Voluntary Renewable Programs: Optimal Pricing and Revenue Allocation
Zhiyuan Fan, Tianyi Lin, Bolun Xu

TL;DR
This paper presents a multi-period optimization framework for designing voluntary renewable programs, focusing on optimal pricing, revenue allocation, and renewable deployment to maximize renewable energy adoption within a utility's constraints.
Contribution
It introduces an analytical model for optimal VRP pricing and revenue sharing, revealing strategic insights into renewable expansion and the limitations of voluntary programs.
Findings
Optimal pricing depends on grid carbon intensity.
Myopic policy is conditionally optimal for long-term renewable capacity.
Voluntary programs extend renewable penetration but do not achieve net-zero emissions.
Abstract
This paper develops a multi-period optimization framework to design a voluntary renewable program (VRP) for an electric utility company, aiming to maximize total renewable energy deployments. In the business model of VRP, the utility must ensure it generates renewable energy up to the total amount of contract during each market episode (i.e., a year), while all the revenue collected from the VRP must either be used to invest in procuring renewable capacities or to maintain the current renewable fleet and infrastructure. We thus formulate the problem as an optimal pricing problem coupled with revenue allocation and renewable deployment decisions. We model the demand function of voluntary renewable contracts as an exponential decay function based on survey data. We analytically derive the optimal pricing policy of the VRP as a function of the current grid carbon intensity. We prove that a…
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Taxonomy
TopicsElectric Vehicles and Infrastructure · Electric Power System Optimization · Smart Grid Energy Management
