Step 4: Define Object Properties

Data related to electric demands are entered in the file InvDefaults_EDEM.csv. Open the file in Microsoft Excel and inspect the already entered information. You can see that the first row contains the property names, and the second row already has the name of our EDEM object, LOCAL_DEMAND. The property DefMaxDemand is the peak demand for the year. This value is used to scale the demand forecast profile in the time-series input data.

Since demands in CEM can be curtailed, the value of DefValueOfLostLoad is used to penalize this curtailment. In this example, you will to incur a cost of $100000 for every unit of curtailed demand!

The grid supply is modeled using a generic generator. Data related to generic generators are entered in the file InvDefaults_XGEN.csv. You can open the file in Microsoft Excel and inspect the already entered information. The key information is also listed below:

We model the grid supply as an already existing (typically referred in CEM as brownfield) object, with a non-zero initial capacity of 50 MW. This is reflected in the BrownfieldGenCap property. Since the generator is already existing, we set its capital costs (DefGenerationCapacityCapEx) to zero and inform the solver that this is not a candidate for expansion by setting the DefGenCapCandidateType property. The generator has an assumed lifetime of 30 years, and the energy from it costs 50 $/MWh (DefGenerationVOMCost).

Similar to the generator, the transmission line is also modeled as a brownfield object. Open the file InvDefaults_LI.csv in Microsoft Excel and inspect the information. You will find the important information already entered as:

The transmission line is assumed to have sufficient capacity to import all the required power from the upstream grid. Therefore, we arbitrarily allocate a high brownfield capacity of 1000 MW.

The data for PV and Wind objects are entered in InvDefaults_PV.csv and InvDefaults_WIND.csv, respectively. The important properties are:

The discount rate property (7.25% in this case) dictates how the capital costs are annualized over the economic lifetime of the object. We designate PV and Wind objects for expansion by setting their DefGenCapCandidateType property to 1. Both objects do not incur any energy cost. However, there are fixed operational costs associated with them (DefGenerationCapacityFixedOpEx).

The electric storage has its properties in the file InvDefaults_ESTR.csv. The table below lists the important input properties:

The electric storage has significantly more properties as compared to other objects because the charging, discharging, and volume components are modeled independently. The properties show that we set separate capital costs for expanding charging, discharging, and volume capacities. We designate all three components to be expanded by setting the respective CandidateType properties to 1. The charging and discharging efficiencies are 92% each. Similar to the PV and Wind objects, the ESTR object also has fixed operational expenses.

The property IsFixedDemToGenCapRatio is a boolean, letting the solver know that we need the charging and discharging powers to be proportional to each other. When it is set to 1, we also need to specify what that ratio is. In this case, we set DemToGenCapRatio to 1 to achieve equal charging and discharging powers. Similarly, IsFixedDuration and Duration properties together ensure that the storage will have a volume capacity that corresponds to 4 hours of duration.