Assessment of the regionalised demand response potential in Germany using an open source tool and dataset

Heitkoetter, Wilko; Schyska, Bruno U.; Schmidt, Danielle; Medjroubi, Wided; Vogt, Thomas; Agert, Carsten

doi:10.1016/j.adapen.2020.100001

Cited by 35 publications

(5 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The aim of these two works is to provide a methodology that could help the involved actors perform a first economic analysis for the participation in the electricity market. Heitkoetter et al [27] assess the flexibility potential at the NUTS-3 level for Germany by defining a set of load-shifting parameters: flexible load share, time frame constraints, load increase and decrease constraints, and load-shifting costs. Powerto-heat technologies are identified as the option that provides the highest DR potential.…”

Section: Demand Response Investigation In Industrial Thermal Processesmentioning

confidence: 99%

Assessing the Flexibility Potential of Industrial Heat–Electricity Sector Coupling through High-Temperature Heat Pumps: The Case Study of Belgium

Magni,

Peeters,

Quoilin

et al. 2024

Energies

View full text Add to dashboard Cite

Thermal processes represent a significant fraction of industrial energy consumptions, and they rely mainly on fossil fuels. Thanks to technological innovation, highly efficient devices such as high-temperature heat pumps are becoming a promising solution for the electrification of industrial heat. These technologies allow for recovering waste heat sources and upgrading them at temperatures up to 200 °C. Moreover, the coupling of these devices with thermal storage units can unlock the flexibility potential deriving from the industrial sector electrification by means of Demand-Side Management strategies. The aim of this paper is to quantify the impact on the energy system due to the integration of industrial high-temperature heat pumps and thermal storage units by means of a detailed demand–supply model. To do that, the industrial heat demand is investigated through a set of thermal process archetypes. High-temperature heat pumps and thermal storage units for industrial use are included in the open-source unit commitment and optimal dispatch model Dispa-SET used for the representation of the energy system. The case study analyzed is Belgium, and the analysis is performed for different renewable penetration scenarios in 2040 and 2050. The results demonstrate the importance of a proper sizing of the heat pump and thermal storage capacity. Furthermore, it is obtained that the electrification of the thermal demand of industrial processes improves the environmental impact (84% reduction in CO2 emissions), but the positive effect of the energy flexibility provided by the heat pumps is appreciated only in the presence of a very high penetration of renewable energy sources.

show abstract

Section: Demand Response Investigation In Industrial Thermal Processesmentioning

confidence: 99%

Assessing the Flexibility Potential of Industrial Heat–Electricity Sector Coupling through High-Temperature Heat Pumps: The Case Study of Belgium

Magni,

Peeters,

Quoilin

et al. 2024

Energies

View full text Add to dashboard Cite

show abstract

“…Many active management methods such as demand response (DR) [3], [4], DG curtailment [5], reactive power compensation, and network reconfiguration, are effective for improving the controllability of DNs and mitigating security violations [6], [7]. There are various kinds of demand-side resources [8], [9] in DNs that have different response characteristics such as reducible load [10] and transferable load [11]. DG output curtailment [5] is a significant measure of active management on the supply side because it can alleviate over-voltage problems during peak power periods.…”

Section: A Indices I J K Ijmentioning

confidence: 99%

A Multi-objective Chance-constrained Information-gap Decision Model for Active Management to Accommodate Multiple Uncertainties in Distribution Networks

Zhang

Liu

et al. 2023

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

The load demand and distributed generation (DG) integration capacity in distribution networks (DNs) increase constantly, and it means that the violation of security constraints may occur in the future. This can be further worsened by short-term power fluctuations. In this paper, a scheduling method based on a multi-objective chance-constrained information-gap decision (IGD) model is proposed to obtain the active management schemes for distribution system operators (DSOs) to address these problems. The maximum robust adaptability of multiple uncertainties, including the deviations of growth prediction and their relevant power fluctuations, can be obtained based on the limited budget of active management. The systematic solution of the proposed model is developed. The max term constraint in the IGD model is converted into a group of normal constraints corresponding to extreme points of the max term. Considering the stochastic characteristics and correlations of power fluctuations, the original model is equivalently reformulated by using the properties of multivariate Gaussian distribution. The effectiveness of the proposed model is verified by a modified IEEE 33-bus distribution network. The simulation result delineates a robust accommodation space to represent the adaptability of multiple uncertainties, which corresponds to an optional active management strategy set for future selection.

show abstract

“…Examples on national level are: SynErgie [19], Pilot Project DSM Bavaria [20], refrigerated warehouses store energy for smart energy grid (FlexLast) [21]. Commercial and industrial enterprises have large DR potentials [22], which can be divided into cross-sectional technologies [23] and energy-intensive production processes [24]. However, in order to exploit the full environmental and economic DR potential in the industrial and commercial sectors, aspects such as dynamic pricing [25], sector coupling, onsite generation, and onsite energy storage need to be considered in an integral analysis.…”

Section: Dr In the Industrial And Commercial Sectormentioning

confidence: 99%

Demand Response Analysis Framework (DRAF): An Open-Source Multi-Objective Decision Support Tool for Decarbonizing Local Multi-Energy Systems

et al. 2022

View full text Add to dashboard Cite

A major barrier to investments in clean and future-proof energy technologies of local multi-energy systems (L-MESs) is the lack of knowledge about their impacts on profitability and carbon footprints due to their complex techno-economic interactions. To reduce this problem, decision support tools should integrate various forms of decarbonization measures. This paper proposes the Demand Response Analysis Framework (DRAF), a new open-source Python decision support tool that integrally optimizes the design and operation of energy technologies considering demand-side flexibility, electrification, and renewable energy sources. It quantifies decarbonization and cost reduction potential using multi-objective mixed-integer linear programming and provides decision-makers of L-MESs with optimal scenarios regarding costs, emissions, or Pareto efficiency. DRAF supports all steps of the energy system optimization process from time series analysis to interactive plotting and data export. It comes with several component templates that allow a quick start without limiting the modeling possibilities thanks to a generic model generator. Other key features are the access and preparation of time series, such as dynamic carbon emission factors or wholesale electricity prices; and the generation, handling, and parallel computing of scenarios. We demonstrate DRAF’s capabilities through three case studies on (1) the DR of industrial production processes, (2) the design optimization of battery and photovoltaic systems, and (3) the design optimization and DR of distributed thermal energy resources.

show abstract

Assessment of the regionalised demand response potential in Germany using an open source tool and dataset

Cited by 35 publications

References 21 publications

Assessing the Flexibility Potential of Industrial Heat–Electricity Sector Coupling through High-Temperature Heat Pumps: The Case Study of Belgium

Assessing the Flexibility Potential of Industrial Heat–Electricity Sector Coupling through High-Temperature Heat Pumps: The Case Study of Belgium

A Multi-objective Chance-constrained Information-gap Decision Model for Active Management to Accommodate Multiple Uncertainties in Distribution Networks

Demand Response Analysis Framework (DRAF): An Open-Source Multi-Objective Decision Support Tool for Decarbonizing Local Multi-Energy Systems

Contact Info

Product

Resources

About