Consumption Optimization in an Office Building Considering Flexible Loads and User Comfort

Area of Science:

• Energy Management
• Building Automation
• Optimization Algorithms

Background:

• Rising energy demands necessitate efficient building energy management systems.
• Smart grid technologies enable demand response programs for energy conservation.
• Integrating flexible and deferrable loads is key to optimizing building energy consumption.

Purpose of the Study:

• To develop and implement a multiperiod optimization algorithm for building energy management.
• To minimize electricity consumption and maximize user comfort through intelligent load control.
• To integrate demand response strategies within a Supervisory Control and Data Acquisition (SCADA) system.

Main Methods:

• A multiperiod optimization algorithm was developed and implemented in a SCADA system.
• Flexible loads (lights, air conditioners) and deferrable loads (dishwasher) were controlled.
• User comfort was modeled using indoor temperature, and constraints were set based on user preferences and operational needs.

Main Results:

• The algorithm effectively reduced electricity consumption in an office building case study.
• Demand response programs were successfully implemented, demonstrating the system's performance.
• The methodology proved effective in minimizing the difference between actual and desired indoor temperatures.

Conclusions:

• The proposed optimization algorithm offers an effective solution for reducing building energy consumption.
• The system integrates demand response and load shifting for smart grid applications.
• The methodology provides a flexible framework for building energy managers to optimize operations while respecting user comfort and constraints.