Optimization of Hybrid Energy Storage Systems at the Building Level with Combined Heat and Power Generation

Yu, Dongmin; Liu, Huanan; Yan, Gangfeng; Jiang, Jing; Blond, Simon Le

doi:10.3390/en10050606

Cited by 12 publications

(12 citation statements)

References 24 publications

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“…Lead-acid batteries, as the most mature energy-type storage devices, are widely applied to shave the peak demand in a power system [33], whose maximum output (P bmax ) can be expressed as:…”

Section: Distributed Energy Storage Systemmentioning

confidence: 99%

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Sizing Hybrid Energy Storage Systems for Distributed Power Systems under Multi-Time Scales

Liu

et al. 2018

Applied Sciences

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Abstract:With the rapid development of industry, more fossil energy is consumed to generate electricity, which increases carbon emissions and aggravates the burden of environmental protection. To reduce carbon emissions, traditional centralized power generation networks are transforming into distributed renewable generation systems. However, the deployment of distributed generation systems can affect power system economy and stability. In this paper, under different time scales, system economy, stability, carbon emissions, and renewable energy fluctuation are comprehensively considered to optimize battery and super-capacitor installation capacity for an off-grid power system. After that, based on the genetic algorithm, this paper shows the optimal system operation strategy under the condition of the theoretical best energy storage capacity. Finally, the theoretical best capacity is tested under different renewable energy volatility rates. The simulation results show that by properly sizing the storage system's capacity, although the average daily costs of the system can increase by 10%, the system's carbon emissions also reduce by 42%. Additionally, the system peak valley gap reduces by 23.3%, and the renewable energy output's fluctuation range and system loss of load probability are successfully limited in an allowable range. Lastly, it has less influence on the theoretical best energy storage capacity if the renewable energy volatility rate can be limited to within 10%.

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Section: Distributed Energy Storage Systemmentioning

confidence: 99%

“…In order to improve battery lifespan, the maximum output current of the battery is limited by the installation capacity of the battery. Therefore, the initial capacity of the battery (Q b ) can be described as [33]:…”

Section: Distributed Energy Storage Systemmentioning

confidence: 99%

Sizing Hybrid Energy Storage Systems for Distributed Power Systems under Multi-Time Scales

Liu

et al. 2018

Applied Sciences

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“…As the lifetime of a battery can be seriously influenced by charging cycles, to increase the lifetime of a battery, it is preferable to reduce switching frequency when charging a battery [25]. In this paper, it is assumed that batteries for the electric vehicles need to be charged for at least one integer discrete time period (∆t) to avoid frequently changing charging states of batteries.…”

Section: -1 Integer Programming For Regulating Electric Vehicle Charmentioning

confidence: 99%

An Optimal Domestic Electric Vehicle Charging Strategy for Reducing Network Transmission Loss While Taking Seasonal Factors into Consideration

et al. 2018

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Abstract:With the rapid growth of domestic electric vehicle charging loads, the peak-valley gap and power fluctuation rate of power systems increase sharply, which can lead to the increase of network losses and energy efficiency reduction. This paper tries to regulate network loads and reduce power system transmission loss by optimizing domestic electric vehicle charging loads. In this paper, a domestic electric vehicle charging loads model is first developed by analyzing the key factors that can affect users' charging behavior. Subsequently, the Monte Carlo method is proposed to simulate the power consumption of a cluster of domestic electric vehicles. After that, an optimal electric vehicle charging strategy based on the 0-1 integer programming is presented to regulate network daily loads. Finally, by taking the IEEE33 distributed power system as an example, this paper tries to verify the efficacy of the proposed optimal charging strategy and the necessity for considering seasonal factors when scheduling electric vehicle charging loads. Simulation results show that the proposed 0-1 integer programming method does have good performance in reducing the network peak-valley gap, voltage fluctuation rate, and transmission loss. Moreover, it has some potential to further reduce power system transmission loss when seasonal factors are considered.

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“…It is worth noting that this paper is designed to verify the efficacy of the proposed algorithm for a domestic user who has already installed the aforementioned infrastructures, with no need to consider the optimal capacity for each infrastructure, because the rated capacities of the aforementioned infrastructures used in this paper are based on the references of [41,42], in which many constraints, for example, battery SOC, are considered when sizing CHP and batteries. Additionally, the depreciation of energy infrastructures is not considered in this paper.…”

Section: A Case Studymentioning

confidence: 99%

Rule Based Coordinated Control of Domestic Combined Micro-CHP and Energy Storage System for Optimal Daily Cost

et al. 2017

Applied Sciences

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This paper presents a novel control algorithm for optimising operational costs of a combined domestic micro-CHP (combined heat and power), battery and heat storage system. Using a minute by minute basic time-step, this work proposes a simple and computationally efficient rule based whole-system management, developed from empirical study of realistic simulated domestic electricity and heat loads. The CHP availability is considered in two binary states which, together with leveraging storage effectively, maximises CHP efficiency, and gives the algorithm increased real world feasibility. In addition, a novel application of a dual battery system is proposed to support the micro-CHP with each battery supplying just one of the distinctive morning and evening electrical load peaks, and thus inherently improving overall battery system lifetime. A case study is presented where the algorithm is shown to yield approximately 23% energy cost savings above the base case, almost 3% higher savings than that of the closest previous work, and 96.8% of the theoretical minimum cost. In general, the algorithm is shown to always yield better than 88% of the theoretical minimum cost, a ratio that will be considerably higher when real-world CHP limitations are factored into the theoretical minimum calculation.

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Optimization of Hybrid Energy Storage Systems at the Building Level with Combined Heat and Power Generation

Cited by 12 publications

References 24 publications

Sizing Hybrid Energy Storage Systems for Distributed Power Systems under Multi-Time Scales

Sizing Hybrid Energy Storage Systems for Distributed Power Systems under Multi-Time Scales

An Optimal Domestic Electric Vehicle Charging Strategy for Reducing Network Transmission Loss While Taking Seasonal Factors into Consideration

Rule Based Coordinated Control of Domestic Combined Micro-CHP and Energy Storage System for Optimal Daily Cost

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