Monetization mechanisms in gacha games: The behavioral triad of pricing strategies, pity systems, and belief of luck

As multiple energy flows such as cold, heat, and electricity show more in-depth coupling characteristics in multiple dimensions of source, grid, load, and storage, the strategic goals of carbon emission peaking and carbon neutrality and the requirements for building a new-type power system call for advancement of integrated energy system (IES). However, there still exists problems on demand side like lacking highly effective demand response projects to trigger flexible energy interaction. It is urgent to design a friendly interactive mechanism between the power grid and users in IES to alleviate the challenges for flexibility on both supply and demand ends. The proportion of comprehensive energy consumption in the form of park aggregator (PA) in smart cities is increasing year by year. In this context, this article focuses on the interactive optimizing operation scenario of the park-level IES clusters, builds a supply-demand interactive equilibrium model of multiple multi-energy parks based on the multiple multi-energy park aggregative game (MMPAG) and dynamic energy pricing mechanism, and proves the existence and uniqueness of the game solutions. The case studies show that guided by the proposed MMPAG and pricing scheme, multi-energy synergy and efficient interaction are realized and the equilibrium state of supply and demand are achieved among MMPs and energy networks. The model enables each park to optimize individual economy and all the parks to effectively reduce the overall operating cost simultaneously. Besides, the net load at the PA is optimized to remarkably release the transmission burden of the tie line driven by the proposed approach.

Against the backdrop of high investment costs in distributed energy storage systems, this paper proposes a bi-level energy management model based on shared multi-type energy storage to enhance system economics and resource utilization efficiency. First, an electricity–heat–hydrogen coupled shared storage architecture is developed, incorporating hydrogen-blended gas turbines, gas boilers, and hydrogen loads to achieve deep coupling between the power grid and natural gas network. Then, a bi-level game model is formulated with the upper-level objective of minimizing the storage operator’s cost and the lower-level objective of minimizing the cost of the integrated energy microgrid (IEM) aggregator. A cooperative game mechanism is introduced within the microgrids to support peer-to-peer energy trading. Nash bargaining theory is applied to determine benefit allocation and dynamic pricing strategies among microgrids. The model is solved using a genetic algorithm (GA) and the alternating direction method of multipliers (ADMM). Simulation results validate the proposed strategy’s effectiveness and feasibility in reducing system costs, improving overall benefits, and achieving fair benefit allocation.

Construction project bidding is a kind of transaction way of construction project the most widely used ,the bidding is a closed price auction, the game among the bidders and the tenders belongs to a kind of non-cooperation and incomplete static game and so does it among the tenders. According to the special rules of bidding, the game theory is put into construction project bidding ,the game model of bidding mechanism is set up, the game process of a non-cooperation and incomplete information static is analyzed among the tenders according with the different strategies of tendering price, the conclusion can be drawn to be applied to construction project bidding , which can realize ldquothe incentive and compatibility constraintsrdquo and ldquopersonal participating in constraintsrdquo. Meanwhile, the moral hazard and the adverse selection can be avoided. At last, the great degree of equilibrium and the Pareto optimization can be achieved.

With the economic and technological development of the society, the reliability and stability of traditional grid power supply have been faced with more challenges. More attention should be paid to the impact on the environment accordingly. Based on the concept of energy chemistry internet of things (EC-IoT), this paper studies the grid structure and electricity market under the background of renewable energy, and also studies the pricing mechanism of electricity according to game theory. Firstly, the characteristics and basic elements of electricity pricing were analysed deeply and the relevant concept model was established, including power grid environment model, electricity market model and power generation model. Then, in view of the characteristics of the electricity pricing problem in the EC-IoT, one power system model was established. Finally, based on the Bayesian Nash equilibrium (BNE) game, the electricity pricing strategy was proposed, by systematically introducing the process of game pricing and the solution to the equilibrium of the electricity price game.