial park , 2016 .

[19]  Steven A. Lippman,et al.  The asymptotic shapley value for a simple market game , 2009 .

[20]  You-Yin Jing,et al.  Optimization of capacity and operation for CCHP system by genetic algorithm , 2010 .

[21]  Chuntian Cheng,et al.  Coordinated operations of multiple-reservoir cascaded hydropower plants with cooperation benefit allocation , 2018, Energy.

[22]  Jian-xing Ren,et al.  Benefit allocation for distributed energy network participants applying game theory based solutions , 2017 .

[23]  Tan Zhongf.  Joint Delivery System of Large-scale Wind Power and Thermal Power Generation and Its Profit Distribution Model , 2013 .

[24]  Wu Xion,et al.  Economic Generation Scheduling of a Microgrid using Mixed integer programming , 2013 .

[25]  Luis M. Romeo,et al.  Decision-making methodology for managing photovoltaic surplus electricity through Power to Gas: Combined heat and power in urban buildings , 2018, Applied Energy.