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Self-Sufficiency The energy system proposed for the Smarthood concept is capable of achieving near full grid-independence through the use of the flexibility provided by the various system components. The aquaponic system, especially, has a positive
Table 15.4 Flexible demand of the aquaponic system
table thead tr class="header" th Component /th th Order of magnitude /th th Flexibility /th /tr /thead tbody tr class="odd" td rowspan=3 Pumps /td td 0.05–0.15 kWsube/sub Msup3/sup /td td rowspan=3 Not all pumps have to run continuously. Main processes (oxygen control, ammonia control, COsub2/sub control, tank exchanges, suspended solids control) must run continuously. Smaller processes such as pH buffer dosing, backwash routines, water exchanges or back-up oxygenation do not have to run continuously /td /tr tr class="even" td 1–3 kWsube/sub /td /tr tr class="even" td 8,76–28,26 MWhsube/sub/year /td /tr tr class="odd" td rowspan=2 Lighting /td td 80–150 W/msup2/sup /td td rowspan=2 Plants need ~4–6 h of darkness, the rest of the day they can be lit artificially. This leaves approx. 0 (summer) to 12 (winter) hours of flexible additional lighting /td /tr tr class="even" td With a capacity factor of 10–20% this leads to 28–105 MWhsube/sub/year kWsube/sub /td /tr tr class="odd" td rowspan=2 Space heating (underfloor) and aquaculture tank heating /td td 444 kWsubth/sub/msup2/sup/year /td td rowspan=2 Due to the high thermal mass of the concrete floor and the large water volume in the RAS tank, the heat load is extremely flexible /td /tr tr class="odd" td 177,8 MWhsubth/sub/year /td /tr tr class="even" td rowspan=2 Distillation unit /td td 50 kWsubth/sub MWhsube/sub/year /td td rowspan=2 The distillation unit operates on hot water (70–90 ˚C) and can be operated with a significant degree of flexibility (MemSys 2017) /td /tr tr class="odd" td 166,4 MWhsubth/sub/year /td /tr /tbody /table
effect on the overall flexibility of the system. With 95.38% power self-sufficiency, this system performs better than any other economically feasible system assessed in previous research (de Graaf 2018).
Control Architecture Facilitating a decentralised local energy economy, such as the one proposed in the Smarthoods concept, requires a platform that keeps track of all the peer-to-peer transactions occurring within the neighbourhood. The corresponding peer-to-peer network can be classified as a multi-agent system (MAS) approach, in which multiple nodes (e.g. households or utility buildings) function as independent agents with their own objective (e.g. minimise cost or maximise energy saving) and corresponding decision-making process. Such a decentralised, multi-agent decision-making approach is necessary due to the complexity of the system. There is simply too much information and too many variables for the computation of a hierarchical, top-down and centralised control architecture.
Blockchain A blockchain-based multi-agent system control architecture could potentially provide the necessary framework to accommodate a decentralised peerto-peer network. A vast number of distributed nodes ensure stability and security for the network, and an alternative to mining can be used: minting. With minting, tokens/coins are generated based on the data provided by a real-world device such as a smart energy metre. Provided that these sources of information can be trusted, i.e. that these devices can be tamper-proofed, a secure and independent ledger can be created in which various stakeholders can exchange goods (e.g. electricity) and services (e.g. demand-side management). Using smart contracts, complex services such as flexibility trading can be programmed into the control architecture of the system.
Internet of Things The constituent components within the Smarthood system, such as heat pumps, greenhouse lighting or the UASB, can all be controlled using Internet-connected sensors and actuators, known as Internet of Things. An IoT sensor network allows for the extensive acquisition of data, ranging from fish tank nutrient concentration to, for instance, battery load cycles, all on a per-time-step basis. This data can be used to verify the numerical model and optimise the dynamical control of the system.
Artificial Intelligence Optimising the control of the Smarthood system can be done by analysing the data using artificial intelligence algorithms, such as genetic programming (evolutionary algorithms) or machine reinforcement learning. With machine reinforcement learning, for instance, a set of actions and their influence on the environment are passed to the algorithm as input arguments, along with the current state of the system and a cumulative objective/cost function. An incrementally improving, heuristic decision-making process can be implemented at each household that will dynamically adapt to situations in order to find a near-optimal decision-making programme that will manage the energy flows within the house and the Smarthood. Each house can run such an algorithm, and as a result, a multi-nodal control system architecture, known as a multi-agent system (MAS), can be created that is relatively computationally inexpensive (compared to centralised control)—- and close to optimal.
Legal Barriers The highly innovative nature of various aspects of the Smarthood concept, such as the polygeneration microgrid, the multi-loop aquaponic system and the unconventional urban planning requirements, brings along a unique set of challenges to overcome. For many of these challenges, the current regulatory framework is insufficient to accommodate the developments proposed in the Smarthoods concept.
Microgrids, for instance, work best when there is a local marketplace in which various prosumers (consumers that simultaneously produce power) can engage in frictionless peer-to-peer energy trading in a free market. Market forces will then work to create a local energy market in which a fluctuating energy price will result from local supply and demand. This price fluctuation will consequently incentivise smart energy solutions such as energy storage, demand-side management or flexible energy generation. In most EU countries, a free local market is currently impossible due to regulations; taxes have to be paid for every kWh that passes through the electricity metre, the electricity price for consumers is fixed and prosumers are not allowed to participate in the energy market without the intervention of a third party called the aggregator. With the expected increase in the development of microgrid projects, regulators will have to find ways to facilitate local energy markets in order to unlock the full potential of highly integrated microgrids (see Example 15.2).
A recent advancement within the regulatory framework in the Netherlands is the introduction of the experimenteerregeling, an experimental law that allows a small number of carefully selected projects (such as de Ceuvel, example Z.1) to allow energy cooperatives to become their own distribution system operator, as if they were behind a single metre connection. This law is indicative of the awareness amongst Dutch regulatory bodies of previously mentioned legal barriers, and will therefore most likely lead to the current electricity law to be revised in the near future in order to better accommodate microgrid developments.
There are also some legal barriers in most EU countries with respect to reusing treated black water for fish and plant production, as it has to be ensured that human pathogens are fully eliminated. More information on the legal framework of aquaponics can be found in Chap. 20.