Grid systems with storage

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Grid systems with storage

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Context

More and more grid-tied PV systems are now equipped with a battery storage.

The objective of such hybrid systems may be quite different from case to case.  As examples:

-For "purists" of the PV energy, consuming a minimum of energy coming from the grid, whatever the price,
-According to consuming and feed-in tariffs, optimizing the costs of electricity,
-For the optimization of the grid management, injecting power during the "best" periods of the day,
-Grid management: peak shaving,
-Grid management: short term grid stabilization (for example under variable cloudy conditions),
-In "rich" countries, ensuring a secure back-up in case of (rare) grid failure,
-In countries where the grid is weak or intermittent, ensuring electrical availability during the whole day,
-Mini-grids for the electrification of whole villages or islands,
- etc...

Each of these uses of the PV energy will involve different sizings, constraints, energy flux, and quite different control strategies.

On the one hand, the control will depend on the self-consumption profile and the grid characteristics  (availability, overload, etc),

On the other hand, the charging/discharging strategy is important. When should the PV array charge or discharge the batteries?  

-When they are not full ?
-When the consumers have low needs?  
-According to the time-dependent tariffs ?
-When the foreseen weather of the next day is bad ?

Implementation in PVsyst

Since the version 6.76,  PVsyst provides 3 different strategies of Grid-storage:

-Self-consumption, with a simple strategy
-Peak shaving, when the grid-injection power is limited
-Weak grid recovery, for ensuring an electricity supply when the grid is falling.

Each of these strategies have different constraints:

-Self-consumption and Weak grid recovery require the definition of a user's needs hourly profile,
-Weak grid recovery requires the specification of a grid-unavailability hourly profile,
-Weak grid recovery may accept re-injection of PV energy into the grid, or not,  
-Peak shaving doesn't involve a user's needs profile,
-The battery energy will never be used for feeding the grid, except with peak shaving,
-In all these strategies, the battery charging will begin as soon as PV energy is over the user's needs.
-The time of release of the battery energy (discharge) may be different according to the strategies, cost optimizations, etc.

The sizing of the different parts of the system (PV array, battery pack, as function of the needs profile and the electricity price), is a complex problem, specific to each of these strategies. PVsyst will probably provide only rough sizing rules until some experience has been accumulated.

Real System realization

Grid-storage systems require specific electronic devices, especially suited inverters, battery chargers, controllers, etc.

Defining these devices in PVsyst will be extremely complex, as each manufacturer proposes its own integrated solution.

Moreover some battery packs for domestic use are delivered with AC inputs and outputs, meaning that a charger and an inverter is included in the pack.

In this first attempt, these specific devices are not yet implemented. The charging and discharging operations of the battery are approximated by generic charging (AC-DC) and discharging (DC-AC) devices, characterized by an efficiency curve as function of the power, and a maximum output power PNom. These give rise to a conversion loss in the loss diagram.  

Cost of energy

Implementing a storage in a PV system implies an specific cost of the stored energy, expressed as   price/kWh.

This cost corresponds indeed to the maximum energy stored in the battery pack during the battery lifetime, divided by the cost of the battery pack replacement.

The simulation will calculate the Battery ageing as a function of the operating conditions (nb. of cycles and temperature), and evaluate its degradation along the time.

The simulation will perform the replacement of the battery pack when necessary. This should be a crucial information for the financial evaluation and optimization, as well as for the ageing of the whole system.