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In view of the damaging effect of carbon gasses on the environment, governments all over the globe have put in place measures and policies to reduce if not potentially remove carbon emissions in their respective nations.
The energy sector, which is highly reliant on fossil fuels is one sector that if can have a significant impact on carbon emissions. Building have been found to account for a large percentage of energy use in most countries around the globe, 40% in Europe and 50% in Africa. Thus optimizing energy use in buildings is key in reducing energy demand in Africa. One solution to this problem is the concept of Net Zero Energy Buildings and possibly Energy Positive buildings. It is with similar regard that the European Union’s Energy Performance of Buildings Directive of 2010 requires that all new buildings be nearly Zero Energy buildings This Paper discusses the definition of NZEBs, Possible Framework for the development of NZEBs in Africa, with a focus on new building projects.
It is important to note that there is currently no internationally adopted definition for an NZEB. However, for the purpose of this paper the following definition will be considered: A Net Zero Energy Building is a building that has zero net energy consumption and zero carbon emission evaluated over a period of 1 year . Thus from this definition, the main energy source from an NZEB should be an on-site renewable energy resource such as solar or wind energy. According to Torcelline et al, A ZEB should generate enough green energy on site to offset its energy requirements and possibly exceed this requirement  (energy positive building). Below are key definitions for the Net Zero Energy Buildings concept as defined by Torcelline et al.:
Net Zero Site Energy: A site ZEB produces at least as much energy as it uses in a year, when accounted for at the site.
Net Zero Source Energy: A source ZEB produces at least as much energy as it uses in a year, when accounted for at the source. Source energy refers to the primary energy used to generate and deliver the energy to the site.
Net Zero Energy Emissions: A net-zero emissions building produces at least as much emissions-free renewable energy as it uses from emissions-producing energy sources. Thus consequently offsetting its emissions
NZEBs are developed on the following core assumptions:
NZEBs should be designed such that they have a very low energy footprint, however this achievement should not compromise the comfort levels of occupants in the building. Parameters such as temperature, air quality, light intensity etc. must be monitored and controlled to ensure that the comfort of occupants is not compromised. Below are parameters to be taken into consideration when designing NZEBs.
Once the building has been set up and is operational it is necessary to evaluate the performance of the building. The IEA Task 40/Annex 52  report has identified indicators that provide useful information on the energy performance of the building. This paper considers 4 key indicators, these are:
Load cover factor (self –production): this is the fraction of the building under study’s electrical demand that is supplied by on-site electricity generation, and is given by:
Ɣ_load=(∫_(τ_1)^(τ_2)〖min[g(t)-s(t)-〗 ζ (t),l(t)]dt)/(∫_(τ_1)^(τ_2)l(t)dt)
Where g (t) is the onsite production, s (t) is the storage energy balance, ζ (t) energy losses within the system l (t) building load (demand)
Supply cover factor (Self-consumption): This is a complementary index to the load cover factor described above and is defined as the fraction of the on-site generation used by the building. This is expressed mathematically as :
Ɣ_supply=(∫_(τ_1)^(τ_2)〖min[g(t)-s(t)-〗 ζ (t),l(t)]dt)/(∫_(τ_1)^(τ_2)〖[g(t)-s(t)- ζ (t)] dt〗)
Loss of load probability: This refers to the percentage of time for which the on-site generation cannot meet the building’s demand and as such electricity must be imported from the grid. It is expressed mathematically as:
LOLP=(∫_(τ_1)^(τ_2)〖d(t)〗_(l(t)>(g(t)-s(t)-ζ(t))) )/(τ_2 〖-τ〗_1 )
Coverage: This indicator provides information on the energy balance of the building over a given time period (usually a year), a coverage of one indicates a Net Zero Energy balance. It is defined mathematically as:
coverage=(∫_(τ_1)^(τ_2)g(t) )/(∫_(τ_1)^(τ_2)l(t) )
Power grids in Africa are designed with a hierarchical approach, whilst this may have been sufficient in the past, it is becoming significantly more difficult to maintain this approach especially with the increasing presence of Distributed Energy Resources in the grid. NZEBs are considered to be prosumers (both producers and consumers) and as such they can be considered as a DER in the distribution network. This implies that NZEBs will have the similar if not the same impact on the grid, particularly the local grid since NZEB production can be considered as negligible in terms of the national production.
From the network planning perspective  the size and number of users of an NZEB is crucial to the dimensioning of feeders and associated network. Any dimensioning for both the load and supply of to the building must take into account load coincidence, higher number of users implies a lower peak load value per customer.
Again consideration must be made for the potential for reverse power flow due to DERs. Especially in the instance where the penetration of NZEBs is high. For such scenarios there is also the potential for capacity overload and over voltage . That is to say that adequate communication and control strategies should be in place in order to proper manage the impact of NZEBs on the grid. Grid Edge Intelligence is a possible solution to this problem as discussed in .
NZEBs are crucial to the development of African cities. Since most cities in Africa are now developing at an exponential rate. It is important that his development be sustainable and eco-friendly. It is also important to note that NZEBs will interact with the grid as distributed energy resources (DERs) and will consequently have the same impact as any other DER on the grid . Therefore there is the need to develop the Smart Grid, or at least the features of the Smart Grid that support and manage the variability of DERs.
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