###### Abstract  
With the opening of the Chinese electricity market, as a retailer that provides energy services to consumers, the park-integrated energy system (PIES) not only serves as an effective way to earn benefits and reduce carbon emissions but also impacts the energy consumption characteristics of consumers. The PIES implements this function by adjusting the energy selling price in free energy markets. The pricing mechanism model (P-M model) is established to obtain the energy selling price in the planning and design stages. In this model, the impact of the demand response on the energy configuration and the impact of the changes in energy configuration on the energy cost price are both considered. Additionally, the optimal result ensures that both the consumers and the PIES benefit simultaneously. The reactive demand response zone, which represents a consumer trap, is found in numerical studies. The results indicate the following: (1) from the perspective of P-M model optimization, the benefit exclusive point of the PIES is the optimal solution in the short term; (2) from the perspective of the long-term benefit, the ultimate result in the relationship between the PIES and consumers is that the PIES will share its profits with consumers; in other words, benefit sharing point is the optimal solution for the long term. park integrated energy system; pricing mechanism model; transfer ratio; planning and design; demand side +
Footnote †: journal: Applied  
First, ESS is mainly used to transfer electrical or cooling or heating load for large industrial consumers, civil buildings, and power grids. The main tasks involved in employing ESS include the optimization of operation strategies, capacity determination, economic analysis, and renewable energy consumption. ESS is also used to reconstruct the output curve of island grids [5] or distributed microgrids [6] with high renewable energy penetration. In [7], the BESS (battery energy storage system) is used to reduce the electricity production cost by decreasing the peak load. However, [8] indicates that no BESS is economical without subsides, based on the current battery price. In addition, cooling and heating ESS are usually applied to adjust the electricity demand of consumers by reducing the electrical consumption of cooling and heating during the peak hours [9]. Second, as the EV battery remains idle during much of the day, EV can release the remaining power to the grid during the peak load hours and absorb the surplus electricity from the grid during the valley load hours [10]. Nonetheless, the implementation of this mode is still difficult under current technical conditions, because it is available when the EV is only parked in certain areas. Third, DR is mainly used to encourage consumers to adjust their power demand through the real-time electricity price, time-of-use electricity price, incentives, and penalties, in order to achieve load leveling [11]. Limitedly, DR can only adjust the controllable load but not the uncontrollable load. All three strategies can yield positive results of peak demand transfer, which involve reducing the power generation costs of energy producers (e.g., large coal-fired power plants, large-scale renewable energy plants), postponing the system update time of the T&D (transmission and distribution) grid, increasing the economic efficiency of the energy retailer, and reducing the electricity bills of consumers. In practice, the peak load can be satisfied by installing ESS without increasing the installed capacity of generation equipment on the supply side. On the demand side, the three strategies are used to reduce the peak energy demand or smooth the load curve. There are usually several ways to promote the effective implementation of the above three strategies on the demand side: namely, using time-of-use pricing, real-time electricity plans, incentive schemes, and event-driven programs. In previous studies, the methods of electricity pricing mainly included game theory pricing and bilevel approaches.