This paper presents Chemo-tactic PSO-DE (CPSO-DE) optimization algorithm combined with Lagrange Relaxation method (LR) for solving Unit Commitment (UC) problem. The proposed approach employs Chemo-tactic PSO-DE algorithm for optimal settings of Lagrange multipliers. It provides high-quality performance and reaches global solution and is a hybrid heuristic algorithm based on Bacterial Foraging O...

The California ISO has taken several measures to incorporate the uncertainty due to Wind and Solar variability into the unit commitment and dispatch algorithms used in market operations. A hybrid approach that recognizes the need to incorporate uncertainties in operation of Day-ahead and real-time markets is presented. The hybrid approach is based on leveraging different forecasting techniques ...

At Eurocrypt 2011, Lindell presented practical static and adaptively UC-secure commitment schemes based on the DDH assumption. Later, Blazy et al. (at ACNS 2013) improved the efficiency of the Lindell’s commitment schemes. In this paper, we present static and adaptively UC-secure commitment schemes based on the same assumption and further improve the communication and computational complexity, ...

In 2011, Lindell proposed an efficient commitment scheme, with a non-interactive opening algorithm, in the Universal Composability (UC) framework. He recently acknowledged a bug in its security analysis for the adaptive case. We analyze the proof of the original paper and propose a simple patch of the scheme. More interestingly, we then modify it and present a more efficient commitment scheme s...

The environmental concerns are having a significant impact on the operation of power systems. The traditional Unit Commitment problem, which to minimizes the fuel cost is inadequate when environmental emissions are also considered in the operation of power plants. This paper presents a Biased Random Key Genetic Algorithm (BRKGA) approach combined with non-dominated sorting procedure to find sol...

The advent of High Performance Computing (HPC) has provided the computational capacity required for power system operators (SO) to obtain solutions in the least time to highly-complex applications, i.e., Unit Commitment (UC). The UC problem, which attempts to schedule the least-cost combination of generating units to meet the load, is increasing in complexity and problem size due to deployments...

This paper proposes a stochastic unit commitment (SUC) approach to solve day-ahead (UC) problem in system with high uncertainty net load which is caused by photovoltaic (PV) power plants. In contrast robust (RUC) only considers the worst-case scenario, SUC every possible scenario its probability. Multiple PV curves were obtained using k-means clustering on historical data. The proportion of clu...

In recent years, the need for generation mixes that consider inertial constraints in unit commitment (UC) has increased because inertia of these systems decreased with use renewable energy. circumstances, single-machine models can calculate minimum frequency and rate change (RoCoF) at a high speed terms characteristics changes mix, order to identify satisfy constraints. This study proposed meth...

Grid integration of renewable resources such as solar and wind energy can significantly raise the level uncertainty in power systems, making scheduled operation generating units difficult. Therefore, importance operating reserves is more emphasized to prevent disruption by sudden changes outputs generators. In this paper, a stochastic unit commitment (UC) model reflect due large amount proposed...

Approximations made in day-ahead markets can result in suboptimal or even infeasible schedules for generating units and inaccurate predictions of actual costs and wind curtailment. Here we compare different optimal models of day-ahead markets based on unit commitment (UC) formulations, especially energyvs. power-based UC; excluding or including startup and shutdown trajectories; and determinist...