基于PMSC管理及奖惩机制的智能电网实时定价研究

针对用户不断增强的市场价格响应能力，考虑用户电器分类，提出一种惩罚恶意用户和不稳定供电商同时激励非恶意用户的识别机制，并建立社会福利最大化模型研究基于PMSC管理的智能电网实时定价问题。通过对模型进行拉格朗日对偶分解后，最终运用启发式算法求解得到最优电价及电力需求。数值模拟结果表明：求解算法能够快速收敛，且在惩罚和激励双重调节下，电力系统的可靠性和稳定性得到调整和优化，用户效用得以提升；此外，一定范围下激励因子可促使用户效用和社会福利递增。

Real-time Pricing Based on PMSC Management and Reward-Punishment Mechanism in Smart Grid

The emergence of smart grid provides an efficient distribution method for rapidly increasing power demand, the balance of power distribution based on demand response is one of issues keys in smart grid. This article aims at the user’s increasing market price response capacity. The user’s electrical appliance classification is considered, the electrical appliance is divided into the must-use appliances, elastic appliances and semi-elastic appliances, and an improved MIP (Mechanism of Identification and Processing) mechanism is proposed. PMSC (Power Market Scheduling Center) uses the MIP mechanism to screen out malicious users and unstable power suppliers and punish them. By enhancing the penalty mechanism for malicious users and unstable power providers, increasing the cost of providing false data, the number of malicious users and unstable power providers is reduced, while encouraging non-malicious users to prevent them from becoming malicious users, and establishing a model with the goal of maximizing social welfare to study the real-time pricing of smart grid based on PMSC management. Lagrange dual decomposition method is used to construct the Lagrange function of the model, and the decomposition function is used to find the dual problem. Finally, the heuristic algorithm is used to solve the user’s optimal power consumption and the supplier’s optimal load power. The simulation results show that: the solution algorithm can be rapidly converged, and the user’s utility can be improved under the dual adjustment of punishment and incentives; the higher the proportion of malicious users and unstable power providers, the longer it takes for electricity prices to converge, and the longer it takes for user load demands and power providers’ load capacity to stabilize. In addition, the incentive factor can increase users’ utility and social welfare within proper range. By studying the real-time pricing problem in the smart grid environment, the idea of user electrical appliance classification is provided, the malicious user screening mechanism is improved, and the reward and punishment mechanism is fully considered, which provides some methods for improving the reliability and stability of the power system.