This study tackles a risk-limiting scheduling problem of non-renewable power generation for large power systems, and addresses potential violations of the security constraints owing to the volatility of renewable power generation and the uncertainty of load demand. To cope with the computational challenge that arises from the probabilistic constraints in the considered problem, a computationall...

abstract: enviromental concerns, improvements in renewable energy technologies, governmental incentives for the use of these resources, and increased t&d; costs, are the main factors driving the energy sector into a new era, where considerable portions of electrical demand will be met through widespread installation of distributed energy resources (ders). the virtual power plant (vpp) is a dece...

This paper proposes a new, metaheuristic optimization technique, Artificial Gorilla Troops Optimization (GTO), for hybrid power system with photovoltaic (PV) and wind energy (WE) sources, solving the probabilistic optimum flow (POPF) issue. First, selected algorithm is developed evaluated such that it applies to solve classical (OPF) approach total fuel cost as objective function. Second, propo...

This paper presents a new framework for the day-ahead reactive power market based on the uniform auction price. Voltage stability and security have been considered in the proposed framework. Total Payment Function (TPF) is suggested as the objective function of the Optimal Power Flow (OPF) used to clear the reactive power market. Overload, voltage drop and voltage stability margin (VSM) are inc...

The optimal power flow problem is concerned with finding a proper operating point for a power network while attempting to minimize some cost function and satisfy several network constraints. In this report we analyze the optimal power flow problem subject to contingency constraints, which demands that there be enough power to meet demands in the network in the event of contingencies such as a f...

Conventional methods are commonly used to solve optimal power flow problems in system networks. However, conventional not suitable for solving large and non-linear as they influenced by initialization values more likely be trapped local optimum. Hence, heuristic optimization such Firefly Algorithm have been widely implemented overcome the limitations of methods. These often use random strategy ...

This paper is engrossed in the usage of metaheuristic optimization methods named JAYA algorithm and teacher learning based (TLBO) algorithm, which deal with objective function optimal power flow (OPF) problem. TLBO Jaya are parameter-free algorithms, reduce complexity algorithms. The this to real losses maintain voltages tap positions within their limits. IEEE-39 bus system data considered for ...

Abstract Because of the enormous economic gain it may offer, unit commitment (UC) has been a primary optimization job in daily operation planning contemporary power systems. The AC optimal flow (ACOPF) constraint is method for determining ideal load arrangement alternating current (AC) Using and ACOPF limitations to determine distribution an important approach ensure steady functioning with exa...