This paper investigates the weather-driven performance of electricity markets in the operational time frame. Employing the probability distribution fitting approaches, weather impacts on power generation and electricity demand are modeled and assessed through processing large volume of historical data sets. Several novel weather-impact indices are proposed in this paper to evaluate the vulnerab...

This paper presents an online two-stage Q-learning based multi-agent (MA) controller for load frequency control (LFC) in an interconnected multi-area multi-source power system integrated with distributed energy resources (DERs). The proposed control strategy consists of two stages. The first stage is employed a PID controller which its parameters are designed using sine cosine optimization (SCO...

In this paper, an optimal scheduling of thermal and wind power plants is presented by using a stochastic programming approach to cover the uncertainties of the forecasted generation of wind farms. Uncertainties related to wind forecast error, consequently wind generation outage power and also system load demand are modeled through scenario generation. Then, with regard to day-ahead and real-tim...

A new algorithm for solving convex stochastic optimization problems with expectation functions in both the objective and constraints is presented. The algorithm combines a stochastic hybrid procedure, which was originally designed to solve problems with expectation only in the objective, with dual stochastic gradient ascent. More specifically, the algorithm generates primal iterates by minimizi...

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto.fi Author Matti Koivisto Name of the doctoral dissertation Finding Value in Big Data: Statistical Analysis of Large Data Sets with Applications in Electric Power Systems Publisher School of Electrical Engineering Unit Department of Electrical Engineering and Automation Series Aalto University publication series DOCTORAL DISSERTATIONS 22...

this paper presents an application of benders decomposition to deal with the complexities in the simultaneous generation expansion planning (gep) and transmission expansion planning (tep). unlike the power system operation fields of study, the power system planning methods are not expected to be fast. however, it is always preferable to speed up computations to provide more analysis options for...

The European electricity market has been deregulated recently. This means that energy companies must optimize power generation considering the rapidly fluctuating price on the spot market. Optimisation has also become more difficult. Novel production technologies, such as gas turbines (GT), combined heat and power generation (CHP), and combined steam and gas cycles (CSG) require non-convex mode...

The collection of clean power from ambient vibrations is considered a promising method for energy harvesting. For the case of wheel rotation, the present study investigates the effectiveness of a piezoelectric energy harvester, with the application of stochastic resonance to optimize the efficiency of energy harvesting. It is hypothesized that when the wheel rotates at variable speeds, the ener...

It is shown that the evolution of the density perturbations during certain eras of substantial entropy generation in the universe can be described in the scheme of the KPZ equation. Therefore, the in uence on cosmological structure formation by stochastic forces arising from various dissipations can be studied through the universal characteristics of surface growth in d = 3 + 1 dimensions. We i...