Integrated energy hub system based on power‐to‐gas and compressed air energy storage technologies in the presence of multiple shiftable loads

Abstract

Integrated energy carriers in the framework of energy hub system (EHS) have an undeniable role in reducing operating costs and increasing energy efficiency as well as the system's reliability. Nowadays, power‐to‐gas (P2G), as a novel technology, is a great choice to intensify the interdependency between electricity and natural gas networks. The proposed strategy of this study is divided into two parts: (i) a conditional value‐at‐risk‐based stochastic model is presented to determine the optimal day‐ahead scheduling of the EHS with the coordinated operating of P2G storage and tri‐state compressed air energy storage (CAES) system. The main objective of the proposed strategy is to indicate the positive impact of P2G storage and tri‐state CAES on lessening the system uncertainties including electricity market price, power generation of the wind turbine, and even electrical, gas, and thermal demands. (ii) A demand response program focusing on day‐ahead load shifting is applied to the multiple electrical loads according to the load's activity schedule. The proposed strategy is successfully applied to an illustrative example and is solved by general algebraic modeling system software. The obtained results validate the proposed strategy by demonstrating the considerable diminution in the operating cost of the EHS by almost 4.5%.

A hybrid robust‐stochastic approach for optimal scheduling of interconnected hydrogen‐based energy hubs

“…In two hours (i.e., hours 5 and 6), the CHP unit is in the maximum electric power mode and then its heat production is equal to zero. In the remaining hours of Figure 5, besides the CHP generated power, the GT is only committed in peak times (i.e., hours [16][17][18][19][20][21][22] to meet the electrical demand. By explanations for Figure 5, the heat power generated by CHP and gas boiler units are illustrated in Figure 6.…”

“…Hence, the EH operator prefers to buy the required electric power instead of committing the units, which have a high-cost coefficient in power production. However, in peak hours (i.e., hours [19][20] and the periods with additional power, the rest of the electric power is sold to the main grid to minimise operating costs. Likewise, due to gas consumption in gas-based power units (i.e., CHP, gas turbine, and boiler), the imported gas from the main gas network is varied along the scheduling period.…”

“…(20) (21) (22), respectively. These limitations determine that the starting up and shutting F I G U R E 3 Gas and electricity price profiles MANSOUR-SATLOO ET AL.…”

Review on Energy Storage Systems in Microgrids

“…(b) Potential Energy Storage System: i. Compressed air energy storage system (CAESS) [5,6,22,23,[30][31][32][33][34]: The air is compressed into a defined pressure using a piston, then using natural gas to combust it for turbines using as mechanical energy storage generating electricity when needed. It stores a large amount of energy without needs a specific location installation [38][39][40]. ii.…”

Two-Stage Joint Optimal Scheduling of a Distribution Network With Integrated Energy Systems

“…The energy hub has been widely applied in optimal scheduling, optimal design and other fields [22], [23]. The energy hub is an important part of an IES that can transform, distribute and store various types of energy [24], [25]. The expression for the energy hub model in this article is as follows (1), as shown at the bottom of the page, where L e , L h and L c are the electricity load, thermal load and cooling load, respectively; P e , P g and P pv are the energy input of the power grid, natural gas and photovoltaic, respectively; η t , η e gt , η h gt , η rec , η gb , η ex , η ec and η ac are the transformer efficiency, gas turbine electrical efficiency, gas turbine thermal efficiency, waste heat recovery system efficiency, gas boiler efficiency, electric chiller efficiency and absorption chiller efficiency, respectively.…”