Search

Abstract: District heating is used in many urban areas in Sweden. Almost always, the district heating utility is owned by the municipality and the municipality naturally encourages proprietors to connect their buildings to the grid, even if they cannot really force them to do so. The building owners are free to choose the best system, i.e. the cheapest one, for their need. Unfortunately, it is not always so easy to find the best solution. Mixed integer linear programming (MLIP) models might here come to help. By such computer programs it is possible to find the absolutely cheapest system of available alternatives, or even combinations among them. This paper shows how to design such a model and further how to closely depict the district heating, and electricity tariff. This is of course very important because the only interface between the proprietor of the building and the utility is found in this bureaucratic instrument. If the tariff is too high the building owners will choose other heating systems than district heating, or even worse, combining district heating with alternative base load sources. In Sweden, this has been of interest because ground-water coupled heat pumps can be profitable, operated by use of the relatively low electricity prices. In this paper we show that dual-fuel, and sometimes even triple-fuel systems, are of interest when the proprietor aims at minimising the cost for space and domestic hot-water heating. [Copyright &y& Elsevier]

This paper proposes a new method for an optimal control of the heating system at the building scale. This control is a new approach of energy planning that aims to decrease the heating consumption/expenses over a defined prediction horizon while respecting the occupants’ thermal comfort. It employs a simplified building thermal model to simulate the building thermal behavior taking into consideration the weather predictions. This approach is based on the application of Monte Carlo method, i.e., a random generator for the heating system scenarios. The aim is to determine the optimal heating plan for the prediction horizon that fulfills the constraints regarding the thermal comfort of occupants and the minimization of the energy consumption/expenses together with achieving a load shedding. [ABSTRACT FROM AUTHOR]

Abstract: Trigeneration systems, also known as Combined Heat, Cooling and Power (CHCP) systems, are interesting alternatives to supply different energy services in urban districts and in large buildings, particularly in warm areas such as Mediterranean countries. These systems can provide substantial benefits from economic, energetic, and environmental viewpoints, since the cogenerated heat can be used for heating in winter as well as cooling in summer with an absorption refrigerator. This paper develops an optimization model using Mixed Integer Linear Programming (MILP) to determine the type, number and capacity of equipment in CHCP systems installed in the tertiary sector as well as to establish the optimal operation mode for the different plant components on an hour-by-hour basis throughout the year. The objective function to be minimized is the annual total cost. The optimization model considers the legal constraints imposed to feed the surplus autogenerated electricity into the grid at a regulated feed-in tariff. The optimization model is applied to design a system providing energy services for a hospital located in the city of Zaragoza (Spain). The effects of the financial market conditions and energy prices in the optimal structure of the system are analyzed. [Copyright &y& Elsevier]

The ever-increasing demand for heating in different sectors, along with more preventative regulations on greenhouse emissions, has forced different countries to seek new alternative to heat buildings such as District Heating System (DHS). Although the traces of district heating systems can be observed over the centuries, it was not widely implemented until last two decades when the DHS become a method to design more green and energy efficient way for heating buildings. This paper tries to review the state of the art in modeling different components of the district heating systems and state the advantages as well as limitation of each method. Also, different methods used for the optimization of the DHSs have been reviewed.