Abstract
As distributed energy resources (DERs) proliferate power systems, power grids face new challenges stemming from the variability and uncertainty of DERs. To address these problems, virtual power plants (VPPs) are established to aggregate DERs and manage them as single dispatchable and reliable resources. VPPs can participate in the day-ahead (DA) market and therefore require a bidding method that maximizes profits. It is also important to minimize the variability of VPP output during intra-day (ID) operations. This paper presents mixed integer quadratic programming-based scheduling methods for both DA market bidding and ID operation of VPPs, thus serving as a complete scheme for bidding-operation scheduling. Hourly bids are determined based on VPP revenue in the DA market bidding step, and the schedule of DERs is revised in the ID operation to minimize the impact of forecasting errors and maximize the incentives, thus reducing the variability and uncertainty of VPP output. The simulation results verify the effectiveness of the proposed methods through a comparison of daily revenue.
Highlights
Distributed energy sources (DERs) include renewable energy sources (RESs), energy storage systems (ESSs), and distributed generators (DGs) [1]
In Korea, owners who have combined ESSs to RESs can obtain additional renewable energy certificates (RECs) when power from an RES is charged to an ESS and discharged to the grid [4]
If the start time reaches 1 AM, a new optimization problem new optimization problem which starts from 1 AM is constructed and re-scheduling is repeated every which starts from 1 AM is constructed and re-scheduling is repeated every 5 min with narrowed time
Summary
Distributed energy sources (DERs) include renewable energy sources (RESs), energy storage systems (ESSs), and distributed generators (DGs) [1]. An offering strategy involving a three-stage stochastic bi-level optimization model has been proposed for a VPP [10] It considered demand and generation uncertainties, as well as rival offers. The VPP becomes a system of systems [11] and requires an algorithm to distribute the generation among smaller VPPs and schedule each of these To address this issue, an interactive multi-VPP dispatch model based on the demand response and game theory was proposed in [12]. Because the proposed scheme does not narrow its time scale during rescheduling, it suffers from a limitation with regard to variability control of DERs. Optimization problems for sizing, bidding, and operating IPVs have been presented previously [15].
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