Methodology for evaluating the transition process dynamics towards 4th generation district heating networks

Ten questions concerning modeling of distributed multi-energy systems

Smart energy grids include smart thermal and electrical grids. One of the links between them is the combined heat and power (CHP) plant, which supplies both heat and power to the grid. CHPs are designed for stable heat and electric loads and their ability to cope with peaks and lows needs to be improved. This paper explores technical solutions aimed at improving CHP flexibility, considering the potential transition to the 4th generation district heating (4GDH). CHP flexibility extends its operating time and improves the energy efficiency of the system. The solutions examined include coupling CHPs with electric boilers and TES, which will help balance heat and power loads and allow to introduce RES to the system. In this study, these technical solutions are compared in terms of natural gas consumption, heat rejection reduction, and the share of heat supplied to the system by the CHP. The results of this study show that when 150 000 m3 TES and 40 MW electric boiler are integrated into the Tallinn DH system, natural gas consumption can be reduced by 36% and heat rejection by 38%.

Improving CHP flexibility by integrating thermal energy storage and power-to-heat technologies into the energy system

With the present trend toward smart grids and integrated energy systems, the potential benefits achieved by developing integrated planning and operation solutions crossing multiple energy sectors become recently recognizable. This paper investigates the problem of optimal planning for a large-scale heat pump (HP)—a component that links electric and heat utilities together, from an integrated perspective. The proposed method assures an optimal system design with the minimum expense on both capital expenditure and operating expense for the heat network and the electrical network, given that the optional HP locations are already provided together with other technical and economic information needed for executing the planning exercise. The operational flexibility of the HP, i.e., the ability of reducing its electricity consumption from time to time, is also integrated into the planning method. The value of the proposed solution is demonstrated throughout a case study that resembles a live planning exercise conducted for a green field area in Denmark.

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Integrated Planning of a Large-Scale Heat Pump in View of Heat and Power Networks

The goal of this paper was to evaluate heat loss and the demand of district heating (DH) in the context of the fourth generation DH concept using a data-driven approach. The heat loss profile was calculated with GIS Zulu© (software (8.0.0.7539, Politerm, LLC, St.Petersburg, Russia) using eight various states of insulation, detailed information on thermal conductivity, internal heat transfer coefficient, and geometry of the concrete trench. There is a strong correlation between the heat sold and the average annual outdoor temperatures. The outstanding episodes are extremely rare, and the difference in the overall pattern is elusive. The results of the annual heat production and annual heat loss analyses were compared using three different estimation methods. The new method was the only one that showed a positive effect after the complete modernization of thermal insulation. The actual proportion of heat loss is much higher at 16%, while the actual heat delivery is less than anticipated at 85–86% only. The trend of the normative approach is correct but cannot determine changes in network heat loss due to aging. The method focuses on the effects of the state of insulation and actual supply temperature levels. The transition to smart energy systems includes strategic and progressive energy planning, as well as new pricing rules and tariffs. Thus, the method presented is the first step in the transition towards the fourth generation DH networks.

https://www.mdpi.com/1996-1073/13/17/4505/pdf

Eduard Latõšev

Papers

Evaluation Factor for District Heating Network Heat Loss with Respect to Network Geometry