The change of customer behaviors and the fluctuation of spot prices can affect the benefits of electricity retailers. To address this issue, an incentive-based demand response (DR) model involving the utility and elasticity of customers is proposed for maximizing the benefits of retailers. The benefits will increase by triggering an incentive price to influence customer behaviors to change their demand consumptions. The optimal reduction of customers is obtained by their own profit optimization model with a certain incentive price. Then, the sensitivity of incentive price on retailers’ benefits is analyzed and the optimal incentive price is obtained according to the DR model. The case study verifies the effectiveness of the proposed model.

Due to the international circumstances changes and domestic economic restructuring, the policies and planning of energy development have been adjusting in recent years, especially in energy power industry. Under these influences, the Chinese energy development goal "non-fossil energy accounts for 15% of the primary energy consumption" which planned to be realized in 2020 becomes uncertain. To ensure the goal can be achieved, a new energy power planning scheme is provided. Based on this planning scheme, the sensitivity analysis method and the maximum deviation method are proposed to quantify the influence of planning deviation on the target percentage. At the same time, the energy replacement is provided to fill the deviation. Research results shows that the main influence factors of target percentage is the hydro and nuclear power develop scale and their output channel construction. If the hydro and nuclear power capacity can't reach their target scale, wind and solar power capacity can fill the vacancy instead. But if the vacancy of hydropower exceeds 58GW, or vacancy of nuclear power exceeds 27GW, the "15% goal" would be very difficult to achieve. Accelerating the construction of the hydropower output transmission lines helps to guarantee the "15% goal".

With respect to the current campus energy systems, the research on energy storage deployment has focused mostly on single users or a single metric, making it difficult to accommodate diverse multiuser needs while efficiently utilizing the available resources. This results in narrow evaluation dimensions and underutilized storage assets. To address this issue, an integrated method for multiuser energy storage, optimal sizing and leasing is proposed in this paper; the method is aimed at improving the economics and utilization of storage. First, we construct a campus energy system architecture that includes an energy storage service provider and develop a storage sizing model that minimizes the average daily total cost, yielding the optimal power ratings and capacities for different users. Second, we construct a comprehensive evaluation framework from both economic and technical perspectives and apply quantitative methods to select the best configuration scheme. On this basis, we propose a multicriteria optimization-based storage leasing mechanism that enables resource sharing among users and maximizes the revenue received by the service provider. Simulation results reveal that across five typical user scenarios, the proposed method outperforms the traditional single-configuration models: the overall storage utilization rate increases by 3.84%, the cost-reduction rates for some users exceed 16%, and the investment payback period decreases by approximately one year. Compared with configuration-only approaches, the proposed integrated configuration–leasing framework simultaneously enhances user-side economics and the profitability of the service provider. The integrated sizing and leasing method not only demonstrates solid economic and technical feasibility but is also applicable to multiuser campuses, shared storage cases, and cloud storage scenarios, providing a reference path for future multidimensional value extraction processes and commercial operations.

To address low-frequency oscillations in islanded residual-pressure power generation systems caused by water-hammer dynamics and low inertia, this paper proposes a supplementary damping control strategy for the DC-voltage outer loop of a voltage-source converter (VSC), using generator-speed deviation as feedback. First, an electromechanical control model is established, and its oscillatory characteristics are examined using root-locus and frequency-domain analyses. Then, with the supplementary controller disabled, a small-step signal is applied in PSCAD. TLS-ESPRIT is used to identify an equivalent second-order model between the supplementary control signal and generator electromagnetic power, and an independent small-step record is used for validation. Damping-torque theory is subsequently employed to determine the required phase compensation. A constrained particle swarm search is used to audit controller settings against frequency- and DC-voltage-related criteria, while nonlinear verification determines whether the candidate parameters should be adopted. The implemented controller comprises a low-pass filter, a washout stage, and a single-stage lead–lag network. In a unified three-level load check, the controller maintains stable operation for the added loads of 80 and 160 kW, whereas the 240 kW case went out of the normal operating range. In a separate reduced-order hydraulic-lag sensitivity test at 160 kW, the controller maintains bounded responses when T_h2 is varied from 0.36 to 0.54 s. A matched benchmark against a conventional uncompensated supplementary branch shows that the proposed phase-compensated controller reduces frequency ITAE by 18.9% and limiter residence by 22.4% relative to the selected conventional case, although its DC-voltage ITAE is 67.4% higher. The results therefore support a frequency-recovery benefit within the tested range rather than a universal performance superiority.

Traditional symmetric voltage multiplier-based structures offer low current stress and high scalability. However, the equalization current flowing into each energy storage cell must overcome four diode voltage drops per switching cycle, significantly degrading energy transfer efficiency. A compact integrated equalizer based on multi-stacked buck-boost converters for large-scale energy storage systems is proposed. By replacing diodes with inductors, the design achieves high-efficiency cell balancing even at low cell voltages. The integrated design leverages the boost circuit’s inherent current ripple for driving the balancing system, eliminating extra switches and minimizing size and cost. Additionally, it provides independent balancing channels for each cell, eliminating equalization current superposition. This reduces cell current stress while enabling large-scale system balancing. Experimental validation on an eight-cell setup demonstrated successful balancing with 87.5% system efficiency.