Modular hybrid battery storage system for peak-shaving and self-consumption optimization in industrial applications

Böttiger, Michael; Paulitschke, Martin; Beyer, Richard; Neumann, Lorin; Bocklisch, Thilo

doi:10.1016/j.egypro.2018.11.064

Cited by 8 publications

(5 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where s B,c and s B,d are binary variables indicating that charging or discharging takes place in the respective time step and P B,c,max and P B,d,max are the maximum charging and discharging power, respectively. Finally, inequalities (11) and (12) ensure that the heat pump has to either be operated between a minimum and a maximum power or be switched off:…”

Section: Optimization Problem Formulationmentioning

confidence: 99%

“…In [11], this was expanded to a HESS with a heat pump and heat storage device while also adding load peak shaving with the same motivation of reducing stress on the distribution grid. For an industrial consumer, load peak shaving can reduce costs due to capacity pricing of their grid connection [12]. For household consumers, however, feed-in and load peak shaving do not increase the profitability of a given energy storage device under German legislation.…”

Section: Introductionmentioning

confidence: 99%

“…After an adaptation interval passed, the horizon is moved forward and the optimization is carried out again using any newly available information. Although some of these studies do not explicitly name their strategy accordingly, references [4,6,7,[10][11][12] use the MPC scheme and demonstrate its ability to handle complex control problems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Impact of Model and Forecast Uncertainties on the Performance of the Model Predictive Control of a PV-Battery-Heat Pump-Heat Storage System

Gelleschus¹,

Bocklisch²

2023

Atlantis Highlights in Engineering

Self Cite

View full text Add to dashboard Cite

Recent research has shown that model predictive control (MPC) is a practical tool for the realization of an intelligent single-or multi-use energy management for both single and hybrid energy storage systems. Based on a system model and forecasts of external influences, such a controller will find the supposedly optimum decision to take in the immediate future. However, this decision will only be optimal for the given forecast and model. The inevitable model and forecast uncertainties may lead to decisions that are mathematically infeasible. Usually, underlying control loops ensure system stability and safety. However, uncertainties can be detrimental to the performance of the MPC, especially in multi-use applications, which have been shown to be preferable in practice due to a more economical usage of the storage devices.For this study, the authors carried out various analyses on the impact of both model and forecast uncertainties on the performance of the MPC in the case of a PV-Battery-Heat Pump-Heat Storage system in a single-family house providing self-consumption optimization and grid relief. Concerning the impact of model uncertainties, the use case was simulated repeatedly, varying both structure (linear and quadratic) and parameters of the optimization model. The impact of forecast uncertainties was investigated by simulating with real and ideal forecasts and identifying "typical" forecast errors that led to deviations in the system's behaviour using statistical methods. The results show that the influence of forecast uncertainties is usually higher than that of model uncertainties, but large model uncertainties may drastically alter the MPC's usage of a hybrid energy storage system. The identification of the most influential uncertainties forms the basis for developing a more robust MPC-based energy management technique.

show abstract

Section: Optimization Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impact of Model and Forecast Uncertainties on the Performance of the Model Predictive Control of a PV-Battery-Heat Pump-Heat Storage System

Gelleschus¹,

Bocklisch²

2023

Atlantis Highlights in Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…Braeuer et al [7] assessed the economic potential to install BSS for German small and medium sized companies and analysed which BSS capacity is optimal for the revenue stream peak shaving. Böttinger et al [8] developed a simulation model for lithium stationary batteries to reduce operating costs and optimize system lifetime in a manufacturing company. Oudalov et al [9] designed an optimal operating strategy and model for BSS to reduce peak loads in industrial grid.…”

Section: Existing Battery Applications For Peak Shaving In Manufacturingmentioning

confidence: 99%

“…This is often a significant cost component of electrical energy for the companies and depends on the highest peak production load. Energy storage systems were used, studied and integrated in manufacturing plants to reduce peak loads and increase savings for the companies by different researchers [6][7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Why should the automated guided vehicles’ batteries be used in the manufacturing plants as an energy storage?

et al. 2021

View full text Add to dashboard Cite

This paper examines to what extent automated guided vehicles’ (AGV) batteries can be used as a mobile electrical energy storage to increase energy flexibility and reduce peak loads in manufacturing plants. First, it is indicated, what demand response and peak shaving in manufacturing mean. Then, existing battery applications for peak shaving are presented. Finally, the benefits and potential of using AGVs as energy storage to reduce peak loads in the company are illustrated, after an approximate cost calculation for peak shaving of a company with AGV batteries are performed in a use case scenario considering AGV availability during manufacturing. The results of the approximate cost calculation show that it can be beneficial for companies to use AGV batteries as an energy storage in manufacturing plants to reduce their peak loads.

show abstract

Life Cycle Assessment of Energy Storage Technologies for New Power Systems under Dual‐Carbon Target: A Review

Yi,

Chang,

et al. 2024

Energy Tech

View full text Add to dashboard Cite

Aiming at the grid security problem such as grid frequency, voltage, and power quality fluctuation caused by the large‐scale grid‐connected intermittent new energy, this article investigates the life cycle assessment of energy storage technologies based on the technical characteristics and performance indicators. First, the new power system under dual‐carbon target is reviewed, which is compared with the traditional power system from the generation side, grid side, and user side. Based on the power characteristics of the new power system, the energy storage mechanism and energy storage characteristics of mechanical energy storage, electrochemical energy storage, chemical energy storage, electromagnetic energy storage, and thermal energy storage are described. Then, compared with the existing research strategies, a comprehensive life cycle assessment of energy storage technologies is carried out from four dimensions: technical performance, economic cost, safety assessment, and environmental impact. Moreover, the suitable scenarios and application functions of various energy storage technologies on the power generation side, grid side, and user side are compared and analyzed from the working principle, key technologies, advantages and disadvantages, and technical difficulties of energy storage technologies. Finally, combined with the energy storage technologies in the electricity market, four profit models are analyzed.

show abstract

Modular hybrid battery storage system for peak-shaving and self-consumption optimization in industrial applications

Cited by 8 publications

References 14 publications

Impact of Model and Forecast Uncertainties on the Performance of the Model Predictive Control of a PV-Battery-Heat Pump-Heat Storage System

Impact of Model and Forecast Uncertainties on the Performance of the Model Predictive Control of a PV-Battery-Heat Pump-Heat Storage System

Why should the automated guided vehicles’ batteries be used in the manufacturing plants as an energy storage?

Life Cycle Assessment of Energy Storage Technologies for New Power Systems under Dual‐Carbon Target: A Review

Contact Info

Product

Resources

About