diff --git a/3-smart-grid.md b/3-smart-grid.md
index 93d02f3..451e06f 100644
--- a/3-smart-grid.md
+++ b/3-smart-grid.md
@@ -91,3 +91,41 @@
     - ![analytics diagram](./assets/3-smart-grid-analytics.webp)
 - Example:
     - ![Example](./assets/3-analytics-examples.webp)
+
+### Load shifting / Peak shaving
+
+- To flatten the instantaneous energy demand, by load shifting and peak shaving
+    - Using the peak and off-peak electricity tariff (tax)
+
+### Other considerations for smart grid
+
+#### Privacy concern
+- The more fine grained data is, the more risk in privacy
+
+#### Flexibility, and comfort of saving electricity
+
+- Gadgets owned:
+    - TV: least beneficial
+    - EV charger: essential to EV owners
+- Work from home vs. Work from office
+
+### Use cases : Household power usage
+- Usage differs per number of occupants
+- Try to apply load shifting for each house hold
+- Predcit:
+    - Timing for high / low energy usage per day
+    - Same in a week and a year
+    - Most energy consumption during peak
+    - Can you estimate when they wake up or go to sleep
+    - predict if work from home or out
+- Design dual tariff to shift load
+    - Time of day to trigger
+    - If it's the same every day of week
+    - Every month of year
+
+### Example solutions
+
+- Digital twin: has privacy concern
+- Adaptive dual tariff: low rate before, and high rate after threshold
+- Reinforcement learning: to learn about the environment
+- These results in smoothed electric curve