Building Energy Controller for Load-Following Block Rate 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 determining an optimal block size and allocating resources between fixed and variable rate suppliers, using a cost function that represents energy or power sourced from different suppliers, and performing optimization processes to minimize total costs over time steps, while considering constraints such as energy storage capacity and demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a block-and-index rate structure or load-following-block rate structure is implemented, then cost optimization opportunities arise, but the complexity of managing resource allocation and pricing schemes increases
Solution Approach 1:
The resource allocation problem is segmented into discrete time steps and decision variables (purchase, store, generate, consume amounts at each time step). The cost function is segmented into fixed rate portion (block) and variable rate portion (remainder), allowing independent optimization of each segment while maintaining overall cost minimization.
Solution Approach 2:
The system dynamically adjusts resource allocation strategies based on time-varying pricing schemes. The controller performs real-time optimization of the cost function subject to constraints, adapting purchase, storage, generation, and consumption decisions at each time step according to current pricing conditions and system state.
2Loss of energy
If optimization processes are performed to minimize total costs, then energy cost reduction is achieved, but computational complexity and processing requirements increase
Solution Approach 1:
The system performs preliminary optimization calculations to determine the optimal block size before implementing the resource allocation strategy. The controller pre-calculates decision variable values for each time step based on forecasted pricing and load conditions, enabling proactive cost minimization rather than reactive adjustments.
Solution Approach 2:
The optimization process incorporates feedback loops where the controller continuously monitors actual resource consumption, storage levels, and pricing conditions, then adjusts decision variables in subsequent time steps. This closed-loop control ensures ongoing cost minimization while adapting to changing system conditions and pricing schemes.
Data Source
AI summary
A controller for equipment that operate to store, discharge, generate, or consume one or more resources is configured to provide an objective function indicating a total value of obtaining a resource from a utility provider over a plurality of time steps subject to a load-following-block rate structure. The objective function includes a first term representing a load-following-block of the resource as being sourced from the utility provider at a fixed rate and a second term representing a remainder of the resource as being sourced from the utility provider at a variable rate. The controller is configured to use the objective function to generate values for decision variables and control the equipment to store, discharge, generate, or consume amounts of the resources indicated by the values of the decision variables at the plurality of time steps.