A robust supply and demand controller against uncertainties of renewable energy sources

Abstract

The rapid growth in demand of electricity combined with renewable energy sources (RESs) are presenting serious challenges for the optimal network operation. The future perspective of the dramatic increase in RESs, such as wind and solar energy, may lead to severe problems related to the load dispatch. Other important aspect is the reduction of controllable resources yielding concerns about the reliability issues of such sources. This paper focuses on a new technique for mitigating the irregularity associated with renewable power generation. A new method is proposed for 24-hour and real-time generation schedule as an efficient solution for demand and supply management over the limited control resources of a power system. Load following capability will be considered as critically limited. The flexible operational outcome of the proposed approach satisfies the economical requirements and reliability against uncertainties of RESs.

Deep analysis of wind variability and smoothing effect in Moroccan wind farms

“…In Kenya, another study shows that “the spread effect is important when the sites are considered for integration in the power system” and “Concentration of wind farms in one region could result in a higher increase in operating reserve and vice-versa” (Barasa and Aganda, 2016). For regional impact of smoothing effect, a study on the correlation between wind power generation in the European countries shows that the correlation in hourly energy decreases with separation distance in a manner often described by an exponential function (Olauson and Bergkvist, 2016); for the same region, a recent study shows that an “Optimized allocation increases the average output from 20% to around 30%, and significantly reduces the frequency of low output values” (Sasaki et al, 2014). Another study titled “The Smoothing Effect in an Afro-Eurasian Renewable Power Grid” shows that sufficient interconnections between Europe, Africa, and Asia lead to a relative reduction of the total backup energy need of 50% (from 15% of the consumption to 7.5%; Krutova et al, 2016).…”

“…• • Sensitivity to current generator ramp rates to balance large-scale RES generation (Sasaki et al, 2014).…”

A Study for On-demand Generation Regulation Control

“…That is, forecasting gets complicated with more factors to be predicted, and demand-supply balancing control becomes difficult. In this context, we proposed robust demand and supply control manager (DS manager) 1 as a demand-supply control system to deal with uncertainties of intermittent renewable generators. With DS manager, longto short-term demand-supply forecasting and scheduling are performed as in conventional demand-supply adjustment, but uncertainties of operated intermittent renewable generators are taken into account.…”

A study for on‐demand generation regulation control

“…That is, forecasting gets complicated with more factors to be predicted, and demand‐supply balancing control becomes difficult. In this context, we proposed robust demand and supply control manager (DS manager) as a demand‐supply control system to deal with uncertainties of intermittent renewable generators. With DS manager, long‐ to short‐term demand‐supply forecasting and scheduling are performed as in conventional demand‐supply adjustment, but uncertainties of operated intermittent renewable generators are taken into account.…”