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Integrated Transmission and Distribution Expansion Planning Considering Customer Actions and Distributed Energy Resources
Abhinav Ayri, Haotian Yao, Mostafa Farrokhabadi, Hamidreza Zareipour
TL;DR
The paper addresses the limited representation of customer-driven DER adoption and operation in integrated system planning. It proposes a multistage framework combining integrated planning, cost allocation, and retailer-based customer decisions, and reports lower system costs, reduced transmission reliance, and lower transmission loading with customer DER participation.
Problem
Existing integrated planning models rarely capture customer-driven DER adoption and operation despite DERs’ potential to reduce system costs.
Method
The framework combines integrated transmission–distribution planning, cost allocation, and a retailer-based economic model that feeds customer DER decisions into planning through updated loads.
Results
Approximately 25.7% lower overall system costs, 89.4% lower load-shedding costs, and a 62.3% reduction in flow into node 4 were reported in the evaluated scenarios.
Takeaways & Limitations
Accounting for system- and customer-level DER benefits can improve cost efficiency and reliability while reducing reliance on transmission supply and loading.
Takeaways & Limitations
The sequential framework does not fully capture feedback between system decisions and customer behaviour, so costs and adoption may not represent a coordinated equilibrium.
Abstract
from arXiv · showhide
The continued integration of distributed energy resources (DERs) motivates research into integrated system planning. While existing literature shows that DERs can reduce system costs, it often overlooks customer behaviour, particularly DER adoption driven by cost savings and incentives. System cost allocation can influence these decisions, affecting DER uptake, grid injections, and overall system efficiency. Therefore, integrated system planning should consider both system- and customer-level benefits of DERs. This paper proposes a multi-step framework that combines an integrated planning model with cost allocation and retailer business models. The integrated planning model minimizes total system costs subject to network constraints, while the cost allocation and retailer models capture customer responses to costs and DER opportunities. By coordinating these models, the framework represents how customer behaviour influences planning outcomes. The proposed approach is demonstrated on a 36-bus system, with results showing that incorporating customer decision-making reduces overall system costs, lowers reliance on transmission-connected generation, and supports more realistic system planning.
I. INTRODUCTION
DER adoption has changed transmission–distribution interactions, but integrated planning models rarely treat customer adoption and operation as decision outcomes. The paper therefore proposes integrating planning, cost allocation, and customer decision models.
- DERs such as rooftop photovoltaics and battery storage introduce bidirectional power flows and alter transmission–distribution interactions.
- Integrated system planning can capture DER benefits and reduce overall system costs, but existing models primarily optimize investment and operation under uncertainty.
- Existing planning studies typically model DERs as controllable system resources rather than outcomes of customer adoption and operation decisions.
- Customer DER investment and operation are driven by electricity prices, tariff structures, and perceived financial benefits.
- The proposed multistage framework integrates planning, cost allocation, and customer decision models to represent customer-driven DER behaviour in system planning.
II. THE PROPOSED PLANNING MODEL
The proposed framework combines transmission–distribution planning, cost allocation, and customer decision stages. It explicitly models customer DER adoption and operation using energy needs and incentives, then incorporates customer actions into planning through updated hourly loads.
- The framework comprises planning, cost allocation, and customer decision stages based on established models.
- Customer decisions to adopt and operate DERs are explicitly modeled using energy needs and incentives.
- Customer actions enter the integrated planning model in a subsequent stage as updated hourly load profiles.
A. First planning stage
The first planning stage establishes a no-DER baseline by jointly expanding transmission and distribution systems while minimizing annualized investment and operating costs under network constraints.
- The first stage runs integrated transmission and distribution expansion planning to establish a baseline without DERs.
- The objective minimizes total annualized investment and operating costs.Investment costs cover transmission and distribution expansion, while operating costs include generation production and load shedding.
- Investment costs include transmission-connected generation and candidate transmission and distribution lines.
- Operating costs represent existing transmission-connected generation production and load shedding of demand.
- The model uses DC power flow for transmission and Linearized DistFlow for distribution, with limits on flows, capacity, load shedding, and distribution-node voltage magnitudes.
B. Cost allocation stage
The cost allocation stage uses first-stage power and load-shedding results to calculate integrated customer costs and prices at distribution nodes. These outputs identify likely DER adopters and inform subsequent DER capacity decisions.
- First-stage active power and load-shedding results determine each distribution customer’s cost and price per node.
- The allocation model assigns customers integrated costs combining transmission and distribution components.
- Transmission cost reflects supply from the transmission system to a distribution node, while distribution cost reflects internal distribution flows serving demand.
- Integrated price is calculated as integrated cost divided by net load demand.
- Customers with the five highest costs and prices are selected as candidates for DER adoption.
C. Customer decision stage
The customer decision stage uses a retailer-based economic framework to evaluate DER adoption and customer-grid interactions. It compares DER and non-adoption costs while updating hourly load profiles for later planning.
- Customer DER adoption: The retailer framework uses hourly load data and integrated prices to calculate customer payments, retailer revenues and profits, distribution-company payments, and DER adoption.Adoption is evaluated across multiple decision intervals.
- Customer DER adoption: DER adoption compares PV and battery configurations’ LCOE with the LCOE of not adopting DERs and considers possible grid defection.LCOE includes capital, O&M, prior-investment, and electricity-bill costs.
- Customer operation: A household energy management system determines hourly net exchange and updates load profiles for the planning model.Net exchange includes consumption from or injection into the grid, while customers must generate sufficient annual energy to meet demand.
D. Second planning stage
The second planning stage reruns the integrated planning model with customer-updated load profiles. It compares a planner-driven no-DER scenario with scenarios reflecting customer-driven DER adoption and operation.
- D. Second planning stage: The integrated planning model is rerun using the updated load profile from the customer decision stage.This enables comparison of planning outcomes before and after customer-driven DER adoption.
- D. Second planning stage: The framework compares a planner-driven scenario excluding DER integration with a customer-driven scenario that includes DER adoption and operation.The comparison evaluates how customer decisions enter integrated planning.
- D. Second planning stage: Customer decision outputs therefore serve as inputs to the subsequent planning model.The staged procedure links customer adoption and operation with system planning.
III. RESULTS
The results use a 36-bus test system with six transmission nodes and 30 distribution nodes. The study combines system data from prior work with hourly Alberta load data and technology-cost assumptions.
- Test system: The test system contains 36 buses, including 6 transmission nodes and 30 distribution nodes.Each distribution system comprises 15 nodes.
- Test system: Figure 1 presents an abridged network with two distribution systems whose nodes are labeled 4-1 through 4-15 and 5-1 through 5-15.The network structure supports evaluation of customer actions within distribution systems.
- Data: The study uses peak demand, network, generation, investment, and load-shedding data from prior work, plus hourly AESO load data from May 1, 2020, to May 1, 2021.PV, battery, and O&M costs are drawn from NREL assumptions that decline annually under conservative or advanced cases.
A. First planning, cost allocation, and customer decision stage results
The study selects five high-cost customers for DER adoption and evaluates four combinations of technology-cost assumptions and feed-in-tariff incentives. Adoption increases with advanced costs and especially with incentives, while battery storage is not adopted.
- Customer selection: Nodes 4-1, 4-3, 4-7, 4-14, and 5-7 were identified as high-cost customers and selected for DER adoption.Selection follows the first planning and cost allocation stages.
- Scenario design: Four scenarios vary conservative or advanced PV, battery, and O&M costs and whether a $0.3/MWh feed-in tariff is offered.Scenarios 1 and 2 exclude the incentive, while Scenarios 3 and 4 include it.
- Adoption results: Approximately 75% adoption growth from Scenario 1 to Scenario 2 and approximately 300% growth from Scenario 1 to Scenarios 3 and 4 were observed.Scenarios 3 and 4 have identical capacities because PV adoption is capped by annual consumption; customers adopt no battery storage in any scenario.
B. Second planning stage and additional results
The second planning stage compares updated customer-driven DER scenarios with the no-DER baseline, showing lower system costs, reduced transmission loading, and redistributed customer costs.
- Second planning stage: Updated hourly load profiles from Scenarios 1–4 were incorporated into the original load data for second-stage system-cost comparisons.Figure 3 summarizes system costs across all scenarios.
- System costs: 25.7%: Overall system costs decline approximately 25.7% in Scenarios 3 and 4, alongside 7.61% lower production costs and 89.4% lower load-shedding costs.These reductions are associated with increased DER adoption and lower reliance on transmission supply.
- Transmission loading: 62.3%: Total apparent power flow into node 4 falls from 77.24 MVA to 29.1 MVA in Scenario 4 compared with no DERs.Flow into node 5 also decreases by 10.3%, from 118.86 MVA to 106.64 MVA.
- Transmission loading: DERs in Scenario 4 supply power locally, reducing loading across most transmission lines compared with the no-DER scenario.The comparison uses active power values at a given instance across the model time horizon.
- Customer costs: Integrated costs decrease significantly for DER-adopting customers and for some electrically adjacent non-adopters, while increasing for the remaining non-adopters.The affected adopting nodes are 4-1, 4-3, 4-7, 4-14, and 5-7; other costs are redistributed among non-adopting nodes.
IV. CONCLUSION
The framework models customer DER adoption alongside integrated planning, showing system and customer benefits while identifying limits from incentive assumptions, sequential staging, and benchmark-only validation.
- Higher DER uptake improves cost efficiency and reliability, reduces transmission loading, and lowers costs for adopting and some non-adopting customers.Reduced load shedding indicates that customer DERs help alleviate generation shortfalls during constrained conditions, although customers are not explicitly compensated for this reliability contribution.
- Feed-in tariffs encourage customer participation and increase DER injections, indirectly improving system reliability.The framework assumes customers respond solely to economic incentives, with reliability benefits emerging as a byproduct.
- Explicit compensation for customer reliability services remains a proposed direction for aligning customer incentives with system needs.The paper suggests that improved alignment could further reduce costs, relieve network loading, and support more balanced benefit allocation while maintaining planning oversight.
- Sequential planning creates a disconnect between system outcomes and customer-driven DER adoption, so costs and adoption may not reflect a fully coordinated equilibrium.Planning is conducted first without DERs, followed by customer decisions, limiting feedback between system decisions and customer behaviour.
- The methodology is demonstrated on a benchmark test system and requires application to real transmission and distribution networks for practical validation.Future work should evaluate performance under practical planning conditions and further validate the observed benefits of customer-driven DER adoption.
- Realizing the full value of DERs requires accounting for both system- and customer-level benefits within integrated planning frameworks.