Building Energy Controller Cost Optimization
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Solution Overview
Problem
Building energy systems face challenges in optimizing costs under block-and-index rate structures or load-following-block rate structures, as existing solutions fail to efficiently manage resource allocation and pricing schemes, leading to suboptimal energy consumption and generation strategies.
Innovation Solution
A building energy system with a controller that optimizes resource allocation by defining a cost function representing resources sourced from fixed and variable rate suppliers, determining optimal block sizes or hedge percentages, and controlling equipment to minimize total costs through stochastic model predictive control and demand charge incorporation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a block-and-index rate structure is implemented, then cost optimization opportunities arise, but the complexity of managing resource allocation increases
Solution Approach 1:
The resource allocation is segmented into multiple time steps within an optimization period, allowing the controller to make discrete optimization decisions at each time step. The cost function is also segmented to account for different pricing structures (block rates, index rates, demand charges) applied at different times, enabling granular cost management while maintaining system tractability
Solution Approach 2:
The system performs preliminary optimization calculations to determine optimal resource allocation strategies before the optimization period begins. The controller pre-calculates decision variables for resource purchasing, storage, generation, and consumption based on forecasted conditions and pricing structures, allowing proactive cost management rather than reactive adjustments
2Loss of energy
If equipment is controlled to achieve optimal cost values, then total resource costs decrease, but the control system complexity increases
Solution Approach 1:
The control system incorporates feedback mechanisms where the controller continuously monitors actual resource consumption and costs against the optimized values, adjusting future optimization decisions based on performance deviations. This feedback loop enables the system to learn from past performance and improve cost optimization over time while maintaining manageable control complexity through iterative refinement
Solution Approach 2:
The control system is designed to be dynamic, with the optimization period and time steps allowing flexible adjustment of control strategies. The controller can adapt the frequency and granularity of control actions based on changing conditions, pricing structures, and system state, enabling effective cost management without requiring overly complex static control mechanisms
Data Source
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AI summary
A building energy system includes equipment operable to consume, store, or generate one or more resources subject to a block-and-index rate structure. The building energy system includes a controller configured to obtain a cost function that represents a block of the resource(s) from the utility provider as being sourced from a first supplier at a fixed rate and a remainder of the resource(s) from the utility provider as being sourced from a second supplier at a variable rate. The controller is configured to optimize the cost function to generate values for one or more decision variables that indicate an amount of resource(s) to purchase, store, generate, or consume at each of a plurality of time steps, and control the equipment to achieve the values of the one or more decision variables at each of the time steps.