This article was submitted to the energy symposium in 2017. Unfortunately I wasn’t able to attend.
Introduction
Today there are viable alternatives to consuming electrical energy from the national grid. Solar photovoltaic (PV) cells can generate electricity that domestic consumers can use to become more self sufficient. A key challenge has always been however matching the timing of supply and demand of energy sources like sunlight, which is not always available. Thanksfully, battery technology has now improved to the point that generation and consumption needs can be more closely matched for domestic use. Add to the mix the increasing use of the electric vehicle (EV) and we have an opportunity to solve two problems with one solution.
Batteries Requirements and Sizes
Batteries these days are usually lithium polymer or lithium iron phosphates. Flow batteries also exist that do not have anodes or cathodes. Even flywheel energy storage (FES) with rotors spinning at up to 50,000 RPM is being used to store excess energy to balance supply with demand.
Any storage method needs to be managed carefully to maximise efficiency and longevity and these requirements are not always in sync with each other. Take for example an electric vehicle (EV) battery. For maximum range and utility the battery management system (BMS) should allow state of charge (SoC) in the range of 20% to 100%. However for longer battery life this range should be limited to 30% to 70%. Using an intelligent IoT gateway running ubiworx™ we can achieve a balance between maximum utility and extending battery life.
Choosing a battery size is an important consideration. In the paper “Energy self-sufficiency, grid demand variability and consumer costs: Integrating solar PV, Stirling engine CHP and battery storage” (Balcombe et al, 2015) the authors found that for a typical household that consumes 3300kWh/yr and which utilises a 6kWp solar PV installation without a battery, only 28% of the energy produced would be consumed.
The report also found that “battery capacity has a significant impact on the amount of electricity imported from the grid” with import decreasing from 55% to 20% with a 5kWh battery down to 12% when a battery with a capacity of 20kWh was installed. Battery sizes in excess of 5kWh therefore produce diminishing returns for a typical household. In the paper “Storage Solutions for Renewable Production in Household Sector” (Bianchi et al, 2014) the authors found that the optimal battery size is 4 to 5 kWh for a 3200kWh/yr household so it is clear that a size of around 5kWh is optimal for a typical domestic installation.
Electric Vehicle Battery Sizes and Charge Requirements
The Nissan Leaf is an example of a popular electric vehicle that has a battery capacity of 30kWh. According to the US EPA the Nissan Leaf can travel 172km on a full charge of its 30kWh battery, which works out at 17.4kWh per 100km. At a grid import cost of about 20c per kWh that’s €3.49 per 100km. A diesel Nissan Note uses 4.2L/100km1 which at today’s price of about €1.20 per litre would cost €5.04 per 100km. So there is definitely some saving in running costs but it is not as much as it could be (although it should be noted that EVs have other advantages such as using far less power when in slow moving traffic). The need for further savings are particularly relevant if you are using Irish grid electricity which is generated created using fossil fuels in the first place.
One way to further reduce your carbon footprint is to use a solar charging station to charge your EV. A 3kWp solar installation will generate about 3,000kWh per year in Ireland2. At 17.4kWh per 100km this would power your EV to cover which would power an average of 17,000 km per year which is certainly adequate for most commuters. A disadvantage here though is that the rate of charge from a solar PV array is going to be quite slow and also limited to hours of daylight. Even at its peak output of 3kW it is going to take 10 hours to fully charge the EV, so a battery is clearly needed here to match the demand with the supply. The maximum charge the EV could use would be the size of its own battery (30kWh in the case of the Leaf) but the battery could be smaller if is only to be used as a top-up. If we aim to keep the EV in the 30% to 70% range then in theory we would need a battery with a capacity of 12kWh (this is assuming 100% efficiency of charge and discharge, which isn’t the case of course but it gives a reasonable indication for our purposes).
Now if we then put both of these concepts together we can have a single solar PV array with one battery that both powers the home and charges the EV. We will need to double the PV size to 6kWp to create enough power for both the EV and the home but a single battery of about 15kWh should under almost all circumstances be able to power both. The problem of wasted excess capacity from the home is reduced by using the stored energy to top up the EV instead and the carbon footprint of the EV is reduced even further by availing of stored energy generated from solar. In this way the two can work together to make best use of each other’s peaks and troughs in supply and demand.
Artificially Intelligent Optimisation
If we use an intelligent IoT gateway running ubiworx™ acting as an intelligent control and battery management system (BMS) to manage the state of charge (SoC) of the EV and the electrical loads in the home will create even further opportunities for optimisation. By performing this function we can also analyse individual cells within the battery. Different cells may have different SoC values or may have different lifetimes. We can optimise charge rates and levels for each cell as well as alerting users of any potential problems down the road.
We could collect and analyse usage data per site as well as using the ubiworx IoT cloud to aggregate big data for mining for trends and patterns to identify other opportunities for optimisiation. We can use machine learning to predict failures, to learn how battery lifetime is affected by charging patterns and to also learn about usage patterns to predict upcoming energy needs. For example, it may be that a user has a short commute during the week but travels longer distances at the weekend. Or that the home energy use is lower at weekends than during the week. These patterns can be used to predict what SoC should be the target for the battery and for the EV. The SoC charge target for the EV could be increased from 70% to 80% at the weekend for example. Being able to anticipate the SoC the EV will have when the home owner returns from work or what the expected domestic electrical load will be allows the BMS
Another option is that we could even treat the EV battery as an extension to the household battery. If a large power demand is made by the house and the EV battery is at full capacity then the BMS could decide to draw some power from the EV instead of from the grid.
Conclusion and Next Steps
As we have seen combining a domestic PV installation with a battery and an inverter along with an EV battery management system using an intelligent IoT gateway can potentially yield significant reductions in the percentage of electricity imported from the grid. Optimal usage of power sources, intelligent analytics and predicted estimates of power requirements can reduce the grid import even further. Participation in peak demand shaving networks and becoming part of a smart grid are also very viable options.
A primary obstacle that needs to be removed is the high capital cost of installing solar PV. In their paper, Balcombe et al recommend a government subsidy of 24% to reduce the 4300kWh/yr break even threshold to the 3300kWh/yr level of a typical household. Ironically also a decrease in the feed in tariff would create a wider gap in the cost between imported and self generated energy which would make the capital cost easier to justify and absorb.
