Abstract
Sum-utility maximization is an important problem in the optimization of energy systems. A conventional assumption in addressing this problem is that the utility to be maximized is concave. But for some key applications, such an assumption is not reasonable and does not reflect well the actual behavior of the consumer. To address this issue, the authors pose and address a more general optimization problem, namely by assuming the consumer's utility to be sigmoidal and in a given class of functions. The considered class of functions is attractive for at least two reasons. First, the classical NP-hardness issue associated with sum-utility maximization is circumvented. Second, the considered class of functions encompasses well-known performance metrics used to analyze problems of pricing and energy-efficiency. This allows one to design a new and optimal inclining block rate (IBR) pricing policy which also has the virtue of flattening the power consumption and reducing the peak power. We also show how to maximize the energy-efficiency using a low-complexity algorithm. When compared to existing policies, simulations fully support the benefit of using the proposed approach.
Original language | English (US) |
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Article number | 118239 |
Journal | Applied Energy |
Volume | 308 |
DOIs | |
State | Published - Feb 15 2022 |
All Science Journal Classification (ASJC) codes
- Building and Construction
- Mechanical Engineering
- General Energy
- Management, Monitoring, Policy and Law
Keywords
- Demand response
- Energy efficiency
- Game theory
- Inclining block rates
- Prospect theory
- Smart grid