Design and Evaluation of Operational Scheduling Approaches for HCNG Penetrated Integrated Energy System

Abstract

This paper proposes and assesses three different control approaches for the hydrocarbon natural gas (HCNG) penetrated integrated energy system (IES). The three control approaches adopt mixed integer linear programing, conditional value at risk (CVaR), and robust optimization (RO), respectively, aiming to mitigate the renewable generation uncertainties. By comparing the performance and efficiency, the most appropriate control approach for the HCNG penetrated IES is identified. The numerical analysis is conducted to evaluate the three control approaches in different scenarios, where the uncertainty level of renewable energy (within the HCNG penetrated IES) varies. The numerical results show that the CVaR-based approach outperforms the other two approaches when renewable uncertainty is high (approximately 30%). In terms of the cost to satisfy the energy demand, the operational cost of the CVaR-based method is 8.29% lower than the RO one, while the RO-based approach has a better performance when the renewable uncertainty is medium (approximately 5%) and it is operational is 0.62% lower than that of the CVaR model. In both evaluation cases, mixed integer linear programing approach cannot meet the energy demand. This paper also compares the operational performance of the IES with and without HCNG. It is shown that the IES with HCNG can significantly improve the capability to accommodate renewable energy with low upgrading cost.

Optimization of Dynamic Dispatch for Multiarea Integrated Energy System Based on Hierarchical Learning Method

“…Note the data as (s k , a k , c k , s k+1 ), and the Q(s k , a k ) updates according to (23) with the learning factor α if s k+1 isnottheendstate. Otherwise,updatesQ(s k , a k ) with (29).…”

“…And many algorithms have been applied to the optimization for the IES. In [29], three different control approaches for integrated energy system is compared with renewable uncertainty. Particle swarm optimization algorithm and generation algorithm are used in the optimization problems of the IES in [30] and [31].…”

Resilience assessment for natural gas systems and electrical power systems without complete integration

“…Therefore, constraint in Equation ( 28) can be used to express the time delay characteristic, that is, it can reflect the inconsistency of input and output flow for pipelines in natural gas transmission. Equation (30) is the gas flow balance constraint at a node in the natural gas network.…”

“…Obviously, ADMM algorithm is widely used, which is suitable for addressing consensus coordination optimization problems. Optimal planning [29] and scheduling [30], risk‐constraint sizing [31], energy market clearing [27] have been studied involving CVaR, but not just these aspects listed. Therefore, under extreme disasters, ADMM and conditional value at risk (CVaR) are more effective to describe the distributed operation mode and strategy of an incomplete integrated energy system.…”

A Data-Driven Scheduling Approach for Hydrogen Penetrated Energy System Using LSTM Network

“…Benefiting from the storage stability, energy density, and transformation capability (Power-to-Gas) of hydrogen, the hydrogen penetrated energy system (HPES) is attracting great attention in recent years [3][4][5]. The hydrogen can be used as the fuel not only for the fuel-cell battery but also for the combined cooling and heating plant (CCHP) when mixed with natural gas, the so-called Hydrogen Compressed Nature Gas (HCNG) [6,7]. However, due to the tight coupling characteristics of the HPES and the little research on HCNG powered CCHP, it is difficult to establish mathematical models of the equipment within HPES in high accuracy, and the operational scheduling and adjustment for HPES also require high computation resources.…”