In the face of the stochastic, fluctuating, and intermittent nature of the new energy output, which brings significant challenges to the safe and stable operation of the power system, it is proposed to use the ice-storage air-conditioning to participate in the microgrid optimal scheduling to improve wind and light dissipation. This paper constructs an optimal scheduling model for the ice-storage air-conditioning to participate in the microgrid, analyzes the regulation advantages of the ice-storage air-conditioning’s cold storage and cold release process and its participation in the scheduling process; secondly, based on the scenario method, the scenario modeling of the microgrid distributed wind and light output uncertainty and cold load uncertainty is carried out; lastly, an optimal scheduling model is constructed to minimize the operation and maintenance cost of each unit and the storage cost of the ice-storage air-conditioning, the highest rate of clean energy generation and the lowest cost of electricity consumption of the air-conditioning users as the objective function. The example simulations show that the proposed optimal scheduling model can promote the new energy consumption rate of the microgrid, proving that the ice-storage air-conditioning is more economical compared with ordinary air-conditioning and that the operating cost within the optimized microgrid is reduced by about 10.5%. The cost of the air-conditioning users’ electricity consumption has been reduced by about 11.7% after responding to the regulation.

With the evolution of the power market and the increase in the new energy penetration rate, the power industry will present diversified characteristics. The continuous development of the electric energy market (EEM) and the peak regulation market (PRM) is also affecting the economic benefits of cascade hydropower stations, in which the EEM, as a market for electric energy trading in the power market, develops synergistically with the PRM and creates the conditions for the consumption of new energy sources; for this reason, this paper, while considering the benefits of cascade hydropower stations in the EEM in different time scales and the impact of the spot market, combines the compensation mechanism and apportionment principle of the PRM. This paper proposes an optimal economic scheduling strategy for cascade hydropower stations. Specifically, firstly, the strategy adopts multi-objective optimization. The objective function takes into account the generation capacity of the cascade hydropower stations, the benefits of the EEM, the influence of the spot market, the compensatory benefits of peaking, and the sharing expenses of peaking; secondly, the constraints at the level of the power grid, the level of the cascade hydropower stations, and the level of the market are taken into account comprehensively, and the Harris Hawk Algorithm is used to solve the model; lastly, by comparing different schemes, it is observed that under varying inflow conditions, the proposed dispatch strategy in this paper yields slightly lower revenue in the EEM than other schemes. However, due to its comprehensive consideration of the synergy between the PRM and the EEM, its overall economic benefits surpass those of other schemes. This fully validates the effectiveness and economic efficiency of the proposed dispatch strategy.

Under the guidance of the “dual-carbon” target, the utilization of and demand for renewable energy have been growing rapidly. In order to achieve the complementary advantages of renewable energy in virtual power plants with different load characteristics and improve the rate of consumption, an interactive operation strategy for virtual power plants based on asymmetric Nash negotiation is proposed. Firstly, the photovoltaic virtual power plant is proposed to establish the optimal scheduling model for the operation of the virtual power plant, and then the asymmetric Nash negotiation method is adopted to achieve the fair distribution of benefits. Finally, the ADMM distribution is used to solve the proposed model in the solution algorithm. The simulation results show that the revenue enhancement rates are 28.27%, 1.09%, and 12.37%, respectively. The participating subjects’ revenues are effectively enhanced through P2P power sharing. Each subject can obtain a fair distribution of benefits according to the size of its power contribution, which effectively improves the enthusiasm of the PV virtual power plant to participate in P2P interactions and thus promotes the development and consumption of renewable energy.

With high renewable penetration, primary frequency regulation (PFR) in low-inertia power systems faces a critical challenge of balancing frequency security with sustainable energy storage system (ESS) utilization. Existing ESS-based PFR studies mainly focus on single-sided resource support or homogeneous modeling, which cannot address the cross-side coordination demands arising from heterogeneous ESS on the source, grid, and load sides. This paper extends ESS-based PFR to a synergistic scenario involving heterogeneous three-sided ESS. A unified modeling framework is established, explicitly incorporating differences in capacity, functional roles, participation priority, and security boundaries. Based on this, a hierarchical decoupling control structure is proposed, separating system-level frequency regulation from side-level energy coordination. The upper level uses a low-dimensional equivalent representation to reduce the optimization burden from modeling numerous ESS units, while the lower level achieves complementary advantages and orderly task allocation among the three sides through differentiated coordination. Simulations show that the method maintains system frequency performance while achieving rational PFR responsibility allocation across source-, grid-, and load-side ESS, effectively leveraging multi-sided heterogeneous ESS for synergistic regulation, and verifying the hierarchical decoupling framework as an effective approach for coordinating multi-side energy storage.

To address the low-voltage violations that may occur in distribution networks with high penetration of distributed photovoltaic (PV) during sunset and evening peak periods under extreme high-temperature conditions, this paper establishes a source–grid–load electro-thermal coupling model that accounts for load thermal accumulation, transient conductor thermal inertia, temperature-dependent line impedance, and PV thermal derating. Based on a soft safety lower bound and a risk-preference utility function, the probability of voltage violation, violation depth, and expected violation duration are introduced to construct node-level and system-level comprehensive risk factors. The cumulant method combined with the Cornish–Fisher expansion is used to reconstruct the probability distribution of nodal voltages, enabling analytical risk calculation. Simulation results on the IEEE 33-bus system at 45 °C show that the proposed method can quantitatively reflect the temporal variations of nodal voltage distributions, physical violation depth, dimensionless severity utility, and expected violation duration, and identify weak nodes in the later part of the evening peak, providing a reference for risk early warning in distribution networks under extreme heat.