Capacity Planning of Micro Energy Grid Using Double-Level Game Model of Environment-Economic Considering Dynamic Energy Pricing Strategy

• Main Authors: Lin Lin, Jiaruiqi Bao, Jian Zheng, Guilin Huang, Jiping Du, Nantian Huang
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Micro energy grid; dynamic energy pricing; environment-economic planning; game theory; dynamic pricing
• Online Access: https://ieeexplore.ieee.org/document/9106354/

Multi-energy unified planning is difficult because of the complex conflicting relationship between the coupling and complementary interaction of multiple forms of energy in micro energy grids (MEGs). Conflicting relationships between the economy and the environment as well as the impact of uncertain energy prices must be considered during MEG planning. To address these problems, this paper proposes a two-level game with an environment-economic planning model that considers dynamic energy pricing strategies. This model consists of an upper environment-economic planning level based on a multi-strategy evolution game considering players' bounded rationality and a lower dynamic energy pricing level, including the MEG operator-user leader-follower Stackelberg game. Simultaneously, based on the energy hub theory, a multi energy coupling matrix is established for a MEG and includes electricity, gas, heat, and cooling. The evolutionary stability strategy (ESS) of the planning results is analyzed using the replicator dynamic equation of the evolutionary game, and the existence of the Nash equilibrium is proven for the dynamic energy pricing of Stackelberg games. Finally, the effectiveness of the proposed environment-economic planning two-level game model considering dynamic energy pricing strategies is verified using simulations. Because dynamic energy pricing and the environment-economic planning are considered, the number of energy equipment required during peak hours is reasonably reduced, thereby reducing the total planning cost and improving the energy utilization efficiency. Simultaneously, greenhouse gas (CO2) and air pollutant (NOx) emissions are reduced to decrease environmental impact.