15.4 Method
A neighbourhood of 50 households was assumed a ‘Smarthood’, with a decoupled multi-loop aquaponics facility present that is capable of providing fish and vegetables for all the 100 inhabitants of the Smarthood.
For the detailed modelling of the Smarthood, a hypothetical reference case of a suburban neighbourhood in Amsterdam was used, consisting of 50 households (houses) with an average household occupancy of 2 persons per household (100 persons total). In addition, one urban aquaponic facility consists of a greenhouse, aquaculture system, a UASB and a distillation unit. The dimensioning of the different components is motivated using data for a typical Dutch household and greenhouse (see Table 15.1).
15.4.1 The Energy System Model
An Energy System Model (ESM) was made that can simulate the energy flows of a wide range of components, whose main specifications are shown in Table 15.2. The ESM is capable of calculating energy flows for each component for each hour of the year.
Table 15.1 Food and energy requirements per persona/household in the Netherlands
table thead tr td/td thAverage (per capita/year)/th thTotal (100 persons)/th thSource/th /tr /thead tbody tr th colspan=4Food/th /tr tr tdVegetable consumption (the Netherlands)/td td 33 kgsupa/sup (whereas u73 kg/u are recommended /td td 7300 kg /td td EFSA (2018) /td /tr tr class=“odd” tdRequired greenhouse area/td td Approx. 4 msup2/sup /td td 400 msup2/sup /td td Estimated based on min. consumption recommendation /td /tr tr class=“even” tdFish consumption/td td 20 kg /td td 2000 kg /td td FAO (2015) /td /tr tr class=“odd” tdRequired aquaculture volumesupb/sup/td td 0.2 msup3/sup /td td 20 msup3/sup /td td Estimated /td /tr tr th colspan=4 Energy/th /tr tr class=“odd” tdHousehold heat consumption (Netherlands)/td td 6500 kWhsubth/sub/house/ year /td td 325 MWhsubth/sub/year /td td CBS (2018) /td /tr tr class=“even” td rowspan=2RAS electricity consumption/td td rowspan=2 0.05–0.15 kWsube/sub/msup3/sup /td td 1–3 kWsube/sub /td td rowspan=2 (Espinal, pers. communication) /td /tr tr class=“odd” td 8,76–28,26 MWhsube/sub/ year /td /tr /tbody /table
supa/supThe average Dutch person eats 50 kg of vegetables per year. However, only 33 kg of vegetables that can be grown in hydroponics systems, which are fruiting vegetables 31.87 g/day, brassica vegetables 22.11 g/day, leaf vegetables 12.57 g/day, legume vegetables 19.74 g/day, stem vegetables 4.29 g/day
supb/supConsidering a max. fish density of 80 kg/msup3/sup
Table 15.2 Production components
table thead tr class=“header” thComponent/th th Size /th th Specifications /th /tr /thead tbody tr class=“odd” tdSolar PV/td td 40 kWsubp,e/sub /td td Eta: 0.15 /td /tr tr class=“even” tdUrban wind turbine/td td 20 kWsubp,e/sub /td td Eta: 0.33 /td /tr tr class=“odd” tdHeat pump/td td 10 kWsubp,e/sub /td td COP: 4.0 /td /tr tr class=“even” tdCHP/td td 20 kWsubp,e/sub /td td Etasubel/sub: 0.24, Etasubth/sub = 0.61 /td /tr tr class=“odd” tdFuel cell/td td 10 kWsubp,e/sub /td td Eta: 0.55 /td /tr tr class=“even” tdElectrolyser/td td 20 kWsubp,e/sub /td td Eta: 0.45 /td /tr tr class=“odd” tdBattery/td td 200 kWh /td td Eta: 0.90 /td /tr tr class=“even” tdHot water tank/td td 930 kWh /td td 40–60C /td /tr tr class=“odd” tdHydrogen tank/td td 1000 kWh /td td 30 kg of Hsub2/sub storage /td /tr /tbody /table
The energy system was modelled in MATLAB using energy profile data for Amsterdam obtained through DesignBuilder. The numerical time-series model incorporates a wide selection of energy technologies, listed in Table 15.2 with their relevant specifications (Fig. 15.4).
The Energy System Model (ESM) uses simple conditional statements for the decision-making process, i.e. it is a rule-based control system. In the current version of this model, the control is centralised, with the objective of self-consumption
Fig. 15.4 The aquaponics microgrid model (F. de Graaf 2018), showing the energy balances for power (upper diagram) and heat (lower diagram) for the reference case (Amsterdam)
maximisation for the system as a whole (in a future version, the control architecture will be decentralised, see Sect. 15.5). The conditional statements to achieve this can be stated as follows:
Keep the heat storage to a minimum.
Forecast the predicted inflexible electricity production and consumption.
(a) If the battery will be full, turn on flexible consumption.
(b) If the battery will be empty, turn on flexible generation.
By keeping the heat storage to a minimum, the buffer for flexible energy balancing is maximised. If there is an overproduction of inflexible electricity (i.e. electricity production that cannot be flexibly scheduled or controlled, such as solar or wind), the heat pump can be turned on to create a buffer provided by hot water storage and the thermal mass of the aquaponic RAS system. Conversely, if there is an underproduction of electricity, flexible generation such as the CHP and the fuel cell can be turned on, thereby utilising the thermal storage capacity.
For both heat and power, the energy balance is equivalent to
$P_{gen,flex} + P_{gen,inflex} + P_{grid} = P_{cons,inflex} + P_{cons,flex} + P_{storage}$ (15.1)
Flexible generations include the heat pump, Combined Heat and Power (CHP) unit, fuel cell, battery and smart/flexible devices (e.g. aquaponic pumps). Wind, solar photovoltaics (PV) and solar collectors are classified as inflexible generation. Non-flexible devices make up the bulk of electricity consumption, especially in winter (due to the need for instant lighting) (Fig. 15.5).
Fig. 15.5 Example of the energy flows (Sankey diagram) of a possible integrated microgrid configuration at De Ceuvel (de Graaf 2018), including a biodigester for the production of biogas. This particular configuration does not include the Combined Heat and Power unit that is present within the Smarthood concept, nor does it take into account a large aquaponics facility