05/00694 Modelling and optimization of district heating and industrial energy system — an approach to a locally deregulated heat market

2005 ◽  
Vol 46 (2) ◽  
pp. 102
Keyword(s):  
District Heating ◽  
Energy System ◽  
Industrial Energy ◽  
Modelling And Optimization

State estimation models of district heating networks for integrated energy system considering incomplete measurements

2021 ◽  
Vol 282 ◽  
pp. 116105
Author(s):  
Suhan Zhang ◽  
Wei Gu ◽  
Haifeng Qiu ◽  
Shuai Yao ◽  
Guangsheng Pan ◽  
...  
Keyword(s):  
State Estimation ◽  
District Heating ◽  
Energy System ◽  
Integrated Energy System ◽  
Heating Networks ◽  
Estimation Models

scholarly journals A Method for Optimizing and Spatially Distributing Heating Systems by Coupling an Urban Energy Simulation Platform and an Energy System Model

Resources ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 52
Author(s):  
Annette Steingrube ◽  
Keyu Bao ◽  
Stefan Wieland ◽  
Andrés Lalama ◽  
Pithon M. Kabiro ◽  
...  
Keyword(s):  
District Heating ◽  
Energy Systems ◽  
Energy System ◽  
Heat Pumps ◽  
Energy Simulation ◽  
Heating Systems ◽  
Optimal Amount ◽  
Urban City ◽  
Urban Energy ◽  
Building Level

District heating is seen as an important concept to decarbonize heating systems and meet climate mitigation goals. However, the decision related to where central heating is most viable is dependent on many different aspects, like heating densities or current heating structures. An urban energy simulation platform based on 3D building objects can improve the accuracy of energy demand calculation on building level, but lacks a system perspective. Energy system models help to find economically optimal solutions for entire energy systems, including the optimal amount of centrally supplied heat, but do not usually provide information on building level. Coupling both methods through a novel heating grid disaggregation algorithm, we propose a framework that does three things simultaneously: optimize energy systems that can comprise all demand sectors as well as sector coupling, assess the role of centralized heating in such optimized energy systems, and determine the layouts of supplying district heating grids with a spatial resolution on the street level. The algorithm is tested on two case studies; one, an urban city quarter, and the other, a rural town. In the urban city quarter, district heating is economically feasible in all scenarios. Using heat pumps in addition to CHPs increases the optimal amount of centrally supplied heat. In the rural quarter, central heat pumps guarantee the feasibility of district heating, while standalone CHPs are more expensive than decentral heating technologies.

scholarly journals Day-ahead Market Modelling of Large-scale Highly-renewable Multi-energy Systems: Analysis of the North Sea Region Towards 2050

2020 ◽  
Author(s):  
Juan Gea Bermúdez ◽  
Kaushik Das ◽  
Hardi Koduvere ◽  
Matti Juhani Koivisto
Keyword(s):  
North Sea ◽  
Large Scale ◽  
Unit Commitment ◽  
District Heating ◽  
Energy Systems ◽  
Energy System ◽  
Computational Time ◽  
Integer Variables ◽  
The North ◽  
The North Sea

This paper proposes a mathematical model to simulate Day-ahead markets of large-scale multi-energy systems with high share of renewable energy. Furthermore, it analyses the importance of including unit commitment when performing such analysis. The results of the case study, which is performed for the North Sea region, show the influence of massive renewable penetration in the energy sector and increasing electrification of the district heating sector towards 2050, and how this impacts the role of other energy sources such as thermal and hydro. The penetration of wind and solar is likely to challenge the need for balancing in the system as well as the profitability of thermal units. The degree of influence of the unit commitment approach is found to be dependent on the configuration of the energy system. Overall, including unit commitment constraints with integer variables leads to more realistic behaviour of the units, at the cost of increasing considerably the computational time. Relaxing integer variables reduces significantly the computational time, without highly compromising the accuracy of the results. The proposed model, together with the insights from the study case, can be specially useful for system operators for optimal operational planning.

scholarly journals Evaluating the Potential Contribution of District Heating to the Flexibility of the Future Italian Power System

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 584
Author(s):  
Chiara Magni ◽  
Sylvain Quoilin ◽  
Alessia Arteconi
Keyword(s):  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
District Heating ◽  
Energy System ◽  
Heat Pumps ◽  
Electricity Sector ◽  
Potential Contribution ◽  
The Future ◽  
Promising Solution

Flexibility is crucial to enable the penetration of high shares of renewables in the power system while ensuring the security and affordability of the electricity dispatch. In this regard, heat–electricity sector coupling technologies are considered a promising solution for the integration of flexible devices such as thermal storage units and heat pumps. The deployment of these devices would also enable the decarbonization of the heating sector, responsible for around half of the energy consumption in the EU, of which 75% is currently supplied by fossil fuels. This paper investigates in which measure the diffusion of district heating (DH) coupled with thermal energy storage (TES) units can contribute to the overall system flexibility and to the provision of operating reserves for energy systems with high renewable penetration. The deployment of two different DH supply technologies, namely combined heat and power units (CHP) and large-scale heat pumps (P2HT), is modeled and compared in terms of performance. The case study analyzed is the future Italian energy system, which is simulated through the unit commitment and optimal dispatch model Dispa-SET. Results show that DH coupled with heat pumps and CHP units could enable both costs and emissions related to the heat–electricity sector to be reduced by up to 50%. DH systems also proved to be a promising solution to grant the flexibility and resilience of power systems with high shares of renewables by significantly reducing the curtailment of renewables and cost-optimally providing up to 15% of the total upward reserve requirements.

Simulation und Optimierung kombiniert/A simulation-based framework for operational optimization of industrial energy systems

2020 ◽  
Vol 110 (01-02) ◽  
pp. 12-17
Author(s):  
Niklas Panten ◽  
Heiko Ranzau ◽  
Thomas Kohne ◽  
Daniel Moog ◽  
Eberhard Abele ◽  
...  
Keyword(s):  
Synthetic Data ◽  
Cost Savings ◽  
Energy Systems ◽  
Decisive Role ◽  
Optimization Methods ◽  
Energy System ◽  
Significant Cost ◽  
Operational Optimization ◽  
Simulation Based ◽  
Industrial Energy

Die optimierte Betriebsweise von industriellen Energiesystemen ist eine Schlüsseltechnologie, um signifikante Kosteneinsparpotenziale durch Steigerung der Energieeffizienz und -flexibilität zu heben. Weil dabei eine Vielzahl dynamischer und stochastischer Einflüsse berücksichtigt werden müssen, spielt die Simulation des Energiesystems eine entscheidende Rolle. Zur Evaluierung unterschiedlicher Betriebsoptimierungsverfahren wird ein simulationsgestütztes Framework vorgestellt, welches bei KI (Künstliche Intelligenz)-Algorithmen unter anderem für das Anlernen mit synthetischen Daten verwendet werden kann.   The optimized operation of industrial energy systems is a key technology to unlock significant cost savings by increasing energy efficiency and flexibility. Since a variety of dynamic and stochastic influences must be considered, the simulation of the energy system plays a decisive role. A simulation-based framework is presented for evaluating various operational optimization methods, which can also be used for learning based on synthetic data with AI (artificial intelligence) algorithms.

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