Combined heat & power generation using smart heat grid
|Document type:||Conference Papers|
|Author(s):||Christian Johansson, Fredrik Wernstedt, Paul Davidsson|
|Title:||Combined heat & power generation using smart heat grid|
|Conference name:||International Conference on Applied Energy (ICAE)|
|Organization:||Blekinge Institute of Technology|
|Department:||School of Computing (Sektionen för datavetenskap och kommunikation)
School of Computing S-371 79 Karlskrona
+46 455 38 50 00
|Abstract:||Combined heat and power (CHP) generation is often used
when building new district heating production. CHP makes
it possible to simultaneously produce electricity and heat, thus maximizing the energy efficiency of the primary fuel.
The heat is used in the connected district heating system while the electricity is sold on the local power market. In a CHP plant it is not possible to separate the physical process of producing heat and electricity, which may cause suboptimal behaviour when high spot prices for power do not coincide with high heat load demand.
This paper presents the design and implementation of a
system which makes it possible to control the heat load demand in a district heating network in order to optimize the CHP production. By using artificial intelligence technology in order to automate the run‐time coordination of the thermal inertia in a large amount of buildings, it is possible to achieve the same operational benefits as using a large storage tank, albeit at a substantially less investment and operational cost.
The system continuously considers the climate in each
participating building in order to dynamically ensure that
only the best suited buildings at any given time are actively
participating in load control. Based on the dynamic indoor
climate in each individual building the system automatically
controls and coordinates the charging and discharging of
the buildings thermal buffer without affecting the quality of
This paper describes the overall function of the system
and presents an algorithm for coordinating the thermal
buffer of a large amount of buildings in relation to heat
load demand and spot price projections. Operational data from a small district heating system in Sweden is used in order to evaluate the financial and environmental impact of using this technology. The results show substantial benefits of performing such load control during times of high spot price volatility.
|Summary in Swedish:||Agentbaserad optimeringsmodell för kraftvärmeproduktion inom fjärrvärmesystem. Smart heat grid, kraftvärme, fjärrvärme, laststyrning|
|Subject:||Computer Science\Artificial Intelligence
|Keywords:||mart heat grid, combined heat and power, district heating, optimization, load control|