Contingency probabilities are essential in applying probabilistic methods to operations-based security assessment and related decision-making. There are two basic issues that need particular attention. One is lack of data. The other is dependence on environmental conditions. This paper describes design and implementation of a contingency probability estimator. Statistical methods employed in the estimator include maximum likelihood and linear regression. The work makes use of a limited amount of historical data together with corresponding weather and locational data, to provide contingency probabilities that appropriately reflect conditions and location of each circuit. The approach is illustrated using four years of outage data

This paper proposes a frequency control strategy for voltage source converter based multi-terminal HVDC systems (VSC-MTDC) to facilitate the exchange of primary frequency reserves among asynchronous AC systems, thus providing frequency support from each AC system to the others. The proposed frequency control utilizes a reference signal calculated from global measurements which reflects the overall frequency dynamics of all connected asynchronous AC systems. The proposed control outperforms the traditional frequency droop scheme by reducing impact on the DC voltage profile and improving frequency nadir. The performance of the designed frequency control with different DC voltage droop controls is evaluated. The adaptation of the proposed frequency control for converter outages is analyzed. The robustness of the proposed control to communication latency and the sensitivity of frequency support to power limits are also investigated. The VSCMTDC model and the proposed control are implemented in the commercial grade software PSS/E and thus is suitable to study large-scale realistic systems and can be incorporated into the power system planning process at utilities and ISOs. The effectiveness of the proposed control is illustrated on a developed AC-MTDC test system and also on a large-scale realistic model combining the North American Western Interconnection (WI) and Eastern Interconnection (EI) with continental HVDC interconnections.

The Interconnections Seam Study examines the potential economic value of increasing electricity transfer between the Eastern and Western Interconnections using high-voltage direct-current (HVDC) transmission and cost-optimizing both generation and transmission resources across the United States, proposing, assessing, justifying, and illustrating a major infrastructure change involving two of the world's largest power grids. The study conducted a multi-model analysis that used co-optimized generation and transmission expansion planning and production cost modeling. Four transmission designs under eight scenarios were developed and studied to estimate costs and potential benefits. The results show benefit-to-cost ratios that reach as high as 2.5, indicating significant value to increasing the transmission capacity between the interconnections under the cases considered, realized through sharing generation resources and flexibility across regions.

This work explored the benefits of increasing transmission capacity between the US Eastern and Western Interconnections under a high-renewables future. Given the existing "seam" between the two interconnections, a co-optimized infrastructure planning model was developed to assess tradeoffs between investments in cross-seam HVDC transmission, AC & DC transmission needs within each interconnection, generation investment costs, and operational costs, at different renewable penetration levels. The model allows existing and candidate generation resources for deliverable planning reserves to be shared throughout the interconnections, a feature which drives identification of least-cost investments. This work is performed using an industry-vetted 169-bus representation of the North American power grid. Results from this analysis indicate that, under high wind/solar growth scenarios, the cost of a macrogrid HVDC transmission is outweighed by the generation-related savings they produce. The presence of other benefits related to grid reliability, resilience, and adaptability, suggest that cross-seam transmission is highly attractive infrastructure.

Due to the variable nature of wind resources, the increasing penetration level of wind power will have a significant impact on the operation and planning of the electric power system. Energy storage systems are considered an effective way to compensate for the variability of wind generation. This paper presents a detailed production cost simulation model to evaluate the economic value of compressed air energy storage (CAES) in systems with large-scale wind power generation. The co-optimization of energy and ancillary services markets is implemented in order to analyze the impacts of CAES, not only on energy supply, but also on system operating reserves. Both hourly and 5-minute simulations are considered to capture the economic performance of CAES in the day-ahead (DA) and real-time (RT) markets. The generalized network flow formulation is used to model the characteristics of CAES in detail. The proposed model is applied on a modified IEEE 24-bus reliability test system. The numerical example shows that besides the economic benefits gained through energy arbitrage in the DA market, CAES can also generate significant profits by providing reserves, compensating for wind forecast errors and intra-hour fluctuation, and participating in the RT market.