Residential Solar Load Analysis: Heat Pump + EV

Last updated: November 2026

A heat pump and an electric vehicle can change both how much electricity a home uses and when it uses it. A yearly bill total cannot show whether charging overlaps with solar production or whether winter heating dominates the remaining imports.

Residential solar load analysis makes those differences visible. This guide follows the existing workflow: gather meter data, separate household, heat-pump and EV demand, compare it with production, then assess PV size, storage and controls. The worked profiles are illustrative assumptions, not measured households or software-generated forecasts.

SurgePV publishes this post and sells solar design software.

What Is Residential Solar Load Analysis (and Why It Matters Now)

Load analysis maps a home’s electricity consumption across time. Annual totals support an initial energy balance, but the timing matters whenever self-consumption, time-varying tariffs, storage or export constraints affect the design.

A kilowatt measures power at a point in time; a kilowatt-hour measures energy over a period. A charger can draw substantial power during a short session without using that power all day. A heat pump can draw less power for many hours and still use more daily energy. Keep those two quantities separate throughout the assessment.

As an illustrative contrast, two homes can each use 10,000 kWh annually while one consumes mainly during daylight and the other mainly overnight. The annual load is identical, but their direct use of PV will differ. Neither their self-consumption percentage nor their savings follows from the annual total alone.

The import and export contract determines the value of that timing. Some arrangements reward exported energy differently from avoided imports; others include time-varying prices or settlement rules. Read the actual tariff rather than assigning a country-wide price ratio.

SurgePV’s published scope includes energy-yield and financial modeling. It does not specify native interval-load imports, heat-pump libraries or EV dispatch controls. Demonstrate any required detailed load workflow before relying on it in a proposal.

Where Load Analysis Sits in the Design Process

Begin load analysis alongside the roof and site assessment. Its findings inform:

• PV array sizing and string layout
• Inverter selection and sizing
• Battery capacity and chemistry choice
• Shadow analysis and yield forecasting
• Self-consumption and ROI modeling
• Tariff selection and time-of-use optimization

Keep energy modeling separate from the electrical service and circuit assessment. Interval averages can inform energy economics but may hide short-duration peaks. The responsible electrical designer must still assess equipment ratings, protection, service capacity and the applicable requirements.

The Three-Load Problem: Base Load, Heat Pump, EV

Modern residential load profiles for electrified homes have a layered structure. Treating them as a single curve obscures the design problem; decomposing them into three layers makes the design problem tractable.

Layer 1: Base Load

Base load here means all household electricity other than the separately modeled heat pump and EV. It may include refrigeration, lighting, cooking, electronics, ventilation and water heating if that is not already included in the heat-pump layer.

Use the household’s records rather than a generic family-size allowance. Occupancy, home working, cooking habits and other appliances can change both daily energy and its timing. Even the overnight minimum is not perfectly constant: refrigerators cycle and equipment may run on timers.

If meter data already includes the heat pump and EV, adding a full base profile on top of it would double-count demand. Submetered records are preferable when available. If disaggregation is estimated from signatures, label the uncertainty and preserve the measured whole-home total as a reconciliation check.

Layer 2: Heat Pump

Heat-pump demand depends on building heat loss, weather, equipment performance and controls. Thermal output capacity is not the same as electrical input. A heating-system assessment should establish the heat demand before it is converted into an electrical profile.

The Energy Saving Trust heat-pump guide explains coefficient of performance, or COP, as heat delivered per unit of electricity. A single rated COP does not describe every operating condition. Obtain the relevant performance data for the actual equipment and account for auxiliary electrical loads where applicable.

Heating demand in a cold climate may be concentrated in periods of limited PV output. A home with substantial cooling can have a different seasonal pattern. Domestic hot water adds another schedule, so distinguish space heating, cooling and water heating in the records.

Within a day, controls and occupancy can matter as much as outdoor temperature. Do not assume every home uses an overnight setback or an early-morning recovery period. Ask how the system actually operates and whether comfort constraints allow any change.

Layer 3: EV Charging

EV demand depends on driving, charging losses and where charging occurs. Start with the vehicle’s measured wall-energy records where available. If estimating from mileage, state the assumed energy per distance, the share charged at home and whether charging losses are already included.

The US Department of Energy’s Alternative Fuels Data Center charging guide distinguishes AC Level 1 and Level 2 charging. It also explains that charging time depends on the battery, state of charge, vehicle charger and supply equipment. A connector’s rating is not a promise that the vehicle draws that power throughout a session.

Model the actual parking window. A car away from home all weekday cannot absorb midday rooftop surplus there. A daytime charging assumption may be reasonable for some households, but it must be agreed rather than silently substituted for observed behavior.

Charging scenarios to compare include immediate charging on arrival, a tariff-based timer, and solar-aware charging where compatible equipment and vehicle availability permit it. Keep the required departure energy fixed when comparing them so the apparent savings do not come from leaving the driver short of charge.

Why the Layered View Is Necessary

A combined load curve that just shows total kW over time is actually harder to design against than the three layers stacked. Stacking lets you ask the right questions in the right order:

1. How much base load overlaps with production in each season?
2. When does heating or cooling run, and what comfort limits constrain it?
3. When is the EV connected, and what charge is required before departure?

Each layer has different leverage. EV charging may be flexible within a parking window. Heating may have limited flexibility within comfort and equipment constraints. Some appliances can be rescheduled while others cannot. Model the agreed flexibility of this household, not a universal percentage.

Getting the Right Data: 15-Minute Intervals vs Monthly Bills

Load analysis quality is bounded by data quality. The available sources, in descending order of usefulness:

15-Minute Interval Data

Quarter-hourly data can reveal timing that monthly bills hide. A complete non-leap year contains 365 × 24 × 4 = 35,040 quarter-hour intervals; a leap year contains 35,136. These are calendar counts, not a guarantee that an export contains a complete record.

Inspect missing and duplicated timestamps, daylight-saving changes, units and the meter boundary. A value may represent interval kWh or average kW; multiplying power by the interval length converts it to energy. Preserve the original export and document how gaps are handled.

The Green Button initiative provides a standardized way for participating utilities to share usage information. Availability, history and interval length depend on the provider. Request the export with the account holder’s consent and check what it actually contains.

For other regions, ask the supplier or meter-data service for the available interval history and permission process. Do not assume that every smart meter supplies the same resolution or that an in-home display app exposes the complete billing record.

Hourly Data

Hourly data can support a preliminary energy-matching model but averages shorter events. Use the finest reliable interval suited to the decision and align production and consumption on a common time basis.

Averaging should preserve energy totals. It should not be used to claim that instantaneous service demand or inverter overload has been assessed. Those require equipment and electrical-design checks beyond an hourly energy balance.

Monthly Bills

Monthly bills are useful for checking seasonal totals and reconciling an interval export. If they are the only records available, construct clearly labeled low-, central- and high-overlap scenarios rather than presenting a synthetic profile as measured behavior.

A reference profile can be a starting assumption, but it cannot reveal the home’s actual charging window. Ask for occupancy, travel and heating-control information, and explain which design decisions remain sensitive to those answers.

Pre-Solar Baselines vs Post-Solar Behavior

Separate observed consumption from proposed behavior changes. A homeowner may agree to move some charging to daylight, but savings should not assume that every flexible load moves perfectly whenever solar is available.

Existing PV changes the meaning of a utility import record. Net grid imports are not total household consumption. Reconstruct the energy balance using generation, export and storage records where relevant before adding new loads.

Keep an unchanged-behavior case alongside the controlled case. That comparison shows what the proposed controller or schedule must achieve and makes the customer’s responsibilities visible in the proposal.

Heat Pump Load Profiles , Hourly, Daily, Seasonal

The heat pump layer drives most of the seasonal mismatch in residential PV. Understanding its shape in detail is what separates a good design from a great one.

Annual Distribution by Month (Northern Europe Example)

The following assumed monthly electrical-demand schedule totals 4,500 kWh. It illustrates a winter-heavy load, not the measured performance of a 12 kW heat pump or a typical UK house. No equipment sizing or floor-area benchmark should be inferred from it.

November through February totals 2,530 kWh in this example, or about 56.2% of annual heat-pump electricity. That is a calculation from the table, not a regional statistic. Compare the assumed load with a site-specific PV series before drawing conclusions about winter coverage.

Daily Profile by Season

Build the daily profile from observed operation or a documented thermal model. Check space-heating demand, hot-water cycles, auxiliary heaters and circulation pumps. A daily total alone does not tell you which of those loads overlaps with solar.

For winter, inspect cold periods and recovery after temperature setbacks. For summer, separate hot water from cooling where both exist. When a generic profile is necessary, label it and keep an alternative operating schedule in the sensitivity analysis.

COP Changes with Operating Conditions

Use the manufacturer’s performance map for the relevant outdoor and delivery temperatures. Avoid applying one nominal COP to an entire year or assuming that every air-source model behaves alike in cold weather.

As simple arithmetic, supplying 12 kWh of heat at an assumed COP of 3 requires 4 kWh of electricity; at an assumed COP of 2 it requires 6 kWh. These are illustrative ratios, not equipment specifications. Auxiliary consumption would need to be included on a consistent boundary.

Smart Controls and Thermal Storage

Thermal storage may move some heat production into a more favorable electricity period. Its usefulness depends on usable storage, heat loss, comfort limits and the effect of operating temperature on heat-pump efficiency.

Compare the original control strategy with the proposed one using the same comfort objective. Preheating that raises indoor temperature unnecessarily can increase heat loss. Higher water temperatures can also change performance. Shifting electrical demand is therefore not automatically an equal-energy operation.

EV Charging Profiles , Schedules, Power Levels, Behavior

The EV layer is structurally simpler than the heat pump layer but more behaviorally variable. Three variables determine the profile: charger power, scheduling strategy, and weekly mileage.

Power and Energy Per Charge Session

Charging duration depends on energy required and the sustained power actually accepted. For a first arithmetic check, divide energy by power, then account for losses and any power reduction during the session.

These selected powers are arithmetic examples, not electrical ratings or charger recommendations. Actual duration also depends on vehicle limits, state of charge, load management and interruptions. Check the equipment documentation and installation design before assigning a power profile.

Charging Strategies and Their PV Implications

Immediate charging: starts when the vehicle is connected. If arrival is after solar production ends, the session will use grid or stored energy. Summer evening overlap should be calculated rather than assumed to be zero all year.

Tariff-based timer: charges during the contracted lower-price window. This can reduce cost without increasing direct solar use. Keep price optimization separate from self-consumption in the results.

Solar-aware charging: varies charging within the equipment’s supported range to use available surplus. It needs compatible controls, a connected vehicle and enough time to reach the required departure charge. Include a fallback when sunlight is insufficient.

Combined schedule: uses solar where practical and another charging window to meet the remaining requirement. Compare the complete bill, including export opportunity cost and any tariff conditions. A more complex strategy is not automatically cheaper for every household.

EV Load Profile Examples

Keep daily and annual assumptions consistent. If an illustrative vehicle requires 12 kWh at the wall every day of a non-leap year, the annual total is 4,380 kWh. A commute-only schedule with weekends excluded produces a different total and must use the actual number of charging days.

For a two-EV household, create a separate parking and departure schedule for each vehicle. A shared charger or household power limit can prevent both from following their preferred schedule simultaneously. Preserve those constraints in the combined model.

For solar-diversion charging, calculate available surplus after other simultaneous loads. The same surplus cannot be assigned to the heat pump, the stationary battery and the vehicle at once. Keep a clear dispatch priority so the energy balance can be audited.

The annual mileage can remain unchanged while the source of charging energy changes. That is the useful comparison: identical transport service, different timing and cost, with any added controller cost included.

Combined Load Stack: Building the 8,760-Hour Profile

Once you have the three layers characterized, the combined load stack is the sum of the three at each 15-minute or hourly timestep across a full non-leap year. This gives 8,760 hourly intervals or 35,040 quarter-hour intervals when complete. Use the actual calendar and time-zone convention for the data.

Construction Steps

1. Start with a measured baseline. Identify whether it includes existing heating, EV charging, PV or storage. Reconcile it with bills before adding or subtracting any component.
2. Add only future incremental loads. Use the heating design and vehicle schedule to model planned additions. If an existing load is replaced, remove the corresponding old consumption on a documented basis.
3. Align the time series. Match interval boundaries, time zones, leap days and daylight-saving treatment. Retain gap flags rather than silently replacing missing values with zeros.
4. Check monthly and annual totals. Explain differences from observed bills or submeter records. Choose acceptance tolerances appropriate to data quality rather than using a universal percentage.
5. Compare alternative schedules. Keep energy services, comfort and departure requirements consistent. Label each scenario so the customer can distinguish observed behavior from a proposed operating change.

Why Modeling Each Layer Separately Pays Off

A single combined curve cannot answer the most important design questions: “What if the homeowner shifts EV charging to daytime?” “What if a buffer tank lets the heat pump run during PV peak?” “What if a battery is sized to cover the evening base load only?” Each of these scenarios changes one layer at a time. A modular load stack lets you re-simulate quickly; a flat curve forces you to start over.

A layered model also helps review future changes: alter one documented load at a time and compare the resulting imports, exports and cost.

Sizing PV to Match the Load: Three Illustrative Examples

PV sizing depends on usable roof area, site yield, load timing and the customer’s objective. The following scenarios retain three contrasting climates but use explicit arithmetic assumptions. They are not real projects, product demonstrations or recommended system sizes.

Example 1: UK Home, Heat Pump and Single EV

Assume annual demand of 9,800 kWh: 4,500 kWh for heating, 4,300 kWh for charging and 1,000 kWh of other demand. This deliberately chosen breakdown is not a typical-household benchmark. The EV is assumed to be away during weekday daylight and connected in the evening.

Suppose an initial site study estimates 900 kWh per kWp annually. This yield is an assumption for comparing sizes, not a verified Manchester output. The roof survey must establish how many modules actually fit after obstructions and required access are accounted for.

The table gives annual energy only. It cannot establish self-consumption, savings or payback without the interval match and tariff. Increasing array size can increase useful energy while also increasing exports; assess both rather than selecting the option with the highest self-consumption percentage.

Example 2: German Home, Heat Pump and Two EVs

Assume annual demand of 12,500 kWh: 5,500 kWh of heat-pump electricity, 6,000 kWh for two EVs and 1,000 kWh of other demand. One car is available during daylight; the other is usually available overnight. Again, these are selected inputs rather than survey results.

Assume the east-west roof provides 950 kWh per kWp annually for the preliminary comparison. The direction of each roof plane must still be modeled separately when timing matters. An annual average alone does not describe the shape of the morning and afternoon production.

Daytime vehicle availability creates an opportunity to use production directly, but it does not determine a fixed self-consumption percentage. Apply the vehicle’s departure requirement, charger limit and actual available surplus. If thermal storage is proposed, have the heating designer define its constraints before assigning any load shift.

Example 3: US Sunbelt Home, Heat Pump and EV

Assume annual demand of 14,200 kWh: 5,800 kWh for heating and cooling, 4,400 kWh for the EV and 4,000 kWh for all other loads. The other-load figure excludes cooling to avoid counting it twice.

Compare an assumed 7 kWp option producing 12,200 kWh annually with a 9 kWp option producing 15,700 kWh. These retained example outputs are assumptions, not verified Phoenix simulations. A site-specific weather and shading model must replace them before proposal use.

Cooling may overlap with solar in summer, while evening charging may fall within a higher-priced import window. That combination makes timing important, but it does not prove a battery pays for itself. Calculate the energy it actually shifts and the marginal value of those intervals.

Sizing by Region Without Fixed Ratios

Climate affects resource and heating or cooling demand, but a regional ratio cannot substitute for site design. Use a preliminary energy-balance calculation as a screening step, then apply roof, equipment, grid and economic constraints.

Divide the desired annual generation by a defensible specific yield to obtain a first-pass capacity. Explain that annual matching does not imply hourly matching. For shaded or multi-plane roofs, model the actual arrangement rather than increasing capacity by a generic percentage.

Compare feasible sizes on total annual bill effect, capital cost and operating assumptions. Include a smaller feasible option when useful: it gives the customer a view of the incremental value of extra modules, instead of forcing a choice between the largest system and no project.

Battery Sizing for Combined HP + EV Households

Battery sizing is where the most expensive sizing mistakes happen. The simple rule “match daily consumption” produces oversized, expensive batteries that never reach payback. The right approach uses the load stack and asks how much capacity actually displaces grid imports at the price the battery cycle costs.

The Cost-of-Cycled-Energy Constraint

Battery value depends on what each cycle avoids and what it gives up. For a solar-charged battery, account for export revenue forgone, conversion losses, operating costs and the cost of the installed system. For grid charging, use the charging tariff and any contract restrictions.

There is no universal 2026 cost per cycled kWh in this guide. Installed price, usable capacity, degradation, efficiency and actual throughput vary by product and household. Calculate a project-specific case and show what happens if annual cycling is lower than expected.

A useful dispatch check is to compare the value of delivered energy with the opportunity cost of the charging energy. If 1 kWh is stored, less than that may be delivered after losses. The avoided import value applies to delivered energy, while forgone export income applies to the energy that would otherwise have been exported.

Sizing Rule for HP and EV Homes

Size storage from the interval energy balance and required services, not a fixed ratio of battery capacity to PV nameplate. Compare candidate usable capacities with the same assumptions for reserve, efficiency, charge power and discharge power.

Track how often the battery fills, how much useful energy it delivers and how much capacity sits unused. A larger battery may improve backup duration while adding little annual bill saving. Keep those benefits separate so the customer understands what the extra expenditure buys.

Power is a separate constraint from capacity. A battery with enough stored kWh may still be unable to supply the simultaneous heat pump and charger. Conversely, a high power rating does not imply enough energy for a long outage. Use the product documentation and the electrical design for both limits.

Backup Is a Separate Sizing Question

A whole-day average is a weak starting point for backup design because outages do not occur only on average days. List the essential loads, expected duration, permitted load shedding and how the system behaves when the grid is absent.

Confirm that the proposed installation supports the required backup operation, including isolation, control and any restart constraints. An ordinary grid-connected solar system should not be assumed to power the home during an outage simply because the sun is shining.

If the customer wants heating during a winter outage, use a winter demand case and a justified available-energy assumption. Reserve held for backup also reduces the capacity available for routine bill optimization. Make that tradeoff visible in the proposal.

Battery and Heat Pump Dispatch

There is no blanket rule that a battery should never feed a heat pump in winter. The economic result depends on the source of charging energy, tariff timing, losses and competing loads. Backup priorities can also justify a different dispatch from the cheapest routine operation.

Model the heat pump’s required service and comfort constraints first. Then determine whether stored energy is available and valuable during the relevant intervals. Do not count a hypothetical sunny-day battery cycle as representative of every winter day.

Load Shifting and Smart Controls

Controls can improve the match between generation and demand, but the size of the benefit depends on the household. Compare feasible schedules before buying more equipment and avoid promising a universal self-consumption uplift.

EV Charging Diversion

Solar-aware charging needs the vehicle connected during production and a compatible controller that can respond within supported limits. Check minimum charging power, response behavior, phase configuration and fallback settings in the actual product documentation.

Keep a departure deadline and minimum energy requirement in the model. A controller that waits indefinitely for solar may maximize a narrow self-consumption metric while failing the driver’s needs. Include any grid top-up required to meet the agreed schedule.

Heat Pump PV Synchronization

A heat-pump control input may allow an energy-management system to request operation during favorable periods. The interface’s existence alone does not prove how much energy can move. Equipment compatibility, hydraulic design and comfort conditions still determine the permitted strategy.

Ask the heating installer to approve the proposed temperature and timing changes. Compare resulting electrical consumption as well as timing: thermal losses or a different operating temperature can offset part of the apparent benefit.

Hot Water Diversion

A hot-water store can provide flexibility where its controls and safety requirements permit it. Compare the useful heat delivered, standing losses and alternative heating method. A resistive diverter and a heat pump do not deliver the same heat per unit of electricity.

Give comfort and water-system safety requirements priority over surplus capture. Do not change required hygiene cycles or temperature protections to improve a chart. The designer responsible for the water-heating system should approve the operating schedule.

Combined Effect

Model all controls together after checking each individually. The EV, thermal store and stationary battery can compete for the same surplus, so summing their separate savings would overstate the combined benefit.

Also distinguish self-consumption from self-sufficiency. Self-consumption is the share of PV generation used on site under the stated accounting boundary. Self-sufficiency is the share of household demand supplied by the system. A home can use nearly all of a small array’s generation while still buying much of its electricity from the grid.

Neither percentage establishes off-grid capability. Autonomy requires enough energy and power through the relevant low-generation periods, with suitable controls and equipment. Report the metric the customer actually cares about rather than substituting the most favorable percentage.

ROI Math: What Heat-Pump and EV Households Save

Bill savings follow the interval energy balance and the actual tariff. A large annual load can create more opportunities for useful PV, but neither a heat pump nor an EV guarantees a favorable return.

Bill Reduction Components

The following is an illustrative annual arithmetic example, not a tariff quote or battery simulation. Assume 7,200 kWh of PV generation, 5,400 kWh used directly on site and 1,800 kWh exported. Assume import value of £0.30/kWh and export value of £0.15/kWh.

This simplified example excludes storage losses, time-varying rates, maintenance, replacements and financing. If an assumed installed cost were £14,500, dividing it by £1,890 gives simple payback of approximately 7.7 years under those omissions. That is not discounted payback or an internal-rate-of-return calculation.

If some on-site use comes through a battery, replace the direct-use row with separate direct and battery-delivered energy. Record charging energy, losses and exports so the annual balance closes. Do not describe all energy sent into storage as energy that avoided imports.

Sensitivity to Tariff Structure

Use the customer’s actual import and export contracts. Ofgem’s Smart Export Guarantee guidance explains that participating suppliers set their own rates and terms, with export payments based on meter readings. There is no single SEG rate to assign to every British home.

For time-varying tariffs, price each interval or the applicable settlement period. Include standing charges that remain payable and any restrictions associated with an EV, battery or export plan. Compare complete bills rather than multiplying all avoided imports by the highest advertised rate.

Run a lower export-value case, an unchanged-behavior case and a lower solar-output case. Keep changes separate first, then combine a defensible downside scenario. This reveals whether the proposal depends mainly on equipment performance, a tariff assumption or customer behavior.

A full investment assessment should also document capital cost, useful life, replacements, degradation, financing and the discount rate. Use the financial-modeling workflow to discuss the required outputs and reviewer-approved assumptions.

Common Sizing Mistakes to Avoid

Most avoidable errors arise when a model silently changes the household, tariff or equipment boundary. Use the following checks before presenting a size recommendation.

Mistake 1: Sizing on Annual kWh Alone

A system can match yearly consumption while exporting in summer and importing through winter. Annual balance is a screening metric, not proof of independence or bill elimination. Compare monthly and interval results before selecting the final size.

Show the remaining imports and exports beside the annual production figure. If the customer wants winter heating coverage, make that season visible rather than hiding it inside a whole-year average.

Mistake 2: Treating EV Charging as a Fixed Solar Load

A midday charging profile is only useful when the car is available and the owner accepts that schedule. Record arrival, departure and required charge. Compare actual behavior with the proposed controlled case rather than replacing one with the other.

For households with irregular travel, include a schedule sensitivity. A controller may help within the available window but cannot move a car that is parked at work into the home’s solar-production period.

Mistake 3: Oversizing the Battery

More capacity does not guarantee more useful throughput. Inspect seasonal state of charge, discharged energy and power limits for each candidate size. Include the cost of the extra capacity and any backup benefit separately.

Do not apply a universal battery-to-PV ratio as an economic ceiling. The appropriate choice depends on tariffs, backup reserve, load shape and the actual system’s operating limits.

Mistake 4: Ignoring the Heat Pump’s Operating Conditions

A rated COP is not an annual electrical-consumption forecast. Use the actual equipment information and heating design, including delivery temperatures and auxiliary energy where relevant. Reconcile the result against meter data if the system is already operating.

Keep heating-system sizing with the qualified heating designer. The solar analysis should use that evidence rather than infer a heat-pump specification from bedroom count alone.

Mistake 5: Designing Only for Today’s Loads

Ask about planned changes such as another EV, cooling, an extension or altered occupancy. Model credible additions as separate scenarios. Do not add an unexplained percentage of capacity and describe it as future-proofing.

Check physical expansion options, inverter compatibility and connection limits before promising later growth. A future-load scenario should identify both its assumed timing and what would need to change in the installation.

Conclusion

Residential solar load analysis should connect the actual household schedule with a site-specific production model. Separate existing and future loads, distinguish energy from power, and keep proposed behavior changes visible.

Choose PV and storage by their contribution to the customer’s stated objective. Report remaining imports, exports, operating assumptions and cost sensitivities alongside any self-consumption percentage.

Bring the reviewed site and load assumptions to a SurgePV design walkthrough to discuss energy-yield modeling, financial modeling and proposal generation. Confirm the detailed modeling scope and let the responsible designers approve the electrical, heating and storage decisions.

Frequently Asked Questions

What is residential solar load analysis?

Residential solar load analysis maps household electricity use across time before PV and storage sizing. Separate base demand, heat-pump demand and EV charging where the evidence permits. Match the resulting profile with site-specific generation and the actual tariff.

How many solar panels do I need for a heat pump and an EV?

There is no reliable panel count based only on having those appliances. Use annual demand for an initial energy balance, then check roof space, specific yield, load timing and grid constraints. Compare feasible sizes using interval imports, exports and cost.

Why does heat-pump load matter for solar sizing?

Heat-pump electricity can be concentrated in periods when PV output is limited. The seasonal pattern depends on climate, building demand and whether the system also supplies cooling or hot water. Use the heating design and equipment performance information rather than a universal winter percentage.

Should I size PV to cover EV charging fully?

Size PV against the household objective and the vehicle’s actual charging opportunities. A car away during daylight cannot use home solar directly during those hours. Compare scheduling, storage and tariff alternatives while preserving the required departure charge.

What battery size do I need with a heat pump and EV?

Choose usable capacity and power from the interval energy balance and required backup service. Compare candidate sizes with consistent efficiency, reserve and tariff assumptions. A fixed kWh-per-kWp ratio cannot determine the economic optimum for every household.

What interval data do I need for load analysis?

Use the finest reliable interval data available across a representative seasonal cycle. A complete non-leap year has 35,040 quarter-hour intervals, but exports may contain gaps or time-zone issues. Monthly bills remain useful for reconciliation and preliminary scenarios when interval records are unavailable.