With the integration of large-scale renewable energy sources (RES) and high voltage direct current (HVDC) based inter-regional transmission, modern power systems are facing low-inertia issues and poor frequency regulation capabilities. This article conducts a comprehensive review on frequency control and optimal operation methods in this context. First, the frequency characteristic of a low-inertia power system is analyzed covering the whole frequency response process. Secondly, the impacts of RES and HVDC integration on system inertia and frequency performance are studied, and the system frequency characteristics considering RES and HVDC are analyzed. Then, the frequency response modes of various frequency regulation resources are compared from the perspective of “source-grid-load-storage”, including their basic control principles and frequency control strategies. Further, from the operation dispatch perspective, the frequency security-constrained power system optimal operation methods are reviewed. Finally, future research trends in this area are discussed.

Active distribution networks (ADNs) with distributed generators (DGs) can provide flexibility for the upstream grid by participating in energy and flexibility markets. In this paper, a novel market-clearing model is proposed to facilitate energy and flexibility transactions through coordinating the flexibility providers in both transmission and distribution networks. The energy and flexibility market-clearing problem is formulated as a bi-level optimization model. The upper-level models the transmission-level joint energy and flexibility market clearings while the lower-level represents the distribution-level ADN market clearings. In the proposed model, the locational marginal prices (LMP) at the coupling bus will affect the dispatch of DGs and power demands of the ADNs. In turn, the power demands of the ADNs and the offers submitted by DGs will affect energy and flexibility market-clearing results and the LMPs as well. Karush-Kuhn-Tucker (KKT) conditions and the duality theory are used to transform the proposed nonlinear bi-level model to a single-level mathematical program with equilibrium constraints (MPEC) model. Case studies verify the effectiveness of the proposed model.

This paper proposes a stochastic optimal energy management and pricing model for LSE with aggregated TCLs and energy storage based on Stackelberg game and stochastic programming. The energy management and pricing problem is formulated as a bi-level optimization model. The upper level model aims to maximize LSE expected profit under market price uncertainties and determines the offering prices to consumers. According to the offering price from upper level model, the lower level model optimizes the power purchasing pattern for consumers of two types of buildings with TCLs: factory and office buildings. The nonlinear bi-level model is reformulated and converted into mixed-integer linear programming (MILP) using strong duality theory. The proposed model is validated by numerical studies based on real market prices from PJM electricity market. In addition, the impacts of energy storage, number of buildings, comfort indoor temperature limits and offering price limits on LSE profit are analyzed.

Extreme natural hazards, such as hurricanes or earthquakes, have a high probability of threatening energy supply security and causing high-order contingencies to island city-integrated energy systems (IC-IESs). To better evaluate and enhance resilience, a novel approach is proposed in this work for IC-IESs. The resilience of an IC-IES is analyzed from both the system level and the component level. At the system level, the impacts of extreme natural disasters are quantified. At the component level, the importance of individual components is analyzed through pre-failure and post-failure indices. The pre-failure index identifies the system’s weak links before an energy interruption, and the post-failure index determines the optimal repair strategy to restore the service. The proposed indices are solved by the impact increment method (IIM), which significantly improves computational efficiency without much affecting result accuracy. Numerical simulation studies are conducted on the modified Barry Island IES and IES E123-G48-H32 test systems. The results validate the effectiveness of the proposed approach.

The existing bidding models for retailers managing electric vehicles (EVs) in distribution-level day-ahead (DA) electricity markets have not fully addressed EVs’ temporal distribution, charging and discharging management, or bidding curves. To address these challenges, this paper proposes a DA optimal bidding model for a retailer with flexible participation of EVs. First, the investigating period for DA optimal bidding is modeled to cover the connecting periods of all EVs that may potentially impact the DA power demand prediction. Then, incentive mechanisms for charging and discharging are proposed to enable retailers to manage EVs under uncertain market prices and EV parameters while also considering the battery degradation cost and the preferences of EV users based on a social survey. The optimal charging model based on incentive mechanisms for charging-discharging helps EVs minimize their energy purchase costs under different price scenarios. Based on the minimum EV energy purchase cost, the optimal bidding model of a retailer aims to achieve the maximum bidding profit considering the conditional value at risk (CVaR), with the step bidding curves and the temporal differences for different time intervals considered. Simulations validate the proposed model under flexible incentive mechanism for charging and incentive mechanism for discharging participation of EVs.

Forced oscillation source location (FOSL) plays a significant role in mitigating forced oscillations (FOs), which threaten the power system stability. This paper proposes a data-driven approach for FOSL in power systems using synchrosqueezing wavelet transform (SWT). The proposed approach conducts SWT on the measured system responses to obtain the SWT matrix. Then, the SWT-based dissipating energy flow (DEF) model in time-frequency domain and dissipating energy spectrum (DES) model in frequency domain are derived from the traditional DEF model. Further, the characteristics of SWT-based DEF and DES are revealed by referring to the traditional DEF, and the FOSL criteria of the SWT-based DEF and DES can be hereby obtained. Using the obtained FOSL criteria, the FO source can be located from the measured responses. The performance of the proposed FOSL method is evaluated by simulation data of the WECC 179-bus test system and field-measurement PMU data of the ISO New England. The results confirm the accuracy and efficiency of the proposed method in the FOSL.