Reliable Dispatch of Renewable Generation via Charging of Dynamic PEV Populations

TL;DR

This paper presents a three-stage scheme for dispatching renewable energy systems with electric vehicles, addressing uncertainties through probabilistic forecasts and dynamic modeling to enhance grid reliability.

Contribution

It introduces a novel three-stage dispatch method combining probabilistic and deterministic forecasts with dynamic vehicle aggregation models for renewable integration.

Findings

Effective dispatch schedule generation using probabilistic forecasts.

Validation with real data demonstrates improved dispatch reliability.

Dynamic vehicle aggregation enhances renewable energy integration.

Abstract

The inherent storage of plug-in electric vehicles is likely to foster the integration of intermittent generation from renewable energy sources into existing power systems. In the present paper, we propose a three-stage scheme to the end of achieving dispatchability of a system composed of plug-in electric vehicles and intermittent generation. The main difficulties in dispatching such a system are the uncertainties inherent to intermittent generation and the time-varying aggregation of vehicles. We propose to address the former by means of probabilistic forecasts and we approach the latter with separate stage-specific models. Specifically, we first compute a dispatch schedule, using probabilistic forecasts together with an aggregated dynamic model of the system. The power output of the single devices are set subsequently, using deterministic forecasts and device-specific models. We draw upon a simulation study based on real data of generation and vehicle traffic to validate our findings.