The energy system of the modelled district is schematically presented in Figure 1. It consists of energy demand and district heating (DH) network model as well as a polygeneration plant model connected to external electricity and gas supply networks. In our study, the focus is on the polygeneration model and related generation scenarios for decarbonisation.

Figure 1

Modelled district energy system

In districts with small to medium-size district heating networks, generation is often concentrated to one or two locations only. For our study, and for the use of H2020 project PLANET [45], a single-point polygeneration model was created, describing a local polygeneration plant with P2H, P2G, CHP and HOB units connected to the local DH and power grids, and having at least a feeding line from the gas grid.

The energy demand feeding the polygeneration model can be covered by power and DH measurements directly, if available. Such measurements must have good enough granularity, being at least hourly measurements. Besides district’s aggregated active power consumption, a minimum measurement set must contain required DH supply temperature T_{DH, supply} and mass flow m_DHfrom the plant to the DH network and its heat consumers, and the resulting DH return temperature T_{DH, return} to the plant. Using the heat capacity of water c_p, such measurement set provides for a small to medium DH network the momentary DH consumption Q_cons,DH as follows

$Q_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{s},\mathrm{D}\mathrm{H}}=c_{\mathrm{p}} \dot{m_{\mathrm{D}\mathrm{H}}} (T_{\mathrm{D}\mathrm{H},\mathrm{s}\mathrm{u}\mathrm{p}\mathrm{p}\mathrm{l}\mathrm{y}}- T_{\mathrm{D}\mathrm{H},\mathrm{r}\mathrm{e}\mathrm{t}\mathrm{u}\mathrm{r}\mathrm{n}})$

Alternatively, a detailed enough model of the buildings’ energy consumption behaviour, the DH network dynamics and power consumption can be used. In our study, a high fidelity thermal-hydraulic model of the districts buildings and DH network, which is presented briefly in [44], was used to calculate the time and weather dependent power and heat demands as well as resulting DH supply and return temperatures and mass flows at the DH plant.

Gas-fired conventional DH production assets are not restricted to only use fossil natural gas, but can also be fired with renewable gas, i.e. biomethane from biogas or SNG. They could therefore be valuable assets in a decarbonized future, and are included in this decarbonisation analysis.

Gas-fired heat-only boilers. The thermal efficiency of a condensing gas-fired HOB, including the dependency of flue gas recovery efficiency on the incoming DH-return temperature, was modelled using theoretical curves from [46] and [47] for an excess air coefficient α= 1.05 typical for standard boilers. A linear relationship was fitted to the non-condensing temperature regime and a 3^rd degree polynomial on the condensing regime of the flue gas recovery unit (c.f. Figure 2).

Figure 2

The effect of district heating return temperature on boiler efficiency

A limit on the size of heat exchanger for flue gas heat recovery was added. Here a limitation of 70% of the theoretical maximum potential was used to fit the theoretical curve to the field measurement data of a 2.1 MW gas-fired HOB presented in [47].

Gas-fired combined heat and power units. The thermal efficiency of a CHP was modelled in a similar way as for HOB. In addition, for a requested heat output Q_CHP, the resulting power output P_CHP was modelled using the power-to-heat ratio r_CHP [48] of the CHP, which for conventional CHP units is assumed constant:

$P_{\mathrm{C}\mathrm{H}\mathrm{P}}=r_{\mathrm{C}\mathrm{H}\mathrm{P}} Q_{\mathrm{C}\mathrm{H}\mathrm{P}}$

In the scenarios where P2G was present, the plant was equipped with post-combustion carbon capture with capture efficiency of 85% [49].

The power-to-heat unit considered in our study was a high-performance heat pump, supplying the heat to district heating network.

District heating level heat pump. A heat pump providing heat at temperature levels higher than a certain threshold, e.g. 70 °C to a DH network or an industrial process, can be considered a high-performance HP. The coefficient of performance (COP, i.e. ratio of useful heat outputQ_HP to power inputP_cons,HP) of the HP is modelled using the following equation:

${COP}_{\mathrm{D}\mathrm{H}}=\frac{Q_{\mathrm{H}\mathrm{P}}}{P_{\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{s}.\mathrm{H}\mathrm{P}}}=\eta \times \frac{T_{\mathrm{S}\mathrm{I}\mathrm{N}\mathrm{K}}}{T_{\mathrm{S}\mathrm{I}\mathrm{N}\mathrm{K}}-T_{\mathrm{S}\mathrm{O}\mathrm{U}\mathrm{R}\mathrm{C}\mathrm{E}}}$

where T_SINK and T_SOURCE are the absolute temperatures [K] of heat exchanger on the hot side (sink) and cold side (source), respectively. η is a dimensionless degradation factor, describing process imperfections compared to ideal Carnot cycle. In [50], a market overview of commercially available high-temperature heat pumps reports COP-values which on average correspond to η = 0.6 (range between 0.4 and 0.7, depending on HP design) for an operation environment with T_SINK of 363.15 K (90 °C) and T_SOURCE 293.15 K (20 °C) or lower. A value of η = 0.7 corresponds to some HP designs using environmentally friendly CO₂-based refrigerant; this HP was reported to have a capacity to reach T_SINK of 383.15 K (110 °C). As a conservative estimate for our model, η = 0.6 was used for a modern high-performance HP [51]. For T_SINK,the momentary value of the DH supply temperature was used, while T_SOURCE depends on the available waste or environmental heat source.

The resulting values of heat pump COP for selected temperature ranges of heat pump source and district heating supply are shown on Figure 3.

Figure 3

The effect of heat pump source and district heating supply temperatures on coefficient of performance

A P2G unit producing SNG consists of at least a water electrolyser (WE), and a subsequent methanation unit. Optionally, if local utilization is possible, such a configuration can also produce useful waste heat and oxygen.

Polymer Electrolyte Membrane Water Electrolysis. The PEM-WE technology has experienced an increased preference in P2G applications [52]. It has a fast response, in the order of seconds and is thus able to provide grid management services, such as, e.g., load following and peak shaving [53], and was selected as technology for our study. Because of fast response time (compared to simulation time step of one hour), the PEM-WE unit could be straight-forward modelled to produce H₂ from local excess power with a simple conversion efficiency of 70% HHV (Higher heating value) [24]. Part of the energy lost in this conversion can be recovered as waste heat. In our study, a recovery factor of 0.5 was assumed for the PEM energy loss.

Methanation. In a decentralized employment supporting distributed power generation, the methanation process unit must also be responsive and suitable for load-following operation. Biological methanation has a far better load-following capability than chemical (catalytic) methanation, and laboratory tests have shown that immediate load changes from 100% to 0% and several weeks long rest periods can be achieved [54]. Also, in contrast to chemical methanation, biological methanation is tolerant to several gas impurities such as hydrogen sulphide (H₂S) and ammonia (NH₃), and is easier to handle with low operating temperatures (40-70 °C)[55]. Consequently, biological methanation was selected for our study. Because of the load-following capability, the methanation unit could be modelled using a simple thermodynamic conversion efficiency of 78%. The energy lost in this conversion can efficiently be recovered as waste heat. In our study, a recovery factor of 0.9 was assumed for the methanation energy loss.

Generation of local renewable energy using rooftop photovoltaic panels and a wind turbine, was considered as alternative electricity sources for the polygeneration model of the district.

Local on-shore wind power. For the location of the district, local wind power potential can be calculated using the Virtual Wind Farm model [56], which is part of renewables.ninja project [57].

Heat and electricity generation installations are usually operated in a certain order determined by operation costs. Selected orders assumed in our study are described below.

Conventional merit order for district heating production. In small and medium-size district heating networks, the conventional merit order is to operate the CHP as baseload unit and use the HOB as peak unit [58]. If cheap or free waste heat is available, such as P2G waste heat, this heat is usually utilized first, before using the CHP. In our study, if a HP is available within imposed power grid import limitations, it is used as intermediate unit on top of the CHP before the HOB is started. This kind of a conventional straightforward merit order, which results from the normally low net heat production cost [59] and high investment cost of the CHP, is referred to as “CHP first” merit order in our study.

Power-to-heat merit order for district heating production. In contrary to the “CHP first” merit order, the HP is used as a baseload unit within imposed power grid import limitations, CHP as intermediate unit, and HOB as peak unit. If P2G waste heat is available, this heat is utilized first, before using the HP. This novel kind of a merit order is referred to as “HP first” merit order in our study.

Power production merit order and grid limitations. The merit order of the DH production determines the power production of CHP plant. Together with the local solar PV and wind power production, the power produced by CHP can locally be utilized to cover baseload and P2H consumption, whenever possible. In case of remaining excess local renewable power exceeding a selected threshold, the P2G unit is started in the polygeneration model. In case of remaining excess power despite P2G operation at full capacity, this power was exported within the grid limits for reverse power flow, and remaining power exceeding the reverse flow limits was curtailed.

The objectives set for the district may be split into two categories: decarbonisation and self-sufficiency, and security of supply and avoided grid expansion.

Decarbonisation and self-sufficiency. For the district, the primary targets are to meet the district heating and power demand and to decarbonise this demand as completely as possible. Our study assumes that there is no net CO₂-import via the (national) power grid on annual base, if the district exports on annual base more renewable power to the power grid than it imports, regardless of the CO₂-emission levels of the power grid. Therefore, to support the decarbonisation target, one primary target for the district is also to reach, in terms of electrical energy, zero import or net export to the power grid. To achieve this, local renewable power generation (wind) power capacity is increased until zero import or net export of power is reached. For scenarios with a P2G unit, the self-sufficiency target can be to attain a level of SNG fuel production that entirely covers the local fuel needs for the operation of CHP and HOB.

Security of supply and avoided grid expansion. During extended periods with very low outdoor temperatures, there will be a peak period in DH energy consumption. At the same time, there may be a considerable risk for non-existent solar and wind power production. The local DH and power production must meet such challenging peak heating periods without exceeding import limits of the power grid.

Figure 4 presents the buildings and local district heating network in the centre of Suonenjoki.

Figure 4

Schematic diagram of Suonenjoki district heating network and building stock

The approximately 100 buildings in the area had a total floor area of ca. 116 000 m². Buildings represent several types: mainly residential but also school, hospital, office and other public and industrial buildings. Major part of the building stock was built between 1960 and 1980. Most of the buildings are connected to the district heating network but there are also other types of heating systems, such as direct electrical heating.

The total annual energy use in buildings amounts to approximately 16.7 GWh of district heat and 9.1 GWh of electricity. The climate conditions are characterized with average outdoor temperature 4.2 °C with summer high of 27.4 °C and winter low -31.8 °C. The potential of solar PV production is ca. 810 kWh/kW_p.

DH and power consumptions are dependent on both heating needs and user-patterns. To estimate these consumptions, a validated physical simulation model of the example district was used [44]. This detailed model includes residential power and domestic hot water consumption patterns, electric heating, building rooftop-PV, thermal mass and heat demands of buildings, temperature levels at buildings’ heating substations, as well as pressures, mass flows, supply and return temperatures in pipes of the district heating network.

One-year simulation runs with the weather conditions of 2016 were performed in order to obtain simulation data with hourly resolution, from which resulting DH and power consumptions (displayed in Figure 5 ) as well as DH supply and resulting return temperatures of the DH grid (Figure 6), which were used in our study.

Figure 5

Simulated district heating and power consumption in Suonenjoki district

Figure 6

District heating supply and return temperatures in Suonenjoki district

Security of supply. From Figures Figure 5 and Figure 7, it can be seen that there is a peak period in DH energy consumption in the beginning of the year (approximately 1.5 week long period with very low outdoor temperature), while at the same time almost no wind nor solar power is produced. The DH and power production must meet this challenging peak heating period so that the import limits of the power grid are not exceeded.

A baseline scenario “Baseline” describing the starting point scenario with current conventional CHP and HOB assets was created, solely based on gas-fired DH-production. CHP production capacity was set to 2500 kW DH / 1000 kW power, (at a power-to-heat ratio set to be r_CHP=0.4, typical for systems with high heat demand) [48], to reach a typical high utilization over 5000 FLH, while a HOB capacity of 4660 kW was needed to completely cover the remaining peak demand. Power grid limits for import and reverse flow to and from the district were selected to be 3000 kW i.e. 50% higher than the estimated 2000 kW power consumption peak for the district with conventional polygeneration system (c.f. Figure 5).

The first evolution scenario “noP2H-CHPfirst” for decarbonizing the power use describes the introduction of local solar and wind power to reach a 100% self-sufficiency in power on yearly basis, without any P2H or P2G assets on the DH production side.

In the subsequent scenarios, the P2H and P2H+P2G related scenarios, a lake water-source HP was added with the same DH capacity as the CHP. The “P2H only” scenarios have only the HP added, while the “P2H+P2G” scenarios have a P2G unit with a capacity set to a level that delivers the needed SNG for the CHP and HOB operation. In case of remaining excess local renewable power exceeding a selected threshold of 200 kW, the P2G unit was started. The objectives of the scenarios are summarized in Table 1 below.

For the HP added in the scenarios, our study assumes lake water as heat source. For a large Finnish lake, we approximate T_SOURCE using a yearly sine wave characterized with a minimum of 2 °C (lake bottom temperature in wintertime) and a maximum of 12 °C (summertime, higher water layers). This approximation corresponds to the measured lake water temperatures of the Finnish large lake Kallavesi (located at 62°45′N, 27°47′E, and having a maximum depth of 75 m) at 40 m depth during wintertime and 15m during summertime [60].

In the scenarios, the local wind power of the district was calculated with the Virtual Wind Farm model [56]. For this calculation, the library model of the “Vestas V90” turbine with a rated capacity of 2000 kW was selected, and a hub height of 80 m was assumed. The resulting hourly time series was multiplied to the needed total wind power capacity of each scenario.

Local solar PV power was calculated using the physical simulation model [44] of the example district In the example district, rooftop-PV was assumed to be installed on all roofs of public buildings (hospital, school, ice arena, swimming hall, etc.) having relatively good solar potential. Technically possible panel area was assumed to be 50% of this roof area. For panel azimuths and tilt angles, the available data on roof slopes were used with the exception of flat roofs, for which the assumptions made were south orientation and a slope angle of 40°, which gives optimal solar electricity production in Suonenjoki [61]. No open-field installations were assumed. The resulting local solar PV production was calculated using hourly local irradiation measurements for 2016 and the building-integrated PV sub-models [62] of the physical simulation model [44] of the example district.

As example, the resulting curves of solar and wind power generation (kW) within the district are shown in Figure 7 for the full decarbonisation scenario “P2H+P2G-HP first”.

Figure 7

Estimated wind and solar power generation within the example district, scenario “P2H+P2G-HP first”.

The results obtained in the scenarios are briefly described below, and the impact on security of heat supply and needs for power grid expansion are discussed in the end of this section.

The scenario for decarbonizing only the power use. The scenario “no P2H-CHP first” could reach with a modest 1200 kW wind power installation a full decarbonisation of the district’s power consumption, but not the DH consumption. The district’s direct net CO₂-emissions would be 4570 ton CO₂/year because of CHP and HOB operation for DH production. To reach a full decarbonisation, the needed fuel amount of 23060 MWh must be bought as SNG or biomethane from outside the district.

The scenario with heat pump and prioritised combined heat and power. The scenario “P2H only-CHP first” could reach with a modest 1500 kW wind power installation a full decarbonisation of the district’s power consumption including the power needed by the HP, but only marginally decarbonised the DH consumption. The district’s direct net CO₂-emissions would remain at the level of 4080 ton CO₂/year, i.e. only a 20% reduction compared to the baseline, because of prioritized CHP operation for DH production. To reach a full decarbonisation, the needed external 20590 MWh of renewable gas fuel must be bought as SNG or biomethane from outside the district.

The scenario with prioritized heat pump and combined heat and power. The scenario “P2H only-HP first” needed a 5200 kW wind power installation to reach a full decarbonisation of the district’s power consumption including the power needed by the HP, and decarbonized the DH consumption by 84%. The districts direct net CO₂-emissions would drop to 720 ton CO₂/year, because of prioritized HP operation for DH production, and to reach a full decarbonisation the needed external fuel amount dropped to 3640 MWh of renewable gas.

The scenario with heat pump, power-to-gas and prioritised combined heat and power. The scenario “P2H+P2G-CHP first” needed a large 16500 kW wind power installation, combined with a large 7000 kW (in terms of electrolyser power input) P2G installation, to reach a full decarbonisation of the both district’s power and DH consumption including the power needed by the HP and P2G unit. Approximately 2600 ton CO₂/year would be used by the P2G unit, corresponding to all CO₂ of the polygeneration system’s flue gas, i.e. enabling a full CO₂-reuse. However, because post-combustion carbon capture is estimated to have a capture efficiency of 85%, 390 ton flue gas CO₂/year would be lost into the air and must be obtained from other CO₂-sources, e.g. direct air capture (DAC) or imported from outside the district.

The scenario with prioritized heat pump, power-to-gas and combined heat and power. The scenario “P2H+P2G-HP first” needed only an 8000 kW wind power capacity, i.e. less than half compared to previous “P2H+P2H-CHP first” scenario due to the prioritized HP operation. The full decarbonisation of the district’s power and DH production is still reached with P2H and P2G. The needed P2G capacity would, anyhow, be dramatically reduced to 1250 kW, which is only one fifth of the previous scenario, due to increased HP heat production. The reduction in P2G capacity reduces needed investment considerably. Approximately 610 tons of CO₂/year would be used by the P2G unit, and a full CO₂-reuse would be enabled. Only 90 tons of flue gas CO₂/year would be lost into the air and must be obtained from other CO₂-sources. The resulting district heating and electricity production, electricity consumption and exchange with external electrical network for this scenario are presented on Figure 8.

Figure 8 (a-b) depicts the utilization of different generation types in DH and power production. Baseload-type utilisation of HP can be clearly seen, while the P2G plant continuously operates throughout the year with high utilisation but in an intermittent mode with many start-ups and shut-downs, capturing the wind power intermittency. CHP plant is utilised only during rather rare periods of peak heat consumption, with less than 10 start-ups of the CHP during the year. The HOB is only activated during the coldest weeks.

Figure 8

District heating production (a), power consumption (b), power production (c) and net grid exchange for the “P2H+P2G, HP first” scenario, enabling 100% decarbonisation

Security of supply and avoided grid expansion. For all scenarios, the needed DH could be supplied to the customers, even during the coldest winter week without wind and solar power production, as shown for the “P2H+P2G, HP first” scenario in Figure 8. At the same time, the estimated current power grid limitations could be met for both power export and import. This target was met despite the quite large wind power installations in the scenarios with P2G units, where 2.7–5.5 times larger wind power installation compared to the grid reverse power limit could be handled or absorbed within the district itself.

In complete decarbonisation scenario, the CHP plant is not likely to achieve high capacity utilisation (FLH). Unless the plant is not required for such purposes as provision of grid services or emergency power supply, it might turn out beneficial not to have a CHP plant in the system at all. In this case, the HOB would fulfil the remaining heat requirement not covered by waste heat from P2G and P2H units.

Decarbonisation with power-to-heat and power-to-gas. The results of a sensitivity analysis in the scenario “P2H+P2G, HP first” are shown in Figure 9. In case of decarbonisation of the modelled district when heat is generated by HOBs only (without CHP), and the system is decarbonised using P2H, then a large 6.5 MW P2G and 15 MW wind power capacity would be required. This requirement decreases substantially with first 1500 kW of HP installation, as displayed in Figure 9, showing a clearly decreasing trend in needed capacity for both P2G and wind power installations, until flattening after P2H installations reach 3 MW.

Figure 9

Heat pump vs. needed P2G and wind power capacities to reach complete decarbonisation of heating (left) and corresponding full load hours of heat production units (right)

Compared to the original scenario “P2H+P2G-HP first”, keeping the HP at 2500 kW but leaving the CHP out would have decreased the needed WP installation by 300 kW to 8200 kW and P2G installation by 320 kW_e to 880kW_e nominal sizes, which is shown in Figure 9. For very large HP installations, over 3500 kW, this difference would more or less disappear. However, at smaller HP installations, this dimensioning difference, i.e. saving, would have been much larger, over 2000 kW of the needed P2G and 1500 kW of the needed wind power capacity if capacity of P2H in the system would only be 500kW. This clear saving would however come with the loss of capacity for emergency reserves or grid services the CHP could provide for the decarbonised system.

Decarbonisation with power-to-heat and excessive wind power production. A complete decarbonisation, i.e. 100% or more reduction in the total CO₂ emissions of the district energy system can also be reached with only P2H and excess wind power, without using P2G. The scenario “P2H-HP first” was further analysed for this case, for various nominal sizes of the local wind power installation. The local wind power was utilised to cover local electricity consumption as well as consumption of the 2500 kW P2H installation, and excess wind power was fed to external electrical grid within the limits of identified existing grid interface. The fed wind power replaces average grid power production, and corresponding national grid CO₂ reduction was accounted for. The results of this sensitivity analysis in the “P2H-HP first” scenario, including the sensitivity to the CO₂-emission factors, are shown in Figure 10.

In this case, the district energy system could efficiently reach a complete decarbonisation if the national grid had considerable CO₂ emissions that could be reduced. For EU-average power grid emissions (296 gCO₂/kWh in 2016 [63]), a full decarbonisation could be reached if the local wind power installation capacity was increased from 5700 kW to 7000 kW, reaching 20% over-production annually. For the Finnish power grid, with lower average emission factor (113 gCO₂/kWh in 2016 [63]), the increase in local wind power installation capacity has to be greater, up to 9000 kW, reaching 50% annual over-production.

However, for a practically carbon-free power grid like in Sweden (13 gCO₂/kWh in 2016 [63]), this indirect way of decarbonisation could not be utilized, since practically no additional carbon reduction would be achievable. Consequently, in such clean power system, a complete decarbonisation of the heating sector cannot be reached by simply feeding wind power into the clean power grid, and decarbonisation measures must instead be taken on the heating itself e.g., by increasing capacity of heat pumps and utilization of green fuels.

In addition, the use of larger wind power installations resulted in strongly increasing curtailment losses, where 15% of added wind power was lost at a 9000 kW wind power installation, and 60% of added wind power was lost at a 15000 kW wind power installation. These significant curtailment losses could be avoided using the P2G installations.

Figure 10

Impact of wind power generation capacity on district’s self-sufficiency level (left) and total CO2 emission reduction of the corresponding district energy system (including heat and electricity) using power-to-heat

The earlier study of Kötter et al. [32] found that regional electricity and heat demand could be covered by 100% RES also in the Rhineland Palatine region with help of P2G and P2H, even if their study did not explicitly investigate district heating. In their cost-optimized wind-scenario, 56% of produced energy was covered with wind power and 19% with PV, the rest being hydropower and gas-fired CHP. In our study, no hydropower was assumed to be available. In our “P2H-only” scenarios, with P2H as baseload, 84% of local CO₂ emission reduction was obtained using PV and wind power generation. Adding P2G storage further decreases the emissions to negative total emissions. In our study, the PV panels were installed on roofs of public buildings, which limited the share of PV output in total generation (6% “P2G HP-first” scenario) and the share of wind power was larger. It is likely that availability of roof surface for PV installation limited the output of PV.

In our study, by meriting heat pump production, CHP production can be significantly decreased. Similar need for decreasing CHP production to was also observed by Salpakari et al. [43], who proposed that replacing CHP with P2H should be studied. In one of their renewable energy scenarios, significant loss of CHP production was found when used together with P2H, which made the configuration unprofitable. The full load hours used in the study of Salpakari et al. [43] were in line with the results of our study for the scenarios with prioritized heat pump and CHP, but not utilising P2G. Salpakari et al. [43] did not reach 100% decarbonization in their study, most likely because P2G was not investigated by them.