Release 1.3.0 (#67)

Makefile

@@ -55,6 +55,7 @@ test: setup-test test-docs
 create-test-docs: setup-test clean-test-docs
 	mkdir -p ./tests/phmdoctest
 	python -m phmdoctest README.md --outfile tests/phmdoctest/test_readme.py
+	python -m phmdoctest ./docs/docs/changelog.md --outfile tests/phmdoctest/test_changelog.md
 	python -m phmdoctest ./docs/docs/how-to/complex-terms.md --outfile tests/phmdoctest/test_complex_terms.py
 	python -m phmdoctest ./docs/docs/how-to/custom-objectives.md  --outfile tests/phmdoctest/test_custom_objectives.py
 	python -m phmdoctest ./docs/docs/validation/battery.md --outfile tests/phmdoctest/test_validate_battery.py

docs/docs/changelog.md

@@ -1,15 +1,134 @@
 # Changelog
 
-## [1.3.0 - Unreleased]()
+## [1.3.0](https://github.com/ADGEfficiency/energy-py-linear/releases/tag/v1.3.1)
 
 ### Different Battery Charge and Discharge Rates
 
-### Minimum and Maximum Objective Function Terms
+It's now possible to define a different charge and discharge rate in the `epl.Battery` asset.
+
+The example below defines a maximum charge and discharge rate of `2.0`:
+
+```python
+epl.Battery(power_mw=2.0)
+```
+
+The example below defines a maximum charge rate of `2.0` with a maximum discharge rate of `1.0`:
+
+```python
+epl.Battery(power_mw=2.0, discharge_power_mw=1.0)
+```
+
+### Complex Objective Function Terms
+
+A complex custom objective term allows you to construct an objective function with a complex set of costs and revenues.
+
+For example, we can define an objective function that includes a cost for the maximum import above a threshold of `40`:
+
+```python
+{
+    "function": "max_many_variables",
+    "variables": {
+        "asset_type": "site",
+        "variable": "import_power_mwh",
+    },
+    "constant": 40,
+    "coefficient": 200,
+    "M": max(electric_load_mwh) * 10
+}
+```
+
+See [Complex Objective Function Terms](https://energypylinear.adgefficiency.com/latest/how-to/complex-terms) in the documentation for more examples.
 
 ### Custom Accounts
 
+To accommodate complex custom objective functions, we have added the ability to include these custom costs and revenues as a custom account:
+
+```python
+import energypylinear as epl
+
+chp_size = 50
+electric_efficiency = 0.5
+electric_load_mwh = 0
+electricity_prices = np.array([-1000, -750, -250, -100, 0, 10, 100, 1000])
+export_charge = -500
+export_threshold_mwh = 5
+gas_prices = 20
+
+assets = [
+    epl.CHP(
+        electric_efficiency_pct=electric_efficiency,
+        electric_power_max_mw=chp_size,
+    )
+]
+site = epl.Site(
+    assets=assets,
+    gas_prices=20,
+    electricity_prices=np.array([-1000, -750, -250, -100, 0, 10, 100, 1000]),
+    electric_load_mwh=electric_load_mwh,
+)
+
+terms: list[dict] = [
+    {
+        "asset_type": "site",
+        "variable": "export_power_mwh",
+        "interval_data": "electricity_prices",
+        "coefficient": -1,
+    },
+    {
+        "asset_type": "*",
+        "variable": "gas_consumption_mwh",
+        "interval_data": "gas_prices",
+    },
+    {
+        "type": "complex",
+        "function": "min_two_variables",
+        "a": {
+            "asset_type": "site",
+            "variable": "export_power_mwh",
+        },
+        "b": 5.0,
+        "coefficient": export_charge,
+        "M": (
+            electric_load_mwh
+            + assets[0].cfg.electric_power_max_mw
+            + export_threshold_mwh
+        )
+        * 1,
+    },
+]
+
+simulation = site.optimize(
+    verbose=4,
+    objective={"terms": terms},
+)
+
+accounts = epl.get_accounts(simulation.results, custom_terms=terms[-1:])
+print(accouts.custom)
+```
+
+```
+<Account profit=15000.00 emissions=0.0000>
+```
+
 ### Optimization Status
 
+The objective function value has been added to the `epl.optimizer.OptimizationStatus` object:
+
+```python
+import energypylinear as epl
+
+site = epl.Site(
+    assets=[epl.Battery()],
+    electricity_prices=np.array([-1000, -750, -250, -100, 0, 10, 100, 1000]),
+)
+simulation = site.optimize(verbose=4, objective="price")
+print(simulation.status)
+```
+
+```
+OptimizationStatus(status='Optimal', feasible=True, objective=-5811.11111)
+```
+
 ## [1.2.0](https://github.com/ADGEfficiency/energy-py-linear/releases/tag/v1.2.0)
 
 ### Custom Objective Functions

docs/docs/how-to/custom-objectives.md

@@ -1,16 +1,12 @@
-`energypylinear` has two different objective functions (price or carbon) built into the library.
+In linear programming, the objective function defines the incentives and costs you want to optimize for.
 
-An objective function determines the incentives and costs in a linear program.  It's what you are trying to optimize for.
-
-`energypylinear` has two different objective functions (price or carbon) built into the library. 
-
-However you may want to optimize for a different objective function in the linear program. You may have a business problem with a different set of revenues and costs than are included by default.
+`energypylinear` has two different objective functions (price or carbon) built into the library.  In addition, `energypylinear` allows you to define your own, custom objective function.
 
 **A custom objective function allows you to construct an objective function that can optimize for the revenues and costs that are important to you**.
 
 ## Simple Objective Function Terms
 
-Core to the custom objective function is the `epl.Term` - representing a single term in the objective function:
+Core to the custom objective function is the `epl.Term`, which represents a single term in the objective function:
 
 <!--phmdoctest-mark.skip-->
 ```python

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "energypylinear"
-version = "1.2.0"
+version = "1.3.0"
 description = "Optimizing energy assets with mixed-integer linear programming."
 authors = ["Adam Green <adam.green@adgefficiency.com>"]
 license = "MIT"