[Paper Review] Prosumage of solar electricity: tariff design, capacity investments, and power system effects

Claudia Günther, Wolf-Peter Schill+1 more|arXiv (Cornell University)|Jul 23, 2019

Smart Grid Energy Management4 citations

TL;DR

This study uses a power system model with prosumage agents to analyze how retail and feed-in tariff designs influence residential PV and battery investments in Germany by 2030. It finds that lower feed-in tariffs reduce PV investments but have limited impact on optimal battery sizing and self-consumption, while higher fixed tariff components reduce both, increasing households' contribution to non-energy system costs—highlighting the need for balanced tariff design to support renewable expansion and cost-sharing.

ABSTRACT

We analyze how tariff design incentivizes households to invest in residential photovoltaic and battery systems, and explore selected power sector effects. To this end, we apply an open-source power system model featuring prosumage agents to German 2030 scenarios. Results show that lower feed-in tariffs substantially reduce investments in photovoltaics, yet optimal battery sizing and self-generation are relatively robust. With increasing fixed parts of retail tariffs, optimal battery capacities and self-generation are smaller, and households contribute more to non-energy power sector costs. When choosing tariff designs, policy makers should not aim to (dis-)incentivize prosumage as such, but balance effects on renewable capacity expansion and system cost contribution.

Motivation & Objective

• To examine how retail and feed-in tariff structures influence household decisions to invest in residential photovoltaic (PV) and battery storage systems.
• To assess the resulting impacts on renewable capacity expansion, peak PV feed-in, and households' contributions to non-energy power system costs in Germany.
• To evaluate whether tariff designs can simultaneously support decarbonization goals and equitable cost-sharing without distorting prosumage incentives.
• To explore the trade-offs between incentivizing self-generation, minimizing grid strain, and ensuring fair cost allocation across electricity consumers.

Proposed method

• Develops a computable general equilibrium model of the German power system with explicit representation of prosumage households as agents.
• Incorporates interactions between household investment decisions and wholesale electricity market outcomes through a market-clearing mechanism.
• Uses open-source modeling tools to simulate 2030 scenarios under varying combinations of feed-in tariffs (FIT), retail tariff structures (volumetric vs. fixed components), and technology cost assumptions.
• Calibrates PV and battery costs based on projections from Schmidt et al. (2017), with sensitivity analysis on conservative cost reduction paths.
• Models household optimization behavior under different tariff regimes, including self-consumption incentives and grid connection constraints.
• Analyzes system-level outcomes such as total renewable capacity, peak feed-in levels, and the share of non-energy system costs borne by prosumage households.

Experimental results

Research questions

• RQ1 How do varying feed-in tariff levels affect residential PV investment decisions and optimal battery sizing?
• RQ2 To what extent do fixed versus volumetric components in retail tariffs influence household incentives for self-generation and battery storage?
• RQ3 What is the impact of different tariff designs on the total contribution of prosumage households to non-energy power system costs (e.g., grid infrastructure, renewable support schemes)?
• RQ4 Can peak PV feed-in be limited through tariff design without significantly reducing prosumage incentives or distorting investment behavior?
• RQ5 How do tariff structures affect the alignment of prosumage behavior with system-level needs such as peak shaving and valley filling?

Key findings

• Lower feed-in tariffs significantly reduce PV investments, as households face a trade-off between system size and remuneration for surplus generation.
• Optimal battery capacity and self-generation levels are relatively robust to changes in feed-in tariffs, as they are primarily driven by the temporal mismatch between PV generation and household demand profiles.
• Higher fixed components in retail tariffs reduce optimal battery capacity and self-consumption, leading to lower household contributions to energy consumption but higher contributions to non-energy system costs.
• Households with high fixed tariffs contribute more to non-energy system costs such as grid infrastructure and renewable surcharge, potentially creating distributional inequities.
• A maximum feed-in policy can effectively reduce peak grid congestion without substantially undermining prosumage incentives, offering a viable grid relief mechanism.
• A combination of high feed-in tariffs and increased fixed tariff components can simultaneously promote high PV deployment and ensure prosumage households contribute fairly to system costs, supporting both decarbonization and fiscal sustainability.