Risk-Averse Scheduling of Combined Heat and Power-Based Microgrids in Presence of Uncertain Distributed Energy Resources

Abstract

In this paper, a robust scheduling model is proposed for combined heat and power (CHP)-based microgrids using information gap decision theory (IGDT). The microgrid under study consists of conventional power generation as well as boiler units, fuel cells, CHPs, wind turbines, solar PVs, heat storage units, and battery energy storage systems (BESS) as the set of distributed energy resources (DERs). Additionally, a demand response program (DRP) model is considered which has a successful performance in the microgrid hourly scheduling. One of the goals of CHP-based microgrid scheduling is to provide both thermal and electrical energy demands of the consumers. Additionally, the other objective is to benefit from the revenues obtained by selling the surplus electricity to the main grid during the high energy price intervals or purchasing it from the grid when the price of electricity is low at the electric market. Hence, in this paper, a robust scheduling approach is developed with the aim of maximizing the total profit of different energy suppliers in the entire scheduling horizon. The employed IGDT technique aims to handle the impact of uncertainties in the power output of wind and solar PV units on the overall profit.

IGDT-Based Robust Operation of Thermal and Electricity Energy-Based Microgrid with Distributed Sources, Storages, and Responsive Loads

“…Terefore, to better model MG operation, it is necessary to formulate the thermal model of sources and consumers. Tis has rarely been discussed such as in [19-24, 27, 28], but note that references [19,20,22,23] present only a hybrid system of sources, ESS, and heat storage, while neglecting their connection to the energy or electrical network. (ii) Note that by managing the scheduling of power sources, storage devices, and responsive loads, a suitable fnancial beneft can be obtained for them from the energy and ancillary services markets.…”

“…However, in most pieces of research, the MG operation model has been considered, the aim of which is to improve the technical indices of the network, such as reducing power losses and voltage drop, along with achieving the lowest operating cost of MG and the mentioned elements. In a few references such as [9,16,18,22], their participation in the energy market has been addressed. Also, these resources, with the ability to control reactive power, can play a role in ancillary services such as reactive power compensation.…”

“…Furthermore, to achieve a reliable solution in the presence of uncertainties, it is necessary to consider the risk model, which cannot be evaluated using the mentioned methods. To address these limitations, robust programming based on IGDT is appropriate, which has been considered in fewer studies such as [13,22,23] related to MG operation problems.…”

“…Te heating network is frst modeled linearly, and then a computationally tractable PBIDR model is proposed. Reference [22] presents a robust scheduling model for MGs that operate based on CHP. Te model is constructed with the help of IGDT.…”

Boosting Transmission System Flexibility in Network-Constrained Unit Commitment by Incorporating Distributed Series Reactors

“…According to the existing studies, there is a need for a flexible power transmission grid to handle this challenge and determine the optimal hourly scheduling of both generation and transmission networks. Proposed solutions include the use of energy storage systems (ESS) [2], the use of demandside programs such as demand response programs (DRPs) [3], and the use of flexible AC transmission system (FACTS) devices to add more flexibility to the transmission grid [4]. By proper coordination between these flexibilities via a unit commitment (UC) framework, transmission system congestion can be mitigated.…”