Hantao Cui

Distribution network reconfiguration with aggregated electric vehicle charging strategy

With a higher level of electric vehicle load penetrated in the distribution network, reconfiguration could be employed to minimize energy losses. Based on a second-order conic programming formulation, an improved set of network radiality constraints is proposed using power-flow based network connectivity conditions. This proves to be a computationally more efficient method compared to the spanning tree constraints. To incorporate electric vehicle charging in the reconfiguration model, two aggregated charging strategies are proposed: the arbitrary delay and the peak-avoiding delay. The decision of delay hours is formulated as constraints and co-optimized into the reconfiguration model. Case study on the IEEE 33-bus system illustrates the performance of the proposed model and the effectiveness of the proposed charging strategy.

Application of battery-supercapacitor energy storage system for smoothing wind power output: An optimal coordinated control strategy

In the application of energy storage for smoothing wind power output, the combination of battery and supercapacitor (SC) is considered as an effective alternative to improve the battery lifetime and enhance the system economy. In this paper, third-order Butterworth low-pass filter and high-pass filter are adopted to smooth the wind power and allocate power between battery and SC. Then, an optimal coordinated control strategy is proposed to determine the cut-off frequencies of the two filters and the power sharing between battery and SC. With this strategy, the total deprecation cost of the system caused by charge/discharge is minimized while satisfying the requirements of wind power integration. Finally, the effectiveness of the proposed method is demonstrated with a simulation study.

Bilevel Arbitrage Potential Evaluation for Grid-Scale Energy Storage Considering Wind Power and LMP Smoothing Effect

This paper deals with extended-term energy storage (ES) arbitrage problems to maximize the annual revenue in deregulated power systems with high-penetration wind power. The conventional ES arbitrage model takes the locational marginal prices (LMP) as an input and is unable to account for the impacts of ES operations on system LMPs. This paper proposes a bilevel ES arbitrage model, where the upper level maximizes the ES arbitrage revenue and the lower level simulates the market clearing process considering wind power and ES. The bilevel model is formulated as a mathematical program with equilibrium constraints) and then recast into a mixed-integer linear programming using strong duality theory. Wind power fluctuations are characterized by the GARCH forecast model and the forecast error is modeled by forecast-bin-based Beta distributions. Case studies are performed on a modified PJM 5-bus system and an IEEE 118-bus system with a weekly time horizon over an annual term to show the validity of the proposed bilevel model. The results from the conventional model and the bilevel model are compared under different ES power and energy ratings, and also various load and wind penetration levels.

Mitigate overestimation of voltage stability margin by coupled single-port circuit models

Wide-area measurement-based voltage stability assessment (VSA) by coupled single-port circuit models has been widely discussed recently. This method models the coupling effects of load buses within a meshed network into extra impedance of a single-port model for each load bus. In simulation studies, overestimations of voltage stability margin using this approach have been observed when critical load bus or buses are decoupled from other load buses. In this paper, the overestimations are reported for the first time through examples and are further analyzed in details. Moreover, to mitigate such overestimations, two methods are proposed: one method uses a mitigation factor based on actual system reactive power response; the other method changes the types of certain weak generation buses when forming the coupled impedance. Both approaches are applied to a sample 4-bus system as well as the IEEE 118-bus system and successfully mitigate the overestimations.

Probabilistic Load Flow Analysis Using Randomized Quasi–Monte Carlo Sampling and Johnson Transformation

AbstractAs the fastest growing type of renewable generation, wind power integration has been widely studied to address both the environmental and the energy concerns. The intermittent and stochasti...

Security-Based Active Demand Response Strategy Considering Uncertainties in Power Systems

In modern power systems, the stochastic and interactive characteristics of mixed generations have gained increasing interest, especially when more renewable energy sources are connected to the grid. The uncertainty of renewable energy has notable effects on power system security. In this paper, a set of composite security indices, which are derived from the Hyper-box and Hyper-ellipse Space theory, are extended by a Latin hypercube sampling method to model multiple probabilistic scenarios under uncertainty. Thus, the proposed approach is suitable for power system security assessment with wind power integrated. According to the indices, a security-based active demand response (DR) strategy is proposed. This strategy is able to provide expected active DR capacity based on the forecast wind power fluctuations. Therefore, it can be applied to day-ahead power system dispatches.

A two-stage MILP formulation for source-load coordinated dispatch with wind power considering peak-valley regulation and ramping requirements

In this paper, a two-stage mixed integer linear programming (MILP) formulation for source-load coordinated dispatch with wind power considering peak-valley regulation and ramping requirements is proposed. First, the peak-load regulation and ramping requirements of the net load curve are analyzed. Second, the first stage optimization model considering incentive-based demand response (IDR) is formulated to optimize the net load curve, in which the objective function is to minimize the compensation costs of IDR. Several constraints are taken into account to reduce the peak-valley regulation needs and meet the ramping requirements. Then, based on the optimized load curve, the second stage day-ahead dispatch optimization model is proposed to optimize the allocation of generation sources, taking the total costs of power generation minimization as the objective function considering thermal unit reserve costs. The proposed model is applied to a 10-unit system with a wind power farm with 600MW installed capacity. Simulation results demonstrate the effectiveness and feasibility of the proposed model.

Power management strategy combining energy storage and demand response for microgrid emergency autonomous operation

This paper presents a power management strategy for microgrid emergency autonomous operation subsequent to unplanned islanding events. The proposed approach is composed of two coordinated scheduling stages operating in different time-frames to accommodate the uncertainty and variability associated with renewable generations as well as forecasting errors, and combines distributed generations, energy storage systems and demand side management techniques to ensure secure and stable microgrid autonomous operation. A scenario dependent rule-based approach is adopted for scheduling the microgrid resources which is computationally efficient and particularly suitable for microgrids with limited number of resources. Case study on a grid-connected microgrid test system based on IEEE 13-node distribution feeder demonstrates the effectiveness of the proposed approach in microgrid frequency regulation following an unplanned islanding events.