45 research outputs found
Stochastic Procurement of Fast Reserve Services in Renewable Integrated Power Systems
Ensuring the security and quality of supply in a power system after a contingency event is one of the most challenging tasks for an electricity system operator. This work is initiated by this challenge and proposes a solution based on the use of provided reserves by fast generators, storage devices, and wind farms. A coordinated model is proposed in a joint energy and reserves market considering their corresponding cost to ensure the adequacy in the simultaneous deployment of reserves for the different sources of uncertainties. The Benders decomposition approach is used in the modeling of the stochastic security-constrained unit commitment, and considering the large-scale and complex nature of the model, acceleration techniques are suggested to reduce the execution time. The proposed model is tested on the 6-bus and the IEEE 118-bus test systems. Numerical results show that the optimal values of reserves successfully address contingencies in both of the critical and normal periods after the contingencies and the optimal solution is calculated in a reasonable computing time
Distribution Market Clearing and Settlement
There are various undergoing efforts by system operators to set up an
electricity market at the distribution level to enable a rapid and widespread
deployment of distributed energy resources (DERs) and microgrids. This paper
follows the previous work of the authors in implementing the distribution
market operator (DMO) concept, and focuses on investigating the clearing and
settlement processes performed by the DMO. The DMO clears the market to assign
the awarded power from the wholesale market to customers within its service
territory based on their associated demand bids. The DMO accordingly settles
the market to identify the distribution locational marginal prices (DLMPs) and
calculate payments from each customer and the total payment to the system
operator. Numerical simulations exhibit the merits and effectiveness of the
proposed DMO clearing and settlement processes.Comment: 2016 IEEE Power & Energy Society General Meetin
Economic operational analytics for energy storage placement at different grid locations and contingency scenarios with stochastic wind profiles
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.The placement of energy storage systems (ESS) in smart grids is challenging due to the high complexity of the underlying model and operational datasets. In this paper, non-parametric multivariate statistical analyses of the energy storage operations in base and contingency scenarios are carried out to address these issues. Monte Carlo simulations of the optimization process for the overall cost involving unit commitment and dispatch decisions are performed with different wind and load demand ensembles. The optimization is performed for different grid contingency scenarios like transmission line trips and generator outages along with the location of the ESS in different parts of the grid. The stochastic mixed-integer programming technique is used for optimization. The stochastic model load demand and wind power are obtained from real data. The uncertainty in the operational decisions is obtained, considering the different stochastic realizations of load demand and wind power. The data analytics is performed on ESS operations in the base and its corresponding contingency scenarios with different locations in the grid. Moreover, it is aided by non-parametric multivariate hypothesis tests to understand their dependence amongst various parameters and locations in the grid. The numerical analysis has been shown on a simple 3-bus system considering all the locational and contingency scenarios.F ERDF Cornwall New Energy (CNE