Hybrid Population Based MVMO for Solving CEC 2018 Test Bed of Single-Objective Problems

The MVMO algorithm (Mean-Variance Mapping Optimization) has two main features: I) normalized search range for each dimension (associated to each optimization variable); ii) use of a mapping function to generate a new value of a selected optimization variable based on the mean and variance derived from the best solutions achieved so far. The...

Hybrid Single Parent-Offspring MVMO for Solving CEC2018 Computationally Expensive Problems

Mean-Variance Mapping Optimization (MVMO) belongs to the family of evolutionary algorithms, and has proven to be competitive in solving computationally expensive problems proposed in the Icompetitions CEC2014, CEC2015, and CEC2016. MVMO can tackle such problems by evolving a set of solutions (population based approach) or a single solution ...

Economic outage scheduling of transmission line for long-term horizon under demand and wind scenarios

A substantial increase in renewable energy in-feed to the primary grid as well as demand growth poses a challenge for transmission system operators (TSOs) to perform maintenance activities while addressing security of supply. A computationally efficient outage scheduling algorithm which is customizable in terms of area and time selection is...

PowerFactory-Python based assessment of frequency and transient stability in power systems dominated by power electronic interfaced generation

The deployment of variable renewable energy based power plants is increasing all over the world, however, unlike conventional power plants these are mostly connected to the grid via power electronic interfaces. High penetration of power electronic interfaced generation (PEIG) has an important impact on the inertia of the system, which is of...

Parametric Evaluation of Different ANN Architectures: Forecasting Wind Power Across Different Time Horizons

The participation of volatile wind energy resources in the generation mix of power systems is increasing. It is therefore becoming more and more crucial for system operators to accurately predict the wind power generation across different short term horizons (5 to 60 minutes ahead) in order to adequately balance the system and maintain system...

Co-simulation and Dynamic Model Exchange with Consideration for Wind Projects

This paper discusses and compares two approaches to address technical challenges in performing collaborative studies of power system dynamics. On one side, we consider the model migration approach which is an essential piece of dynamic model exchange. On the other side, we look at the co-simulation approach which is used to couple simulation...

Volatility in Electrical Load Forecasting for Long-term Horizon: An ARIMA-GARCH Approach

Electrical load forecasting in long-term horizon of power systems plays an important role for system planning and development. Load forecast in long-term horizon is represented as time-series. Thus, it is important to check the effect of volatility in the forecasted load time-series. In short, volatility in long-term horizon affects four main...

Neural Network-based Load Forecasting and Error Implication for Short-term Horizon

Load forecasting is considered vital along with many other important entities required for assessing the reliability of power system. Thus, the primary concern is not to forecast load with a novel model, rather to forecast load with the highest accuracy. Short-term load forecast accuracy is often hindered due to various load impacting factors....

Classification, domains and risk assessment in asset management: A literature study

This paper presents a literature study on asset management in electrical power transmission and distribution system. Due to restructure and deregulation of electric power industry in recent times, the focus has been on transmission and<br/>distribution assets that include transmission lines, transformers, power plants, substations and support...

Robust course-changing controller for a ship using QFT design technique