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Prosumer Synchronisation Risk: Impacts of Time-Varying Tariffs on Distribution Network Expansion
Dillon Zadoks, Alfredo Oneto, Carlo Tajoli, Yi Guo, Philipp Heer, Giovanni Sansavini, Gabriela Hug
TL;DR
Rapid DER deployment is increasing stress on low-voltage networks, raising the question of how tariff-driven prosumer operation affects reinforcement needs. The paper uses a MILP across 471 projected 2050 networks to optimise DER operation and reinforcement planning under time-varying tariffs. Reinforcement costs can fall substantially at moderate adoption, but prosumer synchronisation reverses the benefit beyond tariff-specific thresholds.
Problem
Increasing electrification and DER deployment are intensifying stress on low-voltage networks, motivating evidence on reinforcement impacts under time-varying tariffs.
Method
A MILP evaluates reinforcement planning across 471 low-voltage networks, with DERs operating to minimise costs under subscribed tariffs and the DSO subsequently optimising reinforcements.
Results
Reinforcement costs can decrease by up to 50% at 20% adoption, but rise above 50% ToU and 40% RTP adoption thresholds; above 90% RTP adoption, needs can exceed flat-rate levels.
Takeaways & Limitations
Time-varying tariffs can reduce reinforcement costs at moderate adoption, but prosumer synchronisation can increase reinforcement needs at high adoption.
Takeaways & Limitations
The economic analysis assumes standard LVN equipment prices and lifespans of 40 years for cables and 20 years for transformers.
Abstract
from arXiv · showhide
The rapid deployment of distributed energy resources, including heat pumps, electric vehicles, photovoltaics, and battery storage, is reshaping the operation of low-voltage networks. While distribution system operators often aim to develop time-varying tariffs to incentivise network-friendly behaviour and defer reinforcements, they risk triggering prosumer synchronisation. As prosumers follow price signals, their behaviour may synchronise, avoiding existing load peaks while creating undesirable peaks at other times. This paper quantifies the impact on low-voltage network reinforcement needs when shifting from flat tariffs to two time-varying tariffs: Time-of-Use and Real-Time Pricing. Applying a mixed-integer linear model across 471 low-voltage reference networks in Switzerland, we evaluate expansion requirements under projections of distributed energy resource deployment for 2050. In the model, prosumers operate their distributed energy resources in accordance with their subscribed electricity tariff to minimise costs, and the distribution system operator subsequently optimises reinforcements. Our results demonstrate that while adopting time-varying tariffs can reduce reinforcement investment costs by more than 50%, high adoption rates can reverse this declining trend. Specifically, once prosumer adoption exceeds the optimal thresholds of 50% for Time-of-Use and 40% for Real-Time Pricing, reinforcement needs increase by 39% and 134%, respectively, for an additional 20% of tariff adoption.
1 Introduction
Electrification and distributed energy resources increase stress on low-voltage networks, while flexible demand and time-varying tariffs may reduce reinforcement needs but can create planning challenges. The paper develops a MILP framework to evaluate tariff adoption and reinforcement requirements across projected future networks.
- Motivation: Electrification of heating and transport, alongside PV and battery adoption, is increasing stress on low-voltage networks.Flexible devices such as heat pumps, electric vehicles, and batteries can shift demand and potentially reduce reinforcement needs when appropriately managed.
- Motivation: Time-varying tariffs, including Time-of-Use and Real-Time Pricing, aim to encourage network-friendly electricity use through higher and lower cost periods.Price-responsive home-management systems and smart devices allow DSOs to use more granular tariff signals.
- Research gap: Existing heuristic studies support large-scale analysis but may produce suboptimal reinforcement decisions.A prior centralised approach reduced operational violations while increasing electricity procurement expenses.
- Approach: The paper proposes a Mixed Integer Linear Program that jointly considers reinforcement planning and cost-minimising DER operations under different time-varying tariffs.The model evaluates tariff adoption levels, with some flexible resources responding to prices and others remaining price-agnostic.
- Results: Up to 50% tariff adoption can reduce reinforcement costs by more than 50%, but higher adoption can reverse the declining trend.The assessment covers 471 low-voltage networks with projected DER deployments for 2050.
2 Methodology
The methodology models distributed energy resources, tariff-driven prosumer scheduling, and subsequent distribution-network expansion planning under multiple tariff structures.
- 2.1. Distributed Energy Resources: The study models PV, BESSs, HPs, and EVs using operational constraints for generation, storage, thermal dynamics, and charging flexibility.BESS dynamics link state of charge across time; HP constraints enforce thermal comfort; EV constraints represent bounded charging and daily and weekly energy requirements.
- 2.2. Electricity Tariffs: Prosumers subscribe to flat, ToU, or RTP tariffs and optimally schedule flexible DERs to minimise electricity costs.The flat tariff is constant, ToU distinguishes predefined peak and off-peak periods, and RTP prices are based on forecasted transformer loading.
- 2.2.3. Congestion-Based Real-Time Pricing Tariff: RTP uses forecasted transformer loading as a congestion proxy while preserving the same average tariff as the flat tariff.The tariff components include electricity supply, network usage, and taxes, with parameters chosen so the period-average price remains unchanged.
- 2.3. Distribution Network Expansion: The model determines prosumer consumption from tariff-based cost minimisation without network-flow restrictions, then passes the resulting power flows to DSO expansion planning.Tariff adoption assigns some DERs to time-varying tariffs and the remaining prosumers to the flat tariff before retrieving active and reactive line flows.
- 2.3. Distribution Network Expansion: The DSO minimises integer line and transformer expansions subject to voltage, branch-flow, and ampacity constraints across operational scenarios.Nonlinear constraints are linearised using polyhedral outer approximations and McCormick envelopes with binary representations of integer variables.
3 Case Study
The case study examines projected 2050 distributed energy resource deployments across low-voltage networks in Bern, Switzerland, using generated operational scenarios and specified tariff and investment assumptions.
- The case study analyses low-voltage networks with projected distributed energy resources in Bern, Switzerland.
- The networks operate at 400 V and include projected photovoltaics, co-located battery storage, electric vehicles, heat pumps, and non-controllable loads for 2050.
- Investment costs are expressed in thousands of CHF, with assumed lifespans of 40 years for cables and 20 years for transformers.
- The constructed Time-of-Use tariff uses a 10 Raps/kWh difference between on-peak and off-peak periods, with on-peak hours from 06:00 to 20:00.
- Twenty weekly profiles are generated for each low-voltage network using Gaussian sampling from seasonal means and covariance matrices.
4 Results
Time-varying tariffs generally flatten transformer loading and reduce reinforcement costs at moderate adoption, but synchronised responses create new peaks and reverse cost reductions beyond tariff-specific thresholds.
- 4.1. Operational Effects of Tariff Adoption: At 30% and 70% adoption, both time-varying tariffs generally flatten the load profile, with a stronger effect under Real-Time Pricing.
- 4.1. Operational Effects of Tariff Adoption: At 100% Time-of-Use adoption, a rebound peak forms when the off-peak price period begins.
- 4.2. Effect of Tariffs in Distribution Network Expansion: At 10% adoption, annualised reinforcement costs fall by 29% under Time-of-Use and 36% under Real-Time Pricing.
- 4.2. Effect of Tariffs in Distribution Network Expansion: Maximum cost reductions reach 78% for Time-of-Use at 50% adoption and 85% for Real-Time Pricing at 40% adoption.
- 4.2. Effect of Tariffs in Distribution Network Expansion: After 50% Time-of-Use or 40% Real-Time Pricing adoption, reinforcement costs increase because a higher share of demand responds synchronously to price signals.
5 Conclusions
The paper proposes a mixed-integer linear model and evaluates tariff adoption across 471 reference low-voltage networks in Bern under projected 2050 distributed energy resource deployment. It finds substantial reinforcement-cost reductions at moderate adoption, followed by increases above tariff-specific thresholds and, for high Real-Time Pricing adoption, costs exceeding flat-rate requirements.
- The paper proposes a mixed-integer linear model for reinforcement planning that incorporates prosumer adoption of time-varying tariffs.
- The analysis covers 471 reference low-voltage networks in Bern, Switzerland, under projected distributed energy resource deployment in 2050.
- At 20% adoption, annualised reinforcement costs can decrease by up to 50%, with Real-Time Pricing marginally more effective than Time-of-Use.
- Reinforcement costs begin rising above 50% adoption for Time-of-Use and 40% for Real-Time Pricing, indicating prosumer synchronisation as loads shift toward low-price periods.
- For Real-Time Pricing adoption above 90%, reinforcement needs can exceed those under flat-rate subscriptions.