A Hybrid Pricing Mechanism for Joint System Optimization and Social Acceptance

Abstract

In this paper, we propose a socially-accepted local electricity pricing mechanism for households that is dependent on the electric load of the neighbourhood and is able to flatten out the neighbourhood profile. The cost function used for this pricing mechanism is a piecewise linear approximation of a quadratic function.The motivation for using this mechanism is that the energy transition is expected to result in higher peak loads in electricity consumption as well as in renewable generation, which poses a significant challenge to the distribution grids. To tackle this problem, electricity consumption profiles need to be flattened.Following the literature, quadratic cost functions have proven their ability to achieve such a system optimization. However, their problem is that consumers find the resulting pricing mechanisms too complex and are generally unwilling to participate when offered these prices. In contrast, the socially acceptance of simple pricing mechanisms such as currently used in practice is high, but these mechanisms are hardly giving any incentive to reduce peaks in electricity profiles.Based on the feedback of consumers participating in our field test and the criteria defined in the literature, we conclude that the proposed mechanism is socially accepted. Furthermore, a numerical evaluation shows that our proposed mechanism can flatten out peaks on the neighbourhood level, albeit that its convergence is slightly slower than by using the quadratic cost function. These two findings imply that the presented pricing mechanism has the potential to be useful in practice.

On a Reduction for a Class of Resource Allocation Problems

“…This is an effect that can also be observed for other renewable energy systems, such as photovoltaic (solar panel) systems and electric vehicle charging (see, e.g., Munkhammar et al 2013) and heat pumps (see, e.g., Vanhoudt et al 2014). Moreover, energy tariff systems that employ piecewise linear cost functions are shown to be able to flatten the load profile, that is, the objective modeled by a quadratic cost function (see, e.g., Reijnders et al 2020). Because such tariff systems are simpler to explain to end users, they are more likely to be accepted than systems using quadratic cost functions while still achieving the desired objective of load profile flattening.…”

Duality-driven optimization in energy management: offline and online algorithms for resource allocation problems

“…2.5.3 -Stratified sampling and heat pumps (see, e.g., [168]). Moreover, energy tariff systems that employ piecewise linear cost functions have been shown to be able to flatten the load profile, i.e., the objective modeled by a quadratic cost function (see, e.g., [143]). Since such tariff systems are simpler to explain to end-users, they are more likely to be accepted than systems using quadratic cost functions while still achieving the desired objective of load profile flattening.…”

On a reduction for a class of resource allocation problems

“…This is an effect that can also be observed for other renewable energy systems such as photovoltaic (solar panel) systems and electric vehicle charging (see, e.g., [54]) and heat pumps (see, e.g., [80]). Moreover, energy tariff systems that employ piecewise linear cost functions have been shown to be able to flatten the load profile, i.e., the objective modeled by a quadratic cost function (see, e.g., [64]). Since such tariff systems are simpler to explain to end users, they are more likely to be accepted than systems using quadratic cost functions while still achieving the desired objective of load profile flattening.…”