Generation scheduling at PCC in grid connected microgrid

Abstract

A microgrid is a self-sustainable grid which can be operated in two modes, i.e. Grid coneected mode and grid isolated mode. In grid connected mode microgrid can be connected to grid at Point of Common Coupling (PCC). This paper considers grid connected microgrid for generation scheduling. This paper analyzes the Generation scheduling at PCC in grid connected mode of microgrid. Here microgrid is having renewable generators (i.e. Wind and PV) and dispatchable units, and generation scheduling problem at PCC is formed by robust approach and solved by using GAMS (General Algebraic Modeling System). Practical case study considering excess renewable generation and excess demand are discussed.

Solar Power Predictions in Stochastics Framework

“…Despite these problems, solar power and wind power generation are rapidly growing due to consistently decreasing cost of solar power and wind power generation and continuously improving accuracy of available forecasting tools. MG's generation scheduling problem can be treated as a decision-making problem due to uncertainty of wind power and solar power availability and load demands [5][6][7]. Modeling of involved uncertainties is necessary to solve these decision-making problems.…”

“…Therefore, the computational efforts are required to reduce the original scenario set to solve scenario-based optimization models. Reduced scenarios are obtained in such a manner that the reduced set has a smaller number of scenarios, with minimally changed statistical properties [5][6][7][8].…”

“…Thermal rating of transmission lines have been forecasted by the time series ARIMA model, considering the effect of weather uncertainty. Bidding strategy problem using a stochastic programming approach is simulated by generating price scenarios of the Nordic market using ARMA model [7].…”

“…For wind power scenario generation, all methods assume that wind power forecasting error density function follows Gaussian or normal distribution. Statistical analysis shows that due to variable kurtosis, wind power forecasting error probability density function cannot be characterized by normal distribution [7]. Therefore, this assumption is not valid for practical applications.…”

Optimal BESS Scheduling Strategy in Microgrids Based on Genetic Algorithms

“…For an efficient microgrid operation, accurate load demand and renewable energy generation forecasting models are necessary to be implemented. In [13], a three stages approach based on Bender's decomposition is proposed for sizing and scheduling the energy storage system and microturbine, considering also PV generation. A robust optimization model is presented in [14], where the generation scheduling at the Point of Common Coupling (PCC) is analyzed in a microgrid including both wind and PV generation.…”