scholarly journals Enabling Technologies for Sector Coupling: A Review on the Role of Heat Pumps and Thermal Energy Storage

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8195
Author(s):  
Omais Abdur Rehman ◽  
Valeria Palomba ◽  
Andrea Frazzica ◽  
Luisa F. Cabeza
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Renewable Energy Sources ◽  
District Heating ◽  
Energy Systems ◽  
Energy System ◽  
Heat Pumps ◽  
Enabling Technologies

In order to reduce greenhouse gas emissions, current and future energy systems need to be made more efficient and sustainable. This change can be accomplished by increasing the penetration of renewable energy sources and using efficient technologies in energy generation systems. One way to improve the operation of the whole energy system is through the generation and end-use sector coupling. Power-to-heat energy conversion and storage technologies, in this view, are enabling technologies that can help in balancing and improving the efficiency of both thermal and electric grids. In the present paper, a comprehensive analysis of the role of heat pumps and thermal energy storage for sector coupling is presented. The main features of the analyzed technologies are presented in the context of smart electric grid, district heating and cooling and multi-carrier energy systems, and recent findings and developments are highlighted. Finally, the technical, social, and economic challenges in the adoption of investigated technologies are discussed.

scholarly journals Development and Analysis of a Multi-Node Dynamic Model for the Simulation of Stratified Thermal Energy Storage

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4275 ◽  
Author(s):  
Nora Cadau ◽  
Andrea De Lorenzi ◽  
Agostino Gambarotta ◽  
Mirko Morini ◽  
Michele Rossi
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Supply And Demand ◽  
District Heating ◽  
Energy Systems ◽  
High Flow ◽  
Market Penetration ◽  
Flow Rates ◽  
Smart Energy Systems

To overcome non-programmability issues that limit the market penetration of renewable energies, the use of thermal energy storage has become more and more significant in several applications where there is a need for decoupling between energy supply and demand. The aim of this paper is to present a multi-node physics-based model for the simulation of stratified thermal energy storage, which allows the required level of detail in temperature vertical distribution to be varied simply by choosing the number of nodes and their relative dimensions. Thanks to the chosen causality structure, this model can be implemented into a library of components for the dynamic simulation of smart energy systems. Hence, unlike most of the solutions proposed in the literature, thermal energy storage can be considered not only as a stand-alone component, but also as an important part of a more complex system. Moreover, the model behavior has been analyzed with reference to the experimental results from the literature. The results make it possible to conclude that the model is able to accurately predict the temperature distribution within a stratified storage tank typically used in a district heating network with limitations when dealing with small storage volumes and high flow rates.

scholarly journals Optimized Layouts of Borehole Thermal Energy Storage Systems in 4th Generation Grids

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4405 ◽  
Author(s):  
Hoofar Hemmatabady ◽  
Julian Formhals ◽  
Bastian Welsch ◽  
Daniel Otto Schulte ◽  
Ingo Sass
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Heating Temperature ◽  
Storage System ◽  
District Heating ◽  
Temperature Shift ◽  
Heat Pumps ◽  
Optimal Designs ◽  
Practical Implementation

Borehole thermal energy storage (BTES) systems are a viable option to meet the increasing cooling demand and to increase the sustainability of low-temperature district heating and cooling (DHC) grids. They are able to store the rejected heat of cooling cycles on a seasonal basis and deliver this heat during the heating season. However, their efficient practical implementation requires a thorough analysis from technical, economic and environmental points of view. In this comparative study, a dynamic exergoeconomic assessment is adopted to evaluate various options for integrating such a storage system into 4th generation DHC grids in heating dominated regions. For this purpose, different layouts are modeled and parameterized. Multi-objective optimization is conducted, varying the most important design variables in order to maximize exergetic efficiency and to minimize levelized cost of energy (LCOE). A comparison of the optimal designs of the different layouts reveals that passive cooling together with maximizing the heating temperature shift, accomplished by a heat pump, lead to optimal designs. Component-wise exergy and cost analysis of the most efficient designs highlights that heat pumps are responsible for the highest share in inefficiency while the installation of BTES has a high impact in the LCOE. BTES and buffer storage tanks have the lowest exergy destruction for all layouts and increasing the BTES volume results in more efficient DHC grids.

scholarly journals Optimal Energy Portfolios in the Heating Sector and Flexibility Potentials of Combined-Heat-Power Plants and District Heating Systems

2021 ◽  
pp. 219-234
Author(s):  
Maciej Raczyński ◽  
Artur Wyrwa ◽  
Marcin Pluta ◽  
Wojciech Suwała
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Emission Reduction ◽  
Power Plants ◽  
District Heating ◽  
Energy System ◽  
Heat Power ◽  
Heating Systems ◽  
District Heating Systems

AbstractThis chapter examines the role of centralized district heating (DH) systems in context of energy system flexibility and decarbonization. The analysis is performed by applying the model TIMES-Heat-EU. Capacity expansion and operation of the district heating generation units is mainly driven by the evolution of the district heating demand, which varies between the REFLEX scenarios. In all scenarios fuel and technology switches toward bioenergy and natural gas leading to CO2 emission reduction. Since the total amount of energy produced (both heat and electricity) is the highest in the High-RES centralized scenario, the corresponding CO2 emissions for district heating are the highest as well. The CO2 emissions can be reduced by ⁓60% in 2050 compared to 2015. Furthermore, the role of thermal energy storage and power-to-heat technologies is examined.

scholarly journals The role of cool thermal energy storage (CTES) in the integration of renewable energy sources (RES) and peak load reduction

Energy ◽  
2012 ◽  
Vol 48 (1) ◽  
pp. 108-117 ◽  
Author(s):  
Marko Ban ◽  
Goran Krajačić ◽  
Marino Grozdek ◽  
Tonko Ćurko ◽  
Neven Duić
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Renewable Energy Sources ◽  
Peak Load ◽  
Energy Sources ◽  
Load Reduction

scholarly journals Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2766 ◽  
Author(s):  
van der Heijde ◽  
Annelies Vandermeulen ◽  
Salenbien ◽  
Helsen
Keyword(s):  
Optimal Control ◽  
Energy Storage ◽  
Optimal Design ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
District Heating ◽  
Energy System ◽  
And Control ◽  
Heating Networks ◽  
Optimal Design And Control

In the quest to increase the share of renewable and residual energy sources in our energy system, and to reduce its greenhouse gas emissions, district heating networks and seasonal thermal energy storage have the potential to play a key role. Different studies prove the techno-economic potential of these technologies but, due to the added complexity, it is challenging to design and control such systems. This paper describes an integrated optimal design and control algorithm, which is applied to the design of a district heating network with solar thermal collectors, seasonal thermal energy storage and excess heat injection. The focus is mostly on the choice of the size and location of these technologies and less on the network layout optimisation. The algorithm uses a two-layer program, namely with a design optimisation layer implemented as a genetic algorithm and an optimal control evaluation layer implemented using the Python optimal control problem toolbox called modesto. This optimisation strategy is applied to the fictional district energy system case of the city of Genk in Belgium. We show that this algorithm can find optimal designs with respect to multiple objective functions and that even in the cheaper, less renewable solutions, seasonal thermal energy storage systems are installed in large quantities.

scholarly journals Grid-edge technology - Exploring the flexibility potential of a heat pump and thermal energy storage system

2019 ◽  
Vol 111 ◽  
pp. 06002
Author(s):  
Christoph Schellenberg ◽  
Laurentiu Dimache ◽  
John Lohan
Keyword(s):  
Energy Storage ◽  
Heat Pump ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Storage System ◽  
Energy System ◽  
Heat Pumps ◽  
Local Climate ◽  
Effective Manner ◽  
The Impact

Grid-edge technologies (GET) enable and amplify the impact of three emerging energy system trends: electrification, decentralisation, and digitalisation. Smart grid integrated heat pumps with thermal energy storage enable both the electrification of heating and decentralised demand response. Such power-to-heat technologies simultaneously decarbonise heating and facilitate the grid integration of more variable renewable electricity in a cost-effective manner. This may help to explore and exploit untapped wind generation potential. This study explores the flexibility potential of a domestic scale heat pump with thermal energy storage in a typical Irish home in December. The system is simulated to investigate demand-side flexibility and sensitivity to both heat pump and thermal storage capacities for three days with wind energy shares of 7%, 25%, and 60%. Using real-time electricity prices and optimising for operational cost, the implicit demand flexibility potential is quantified with different combinations of heat pump power and storage capacity. The results suggest that 33-100% of critical loads can be shifted dynamically to low-cost periods. Optimised system design depends on local climate, heat demand profile, optimisation horizon, and the type of heat pump. Optimisation with genetic algorithm yielded near-global optimal results approximately 40 times faster than with exhaustive enumeration.

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