Integrated optimization of a regional integrated energy system with thermal energy storage considering both resilience and reliability

Ren, Hongbo; Jiang, Zipei; Wu, Qiong; Li, Qifen; Yang, Yong

doi:10.1016/j.energy.2022.125333

Cited by 26 publications

(6 citation statements)

References 24 publications

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“…The thermal energy for emergency heating at each moment is isolated from the capacity of the HWT. Thus, the thermal energy of the HWT Q TS,t at time t is divided into the thermal energy for daily operation Q use,t and the thermal energy for emergency heating Q em,t as shown in Equation (12).…”

Section: Thermal Energy For Emergency Heatingmentioning

confidence: 99%

“…Currently, most of the existing research focuses on the use of electrical energy storage in dealing with emergent energy outages. Similar to electrical energy storage, the use of TES also has the ability to solve the thermal supply-demand mismatch caused by external energy supply interruption [12]. On the other hand, rather than electric energy storage, TES in REH is more economical [13].…”

mentioning

confidence: 99%

“…In ref. [12], a two-level rolling optimisation method for TES was proposed to ensure load supply in the case of external energy interruption or equipment failure.…”

mentioning

confidence: 99%

“…However, the thermal energy for emergency building heating provided by an HWT is determined by the minimum thermal demand of residents during a power outage. The unpredicted power outage duration and weather, mainly including the outdoor temperature and irradiation, are the main factors that impact the optimal scheduling of REH, especially emergency heating [12,17,18]. Under this circumstance, overestimating the thermal energy for emergency heating will cause excessive energy consumption.…”

mentioning

confidence: 99%

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Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach

Zhang

et al. 2022

IET Energy Syst Integration

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Residential heating faces the challenge of heating interruption when an electric power outage occurs. As a promising heating electrification form, regenerative electric heating (REH) equipped with thermal energy storage (TES) has the flexibility of maintaining the building indoor temperature within the desired range during power outages and reducing the operation cost during normal operation states. However, the allocation and scheduling of the limited thermal energy in TES for the above two purposes is impacted by many uncertainties, for example, outdoor temperature, irradiation, and duration of power outages. Overestimation of the thermal energy required for power outages in the TES can improve the heating supply reliability, but it will also increase the REH operation cost to some extent, and vice versa. To address this problem, an affine arithmetic‐based model predictive control approach (AA‐MPC) for an optimal REH scheduling method is proposed to balance the heating supply reliability during power outages and operation economy of REH at the same time. An REH‐based residential building energy system model is developed to describe the building thermal load associated with the outdoor temperature and irradiation. Then, the required thermal energy for emergency building heating provided by the hot water tank (HWT) is determined using the minimum thermal demand of residents during a power outage, which is constrained by the minimum comfort temperature threshold. Based on this, an AA‐MPC approach that takes the thermal energy for emergency building heating as a time‐varying constraint of the HWT is developed to determine the optimal REH scheduling that considers emergency residential building heating under the above uncertainties. Numerical studies show that the proposed method can maintain minimum thermal demand for at least 2 h when a power outage occurs under uncertainties. At the same time, it can reduce the impact of uncertainties on the operation cost and reduce economic problems caused by emergency heating to a certain extent. Compared to the interval arithmetic‐based model predictive control approach, the operation cost intervals of the proposed method are reduced by 57.3%, 0.3%, and 32.5% under low, middle, and high prediction error levels respectively.

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Section: Thermal Energy For Emergency Heatingmentioning

confidence: 99%

mentioning

confidence: 99%

“…In ref. [12], a two-level rolling optimisation method for TES was proposed to ensure load supply in the case of external energy interruption or equipment failure.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

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Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach

Zhang

et al. 2022

IET Energy Syst Integration

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“…Ref. [18] focused on enhancing system flexibility and stability by optimizing the capacity of thermal storage equipment. The concept of virtual energy storage was explored through the optimization of controllable loads within the system.…”

Section: Introductionmentioning

confidence: 99%

Multi-Time-Scale Optimal Scheduling of Integrated Energy System Considering Transmission Delay and Heat Storage of Heating Network

Wang,

Zeng,

Wan

2023

Sustainability

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In the integrated energy system, significant potential exists for the regulation of the heat storage capacity within the heating network. In relation to this attribute, the establishment of the quasi-dynamic model for the heating network is accomplished through the utilization of the fictitious node method. Additionally, a method is introduced to quantify the heat storage within the heating network. Moreover, a multi-time-scale scheduling approach is proposed for the integrated energy system, with consideration given to the heat storage of the heating network. During the day-ahead scheduling phase, the active regulation of the heat storage within the heating network is carried out to enhance the economy of system operation. Transitioning to the intra-day upper scheduling phase, the heat storage capacity of the heating network is utilized to eliminate the transmission delay effect, thereby achieving the coordinated scheduling of both electricity and heat. Shifting to the intra-day lower scheduling phase, the heat storage capacity of the heating network is utilized to enhance the operational flexibility of the power system. Simulation experiments demonstrate that the coordinated scheduling of electricity and heat in the integrated energy system can be effectively achieved through the utilization of the fictitious node method. Furthermore, the proposed multi-time-scale scheduling method, making full use of the heat storage characteristics of the heating network, can effectively suppress fluctuations in the new energy output and load demand while taking the economy into account. In this paper, it results in a 5.9% improvement in system operating economics and possesses the capacity to mitigate wind power fluctuations with an error rate of approximately 20%. This capability significantly enhances the integration of wind power as a sustainable energy source.

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Power System Resilience: The Role of Electric Vehicles and Social Disparities in Mitigating the US Power Outages

Loni,

Asadi

2024

Smart Grids and Energy

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Electrical power systems with their components such as generation, network, control and transmission equipment, management systems, and electrical loads are the backbone of modern life. Historical power outages caused by natural disasters or human failures show huge losses to the economy, environment, healthcare, and people’s lives. This paper presents a systematic review on three interconnected dimensions of (1) electric power system resilience (2) the electricity supply for/through Electric Vehicles (EVs), and (3) social vulnerability to power outages. This paper contributes to the existing literature and research by highlighting the importance of considering social vulnerability in the context of power system resilience and EVs, providing insights into addressing inequities in access to backup power resources during power outages. This paper first reviews power system resilience focusing on qualitative and quantitative metrics, evaluation methods, and planning and operation-based enhancement strategies for electric power systems during prolonged outages through microgrids, energy storage systems (e.g., battery, power-to-gas, and hydrogen energy storage systems), renewable energy sources, and demand response schemes. In addition, this study contributes to in-depth examination of the evolving role of EVs, as a backup power supply, in enhancing power system resilience by exploring the EV applications such as vehicle-to-home/building, grid-to-vehicle, and vehicle-to-vehicle or the utilization of second life of EV batteries. Transportation electrification has escalated the interdependency of power and transportation sectors, posing challenges during prolonged power outages. Therefore, in the next part, the resilient strategies for providing electricity supply and charging services for EVs are discussed such as deployments of battery swapping technology and mobile battery trucks (MBTs), as well as designing sustainable off-grid charging stations. It offers insights into innovative solutions for ensuring continuous electricity supply for EVs during outages. In the section on social vulnerability to power outages, this paper first reviews the most socioeconomic and demographic indicators involved in the quantification of social vulnerability to power outages. Afterward, the association between energy equity on social vulnerability to power outages is discussed such as inequity in backup power resources and power recovery and restoration. The study examines the existing challenges and research gaps related to the power system resilience, the electric power supply for/through EVs, social vulnerability, and inequity access to resources during extended power outages and proposes potential research directions to address these gaps and build upon future studies.

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Integrated optimization of a regional integrated energy system with thermal energy storage considering both resilience and reliability

Cited by 26 publications

References 24 publications

Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach

Optimal scheduling method of regenerative electric heating for emergency residential building heating: An affine arithmetic‐based model predictive control approach

Multi-Time-Scale Optimal Scheduling of Integrated Energy System Considering Transmission Delay and Heat Storage of Heating Network

Power System Resilience: The Role of Electric Vehicles and Social Disparities in Mitigating the US Power Outages

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