Stochastic Unit Commitment with High-Penetration Offshore Wind Power Generation in Typhoon Scenarios

To tackle the energy crisis and climate change,wind farms are being heavily invested in across the world.In China's coastal areas,there are abundant wind resources and numerous offshore wind farms are being constructed.The secure operation of these wind farms may suffer from typhoons,and researchers have studied power system operation and resilience enhancement in typhoon scenarios.However,the intricate movement of a typhoon makes it challenging to evaluate its spatial-temporal impacts.Most published papers only consider predefined typhoon trajectories neglecting uncertainties.To address this challenge,this study proposes a stochastic unit commitment model that incorporates high-penetration offshore wind power generation in typhoon scenarios.It adopts a data-driven method to describe the uncertainties of typhoon trajectories and considers the realistic anti-typhoon mode in offshore wind farms.A two-stage stochastic unit commitment model is designed to enhance power system resilience in typhoon scenarios.We formulate the model into a mixed-integer linear programming problem and then solve it based on the computationally-efficient progressive hedging algorithm(PHA).Finally,numerical experiments validate the effectiveness of the proposed method.

Frequency-constrained Co-planning of Generation and Energy Storage with High-penetration Renewable Energy

Large-scale renewable energy integration decreases the system inertia and restricts frequency regulation. To maintain the frequency stability, allocating adequate frequency-support sources poses a critical challenge to planners. In this context, we propose a frequency-constrained coordination planning model of thermal units, wind farms, and battery energy storage systems (BESSs) to provide satisfactory frequency supports. Firstly, a modified multi-machine system frequency response (MSFR) model that accounts for the dynamic responses from both synchronous generators and grid-connected inverters is constructed with preset power-headroom. Secondly, the rate-of-change-of-frequency (ROCOF) and frequency response power are deduced to construct frequency constraints. A data-driven piecewise linearization (DDPWL) method based on hyperplane fitting and data classification is applied to linearize the highly nonlinear frequency response power. Thirdly, frequency constraints are inserted into our planning model, while the unit commitment based on the coordinated operation of the thermal-hydro-wind-BESS hybrid system is implemented. At last, the proposed model is applied to the IEEE RTS-79 test system. The results demonstrate the effectiveness of our co-planning model to keep the frequency stability.

A contingency-aware method for N-2 security-constrained transmission expansion planning

In this paper,a novel contingency-aware method for N-2 security-constrained transmission expansion planning is proposed.To ensure that the transmission construction plan satisfies the N-2 security criterion,the proposed method takes advantage of the adjustable robust optimization(ARO)framework and upgrades it.We construct a discrete uncertainty set in which component failures are treated as uncertain events that are handled as binary variables.In addition to the failure of existing lines and generators,we explicitly model the failure of candidate lines.The proposed model comprises a master problem that makes the transmission construction decision,and a series of subproblems that can detect not only the worst contingency,but also the potential contingencies.Computational studies on the IEEE RTS 24-bus and IEEE 118-bus test systems are carried out to validate the effectiveness of the proposed method.Compared with the deterministic method and ARO method in the literature,the proposed method has higher computational efficiency.

Accommodating Uncertain Wind Power Investment and Coal-fired Unit Retirement by Robust Energy Storage System Planning

Increasing wind power integration and coal-fired unit retirements increases the strain on the power system’s spinning reserve and increases the pressure on peak regulation.With the ability to stock extra power generation and supply the peak load,the energy storage system(ESS)can alleviate the rising demand on the spinning reserve and play an increasingly important role in the power system.In this paper,a trilevel robust ESS planning model is proposed to accommodate uncertain wind power investment as well as coal-fired unit retirement.The upper-level of this model is to determine the planning scheme of ESSs,which iteratively takes the worst-case scenario of wind power investment and coal-fired unit retirement into consideration.The middle-level and lower-level of this model are to make the optimal daily economic dispatch under the worst-case realizations of uncertainties.We derive an equivalent reformulation of the proposed robust ESS planning model and solve it with a dual column-and-constraint generation algorithm.Case studies are conducted using the IEEE RTS-79 system.The results demonstrate the superiority of the proposed planning method in comparison with other methods.Furthermore,the effects of the capital cost of ESS,the expected proportion of wind power,and the uncertainty budget on the development of ESS are studied.Taking the uncertainties of unit retirement and wind power investment into consideration achieves a better trade-off between the ESS investment cost and the operational cost.

An Extended DC Power Flow Model Considering Voltage Magnitude

A quasi-linear relationship between voltage angles and voltage magnitudes in power flow calculation is presented.An accurate estimation of voltage magnitudes can be provided by the quasi-linear relationship when voltage angles are derived by classical DC power flow.Based on the quasi-linear relationship,a novel extended DC power flow(EDCPF)model is proposed considering voltage magnitudes.It is simple,reliable and accurate for both distribution network and transmission network in normal system operation states.The accuracy of EDCPF model is verified through a series of standard test systems.