The electric power grid is one of the most complex engineered systems today. Managing thousands of transmission assets spanning many miles and interconnecting regions and countries together combined with optimizing many generators with complex operating requirements creates a very challenging scheduling problem. Such a challenging problem becomes even more complex with resource uncertainty and stringent reliability standards. In order to solve such complex optimization problems within reasonable timeframes, approximations are required. The consequence of such approximations, however, is the need to implement out-ofmarket corrections (uneconomic adjustments). This paper presents an overview of out-of-market corrections, an overview of industry related practices that require out-ofmarket corrections, multiple algorithms that can be used to determine out-of-market corrections, and the various costs and market implications due to out-of-market corrections.

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With the increasing penetration of renewable resources and the retirements of conventional coal-fired generation units, power systems are undergoing significant transformation with the instantaneous renewable generation penetration sometimes approaching over 50 percent of the demand. This transformation makes the need for comprehensive reliability assessment critical to properly account for the composite system adequacy and the sufficiency of essential reliability services (ERSs). This paper introduces a probabilistic approach to evaluate the reliability of wind power integrated power systems considering ERSs including frequency and voltage support, in conjunction with resource adequacy. To consider stochasticity in system operating conditions, the proposed approach utilizes sequential Monte-Carlo Simulation (SMCS) as the probabilistic analysis methodology and formulates probabilistic reliability metrics representing the composite system adequacy and the ERSs. The proposed approach and metrics are demonstrated on a synthetic test system. Simulation results illustrate the efficacy of the proposed approach and its importance in analyzing the impact of increasing wind power penetration as well as wind turbine generators (WTGs) providing ERSs on system reliability. Index Terms-Essential reliability services, frequency control, Monte-Carlo Simulation, reliability metrics, voltage control, wind power penetration. NOMENCLATURE Abbreviations AC Alternating current. COV Coefficient of variation. EGAF Expected generator tripping caused by abnormal frequency. EGAV Expected generator tripping caused by abnormal voltage. ELCC Effective load carry capability. EOAF Expected occurrence of abnormal frequency at generator terminals. EOAV Expected occurrence of abnormal voltage at generator terminals. EPNS Expected power not supplied. LOLP Loss of load probability.

In order to sustain a continuous supply of electric power during a potential N-1 event, sufficient amount of reserves have to be acquired. The acquisition of such contingency reserves starts at the day-ahead scheduling phase. However, modern day-ahead unit commitment problems, which acquire reserves that exceed the largest contingency, do not guarantee a reliable solution as the deliverability of the reserves depends on the reserve locations. Corrective transmission topology control can be used by the operator during a post-contingency state as a mechanism to improve the deliverability of reserves. In this paper, a model that incorporates corrective transmission topology control within contingency analysis is presented. Various solution techniques are also compared in terms of performance and these methods are tested on the IEEE 118-bus and IEEE 73-bus test systems. Numerical results show that topology control significantly reduces the number of cases with constraint violations.Index Terms--Contingency analysis, power system reliability, power transmission control, topology control.

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