The resulting waste heat transportation networks and selected utilities, considering a waste heat price of 25e/MWh, are represented in Fig 4.5.
The total investment costs for heat exchange and transport, the operating costs, the revenues from heat supply and electricity production as well as the payback time are indicated in Tab.
4.4 in detail for the waste heat valorisation sinks and in aggregated form for the remaining
4.3. Case study
Figure 4.5: Waste heat valorisation and selected utility technologies for a waste heat price of 25e/MWh
sites. The investment costs for the waste heat valorisation equipments are given in Tab. 4.5.
The payback time reaches 3 years for waste heat valorisation in nearby sinks (Differdange, Esch-sur-Alzette), and increases up to 5.6 years for more distant sinks. With an average of 2.4 years, it should be mentioned that, under the prices considered above, the actual payback time of the CHP plants strongly varies according to the amount of heat delivered, with values ranging between 1 and 13 years.
Table 4.4: Revenues and costs
Sink [-] Total
in-vestment costs [Me]
Yearly operating
costs [Me/a]
Heat supply revenues
[Me/a]
Electricity production
revenues [Me/a]
Payback time [a]
Differdange 5.9 1.8 3.8 - 3.0
Esch-sur-Alzette 14.4 4.4 9.2 - 3.0
Niederkorn 4.6 1.0 2.1 - 4.2
Oberkorn 3.9 0.7 1.4 - 5.4
Soleuvre 6.7 1.1 2.3 - 5.6
Sum of sinks with CHPs
9.9 15.7 8.8 11.0 2.4
Table 4.5: Investment costs
Differdange 5.9 2.5 0.6 1.4 1.4
Esch-sur-Alzette 14.4 6.0 2.3 3.0 3.0
Niederkorn 4.6 1.4 1.4 0.9 0.9
Oberkorn 3.9 1.0 1.6 0.7 0.7
Soleuvre 6.7 1.6 3.2 1.0 1.0
The absolute and relative (transfer to demand ratio, in parenthesis) waste heat loads for time periodst1,t2andt4, as well as the pipe diameter per connection are given in Tab. 4.6. Instead of selecting the pipe with the largest diameter to cover the highest load demand int1, the diameter related to the load of periodt2is selected to avoid excessive investment costs for the short duration oft1. Due to the important heat demand, the heat supplied to Esch-sur-Alzette is provided by two different processes, the off-gases after post-combustion and the off-gases of the cooling water jacket.
Table 4.6: Transferred waste heat loads
Sink [-] Source [-] Load at
The transportation heat losses, in absolute value and as percentage of the transferred load, are summarised in Tab. 4.7. They range between 43 and 55 W/m, which is in line with studies on specific pipe losses (Boehm [25]: 60 W/m, Perpar et al. [165]: 49 - 58 W/m). The heat losses are
4.3. Case study
compensated in this case study by additional waste heat taken from the upper temperature interval and not from the heating utility. The remaining gas consumption, due to the design of the pipe size and the production interruptions int3andt5are given in the same table. They amount to 3% of the total energy demand for heating.
Table 4.7: Heat losses
For this case study, the valorisation of the waste heat does not need further complex network design and optimisation efforts, as the measures are rather straightforward. In the case of waste heat valorisation from the steel plant in Differdange, several optimisation opportunities arise. First, considering the size of the plant, it should be checked with the steel plant manager if one of the sources with a load above 6’022 kW, the heating demand of Niederkorn, is closer to the town than the clustering point assumed. This would allow for a reduction of the pipe costs (20% of the annualised costs). Second, due to the transportation centralised in Differdange, there is the opportunity to use one common heating utility instead of four separate ones.
This would further reduce the specific investment costs of the utility (36% of the annualised costs). Finally, the optimisation method selected various processes as heat sources, although either the loads of the EAF off-gases after post-combustion or at the end of the water jacket are sufficiently high to cover the heating demand of the four towns. The costs of the heat exchangers at the source (22% of the annualised costs) would then be reduced. The waste heat valorisation in Esch-sur-Alzette can be improved by joining the two heat sources of the steel plant at the level of the transportation pipes, reducing the pipe investment costs.
However, before the detailed network layouts and utility selection is finalised, the design selection should be further discussed with the local actors to ensure the inclusion of potential constraints influencing the layout of the networks (e.g. ease of access of the heat sources)
or additional opportunities (e.g. the existence of service tunnels from the steel plants to the towns).
The low payback times, relevant profits for the ESCo and important revenues for the waste heat transport demonstrate the economic relevance and competitiveness of regional waste heat valorisation for the Luxembourgish domestic sector in 2015, given an adequate heat price. It is also relevant to note that, while 41% of the available waste heat could theoretically be valorised to cover the considered heat demand, only 26% of the excess heat can be economically valorised when constraints of fuel prices, investment costs, energy losses, etc. are included.
By considering aspects of economic viability, as well as real population and energy demand densities, this method generates more realistic estimations than other large scale waste heat potential assessments (e.g. Persson and Werner [170]).
4.4 Discussion
A multi-period, MILP-based, method for the optimal regional valorisation of industrial waste heat by ESCos is proposed in this work. It maximises the profits stemming from electricity production and the supply of heat, while considering infrastructure investment and operating costs.
One of the main strengths of the proposed method is the integrated approach to waste heat valorisation. It does not focus solely on the actual WH valorisation, but also includes the possibility of electricity production as well as the optimal selection of the heating utility type necessary as a backup or main heating equipment. Another major contribution is that the formulation allows the consideration of a potential closure of the heat source plant within a few years. Instead of using the typical lifetime of the technical equipment, the lifetime ne of the annualisation factor of Eq. 4.10 can be used to calculate the investment costs over the prospective remaining lifetime of the plant. Potential investors have the opportunity to assess the annualised investment costs compared to the waste heat price set by the industry, and either require a supply guarantee or a decrease of the waste heat price, thus reducing the investment risk. Finally, while the targeted users are mainly ESCos, potential waste heat supply sites can also use this approach to determine the optimal heat selling price generating the highest revenues. This aspect is of particular importance in case the waste heat valorisation implies changes on manufacturing processes. Normally, industries are resistant to such changes but sufficiently high revenues might prove to be adequate incentive for process modification.
A drawback of the optimisation formulation is that the global heat losses over several temper-ature intervals k are overestimated, as these are determined independently for each interval.
Calculating the losses over all intervals would have led to a non-linear problem, which the authors made efforts to avoid to take advantage of desirable characteristics of MILP formula-tions (e.g. generation of a global solution). Another current shortcoming is the temperature
4.4. Discussion
limitation to 400°C reflecting material constraints, thus excluding high-temperature waste heat valorisation. This could be avoided by including material type selection as a variable in the problem, although this would further increase its complexity. Finally, the fact that several heat sources or sinks can be situated at the same location is not reflected in the method, although it would potentially reduce utility, heat exchanger and pipe investment costs. This decision is intentional, as the sharing of equipment depends on the temperature level of sources and sinks and mixing of streams cannot be automatically assumed. This issue is, however, solved in the network design and optimisation stage which would be completed in more detail based on the analysis presented here.
The main significance of this work lies in the development of a new method for energy service companies focusing on the optimal valorisation of regional waste heat and the simultaneous selection of the best heating utility technology. The optimisation method expressed here leads to two main contributions in the field of integrated large-scale energy supply networks.
First, a novel waste heat valorisation problem is formulated for ESCos instead of industries or municipalities. The outcomes differ from similar works insofar as the configuration selec-tion is based on highest profitability instead of lowest operating and investment costs. The method also considers that competing sinks can have different energy prices, an aspect rarely considered which, however, influences the selection of the valorisation opportunities.
Second, the method improves regional waste heat valorisation methods by also considering op-timal heating technology and standard pipe diameter selection. With this integrated approach, the solutions regarding energy provision proposed by the ESCo are more thoroughly assessed, as potential interactions between these aspects are taken into account simultaneously.