added unit tests

README.md

@@ -5,7 +5,7 @@
 Julia package designed for simulating the operation of battery energy storage systems (BESS) in various energy markets. The package provides tools to model battery characteristics, simulate market operations, and calculate the optimal power dispatch.
 
 ## Installation
-To get started with BatteryOptimization.jl, ensure you have Julia installed on your system (version 1.6 or later is recommended).
+To get started, ensure you have Julia installed on your system (version 1.6 or later is recommended).
 
 - Begin by cloning the repository to your local machine:
 ```

src/Markets.jl

@@ -6,14 +6,14 @@ export Market, get_price
 
 function load_caiso_prices()
     dfmt = dateformat"mm/dd/yyyy HH:MM:SS p"
-    price_per_mwh = DataFrame(CSV.File("src/data/20230101-20240101 CAISO Average Price.csv"; dateformat=dfmt))
+    price_per_mwh = DataFrame(CSV.File("$(@__DIR__)/data/20230101-20240101 CAISO Average Price.csv"; dateformat=dfmt))
     price_per_kwh = transform(price_per_mwh, :price => (x -> x * 0.001) => :price)
     return price_per_kwh
 end
 
 function load_ercot_prices()
     dfmt = dateformat"mm/dd/yyyy HH:MM:SS p"
-    price_per_mwh = DataFrame(CSV.File("src/data/20230101-20240101 ERCOT Real-time Price.csv"; dateformat=dfmt))
+    price_per_mwh = DataFrame(CSV.File("$(@__DIR__)/data/20230101-20240101 ERCOT Real-time Price.csv"; dateformat=dfmt))
     price_per_kwh = transform(price_per_mwh, :price => (x -> x * 0.001) => :price)
     price_per_kwh = price_per_kwh[price_per_kwh.zone.=="LZ_HOUSTON", :]
     price_per_kwh = price_per_kwh[:, [:date, :price]]

test/runtests.jl

@@ -1,6 +1,29 @@
 using BatteryOptimization
+using BatteryOptimization.Dates
+using BatteryOptimization.DataFrames
 using Test
 
 @testset "BatteryOptimization.jl" begin
-    # Write your tests here.
+    battery = Battery(capacity_kwh=100, max_power_kw=25)
+    market = Market("CAISO", DateTime("2023-06-01T00:00:00"), DateTime("2023-06-01T03:00:00"))
+    result = run_simulation(DateTime("2023-06-01T00:00:00"), DateTime("2023-06-01T03:00:00"), market, battery)
+    @test length(result.power_schedule.power_kw) == 4
+    @test result.objective_value isa Real
+    @test all(result.power_schedule.power_kw .<= battery.max_power_kw)
+    @test all(result.power_schedule.power_kw .>= -battery.max_power_kw)
+    @test sum(result.power_schedule.power_kw) >= battery.capacity_kwh * (battery.final_soc - battery.initial_soc)
+    @test all(get_soc(battery.initial_soc, battery.capacity_kwh, result.power_schedule).soc .<= battery.max_soc)
+    @test all(get_soc(battery.initial_soc, battery.capacity_kwh, result.power_schedule).soc .>= battery.min_soc)
 end
+
+@testset "Markets.jl" begin
+    @testset "Test Market $(iso)" for iso in ["CAISO", "ERCOT"]
+        market = Market(iso, DateTime("2023-06-01T00:00:00"), DateTime("2023-06-01T03:00:00"))
+        @test market.price_per_kwh isa DataFrame
+        @test !isempty(market.price_per_kwh)
+        @test all(market.price_per_kwh.date .>= DateTime("2023-05-31T23:00:00"))
+        @test all(market.price_per_kwh.date .<= DateTime("2023-06-1T03:00:00"))
+        @test get_price(market, timestamp=DateTime("2023-06-01T04:00:00")) == market.price_per_kwh[end, :price]
+    end
+    @test_throws ErrorException Market("XYZ", DateTime("2023-06-01T00:00:00"), DateTime("2023-06-1T03:00:00"))
+end