Distribution Grid Constraints Research Articles

A Three-Stage Model to Manage Energy Communities, Share Benefits and Provide Local Grid Services

This paper proposes a three-stage model for managing energy communities for local energy sharing and providing grid flexibility services to tackle local distribution grid constraints. The first stage addresses the minimization of each prosumer’s individual energy bill by optimizing the schedules of their flexible resources. The second stage optimizes the energy bill of the whole energy community by sharing the prosumers’ energy surplus internally and re-dispatching their batteries, while guaranteeing that each prosumer’s new energy bill is always be equal to or less than the bill that results for this prosumer from stage one. This collective optimization is designed to ensure an additional collective benefit, without loss for any community member. The third stage, which can be performed by the distribution system operator (DSO), aims to solve the local grid constraints by re-dispatching the flexible resources and, if still necessary, by curtailing local generation or consumption. Stage three minimizes the impact on the schedule obtained at previous stages by minimizing the loss of profit or utility for all prosumers, which are furthermore financially compensated accordingly. This paper describes how the settlement should be performed, including the allocation coefficients to be sent to the DSO to determine the self-consumed and supplied energies of each peer. Finally, some case studies allow an assessment of the performance of the proposed methodology. Results show, among other things, the potential benefits of allowing the allocation coefficients to take negative values to increase the retail market competition; the importance of stage one or, alternatively, the need for a fair internal price to avoid unfair collective benefit sharing among the community members; or how stage three can effectively contribute to grid constraint solving, profiting first from the existing flexible resources.

Coordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefit

Increased worldwide uptake of Electric Vehicles (EVs) accentuates the need for developing coordinated EV charging and discharging methods that mitigate detrimental and sustained under-voltage and over-voltage conditions in distribution networks. In this paper, a centrally coordinated EV charge-discharge scheduling method is proposed, referred to as Network-aware EV Charging (and Discharging) N-EVC(D), that takes into account both EV customer economics and distribution grid constraints. Specifically, N-EVC(D) is designed to maintain quasi-steady-state feeder voltages within statutory power quality limits, while minimizing EV customer operational costs associated with: (1) purchasing (or otherwise being compensated for delivering) electricity on a time-of-use tariff; and (2) battery degradation due to frequent charging and discharging. The optimization problem for N-EVC(D) is formulated as a quadratic program, with voltage constraints to limit voltage variability across a radial distribution feeder, and individual EV constraints to satisfy heterogeneous EV charge requirements. In N-EVC(D), each grid-connected EV follows an operator-specified battery schedule that is obtained by solving the proposed quadratic program. A receding horizon implementation is also proposed to support near-real-time N-EVC(D) operations while accommodating non-deterministic EV arrivals and departures. The benefits of N-EVC(D) are assessed by means of numerical simulations carried out on an IEEE test feeder populated with a real-world dataset of residential load collected from households within an Australian distribution network. The simulation results confirm that N-EVC(D) mitigates non-compliant voltage deviations that would otherwise occur when voltage constraints are not enforced. Compared to uncoordinated EV charging, N-EVC(D) offers a 92% – 111% reduction in the operational costs incurred by EV customers.

Local use of flexibilities on DSO level – outcomes of the InterFlex project

InterFlex investigated the INTERactions between stakeholders and the technical and economic potential of local FLEXibilities to relieve existing or prevent future distribution grid constraints. The project explored new solutions to foster the development of distributed energy resources and prepare the electric system for new uses including e-mobility.

Modeling coordination between renewables and grid: Policies to mitigate distribution grid constraints using residential PV-battery systems

Distributed photo-voltaic (PV) generation is one of the pillars of energy transitions around the world, but its deployment in the distribution grid requires costly reinforcements and expansions. Prosumage – consisting of a household-level PV unit coupled with a battery storage system – has been proposed as an effective means to facilitate the integration of renewable energy sources and reduce distribution grid stress. However, tapping its full potential requires regulatory interventions; otherwise, system costs could rise despite increasing flexibility. We analyze the effectiveness of different policy schemes to mitigate the need for distribution capacity expansion by incentivizing beneficial storage operation. Our novel top-down modeling approach allows analyzing effects on market prices, storage dispatch, induced distribution grid requirements, system costs, and distributional implications. Based on German power system data, numerical results indicate that distribution grid requirements can be reduced through simple feed-in policies. A uniform limit on maximum grid feed-in can leave distribution system operators better off, even if they fully compensate prosumage households for foregone revenue. Policies imposing more differentiated limits at the regional level result in only marginal efficiency improvements. Complete self-sufficiency (autarky) is socially undesirable, as it confines important balancing potential and can increase system costs despite adding storage.

Modeling Coordination Between Renewables and Grid: Policies to Mitigate Distribution Grid Constraints Using Residential PV-Battery Systems

Distributed photo-voltaic (PV) generation is one of the pillars of energy transitions around the world, but its deployment in the distribution grid requires costly reinforcements and expansions. Prosumage - consisting of a household-level PV unit coupled with a battery storage system - has been proposed as an effective means to facilitate the integration of renewable energy sources and reduce distribution grid stress. However, tapping its full potential requires regulatory interventions; otherwise, system costs could rise despite increasing flexibility. We analyze the effectiveness of different policy schemes to mitigate the need for distribution capacity expansion by incentivizing beneficial storage operation. Our novel top-down modeling approach allows analyzing effects on market prices, storage dispatch, induced distribution grid requirements, system costs, and distributional implications. Numerical results for German power system data indicate that required distribution grid requirements can be reduced through simple feed-in policies. A uniform limit on maximum grid feed-in can leave distribution system operators better off, even if they fully compensate prosumage households for foregone revenue. Policies imposing more differentiated limits at the regional level result in only marginal efficiency improvements. Complete self-sufficiency (autarky) is socially undesirable, as it confines important balancing potential and can increase system costs despite adding storage.

Modeling Coordination between Renewables and Grid: Policies to Mitigate Distribution Grid Constraints Using Residential PV-Battery Systems

Distributed photo-voltaic (PV) generation is one of the pillars of energy transitions around the world, but its deployment in the distribution grid requires costly reinforcements and expansions. Prosumage - consisting of a household-level PV unit coupled with a battery storage system - has been proposed as an effective means to facilitate the integration of renewable energy sources and reduce distribution grid stress. However, tapping its full potential requires regulatory interventions; otherwise, system costs could rise despite increasing flexibility. We analyze the effectiveness of different policy schemes to mitigate the need for distribution capacity expansion by incentivizing beneficial storage operation. Our novel top-down modeling approach allows analyzing effects on market prices, storage dispatch, induced distribution grid requirements, system costs, and distributional implications. Numerical results for German power system data indicate that required distribution grid requirements can be reduced through simple feed-in policies. A uniform limit on maximum grid feed-in can leave distribution system operators better off, even if they fully compensate prosumage households for foregone revenue. Policies imposing more differentiated limits at the regional level result in only marginal efficiency improvements. Complete self-sufficiency (autarky) is socially undesirable, as it confines important balancing potential and can increase system costs despite adding storage.

Robust multi‐objective PQ scheduling for electric vehicles in flexible unbalanced distribution grids

With increased penetration of distributed energy resources and electric vehicles (EVs), different EV management strategies can be used for mitigating adverse effects and supporting the distribution grid. This study proposes a robust multi-objective methodology for determining the optimal day-ahead EV charging schedule while complying with unbalanced distribution grid constraints. The proposed methodology considers partially competing objectives of an EV aggregator and the respective distribution system operator, and applies a fuzzy-based mechanism for obtaining the best-compromise solution. The robust formulation effectively considers the errors in the electricity price forecast and its influence on the EV schedule. Moreover, the impact of EV reactive power support on objective values and technical parameters is analysed both when EVs are the only flexible resources and when linked with other demand response programmes. The method is tested on a real Danish unbalanced distribution grid with 35% EV penetration to demonstrate the effectiveness of the proposed approach. It is shown that the proposed formulation guarantees an optimal EV cost as long as the price uncertainties are lower than the aggregator's conservativeness degree, and that EV reactive power improves local conditions without significantly affecting the EV cost.

Combining Market-Based Control with Distribution Grid Constraints when Coordinating Electric Vehicle Charging

ABSTRACT The charging of electric vehicles (EVs) impacts the distribution grid, and its cost depends on the price of electricity when charging. An aggregator that is responsible for a large fleet of EVs can use a market-based control algorithm to coordinate the charging of these vehicles, in order to minimize the costs. In such an optimization, the operational parameters of the distribution grid, to which the EVs are connected, are not considered. This can lead to violations of the technical constraints of the grid (e.g., under-voltage, phase unbalances); for example, because many vehicles start charging simultaneously when the price is low. An optimization that simultaneously takes the economic and technical aspects into account is complex, because it has to combine time-driven control at the market level with event-driven control at the operational level. Different case studies investigate under which circumstances the market-based control, which coordinates EV charging, conflicts with the operational constraints of the distribution grid. Especially in weak grids, phase unbalance and voltage issues arise with a high share of EVs. A low-level voltage droop controller at the charging point of the EV can be used to avoid many grid constraint violations, by reducing the charge power if the local voltage is too low. While this action implies a deviation from the cost-optimal operating point, it is shown that this has a very limited impact on the business case of an aggregator, and is able to comply with the technical distribution grid constraints, even in weak distribution grids with many EVs.

Optimal Day-Time Charging Strategies for Electric Vehicles considering Photovoltaic Power System and Distribution Grid Constraints

Electric vehicles (EVs) charging stations with a photovoltaic (PV) system for day-time charging have been studied. This paper investigates the issues such as how to coordinate the EVs customers for coordinated charging, maximize photovoltaic utilization, and reduce customers cost of EVs charging and operator electricity. Firstly, an ideal charging load curve was built through using the linear programming algorithm. This optimal curve, which realized maximum photovoltaic power and minimum electricity cost, was used as the objective curve. Secondly, a customer response model was utilized, to propose an optimization method and strategy for charging service tariffs. Particle swarm optimization algorithm was used for time-of-use tariffs and peak-flat-valley time division so that the charging load after price regulation was adjusted to best fit the objective curve, and both the EVs customers and the operator benefit from this. Finally, the proposed model and method have been verified by two cases.

Integrated Energy Management of Plug-in Electric Vehicles in Power Grid With Renewables

This paper presents an integrated control scheme for vehicle-to-grid (V2G) operation in the distribution grid with renewable energy sources. A hierarchical framework is proposed for V2G applications, and the mathematical models are built for both smart charging and V2G operation with distribution grid constraints. V2G power is regulated to minimize the total operating cost (TOC) while providing frequency regulation. The simulation results verify the control algorithm in coordinating distributed electric vehicle (EV) aggregations with the varying wind power and daily load. For V2G dynamic regulation, EVs connected in close proximity to wind power generators can locally compensate for the wind fluctuation with fast response and, hence, smooth out the power fluctuation at the bus having wind power generators and EVs. Each individual EV is strategically assigned to implement the simulated control algorithm through a bidirectional converter. An experimental platform is incorporated into the proposed integrated energy management to demonstrate the instantaneous response of EV battery storage.

Randomized PHEV Charging Under Distribution Grid Constraints

Plug-in Hybrid Electrical Vehicles (PHEV) are promising to improve energy efficiency and environment friendliness. However, without proper control, their charging will cause harmful impact on the power distribution grid, including load congestion and voltage drop. Instead of using centralized optimization which may need accurate predictions on key parameters, in this paper, a new decentralized random access framework is introduced to schedule the PHEV charging. The proposed distributed solution does not need accurate predictions and can be executed online. Simulation on a semi-urban residential medium voltage grid shows that our algorithm can effectively provide demand response to protect the distribution grid from bus congestion and voltage drop, and also improve its efficiency. Most importantly, this algorithm is simple to deploy.

Improving Electric Vehicle Charging Coordination Through Area Pricing

Meeting charging demands of large electric vehicle fleets will raise electrical load significantly and may pose challenges for today’s power system. Appropriate coordination of electric vehicle charging can reduce these threats. Acknowledging the interdependency between the transportation and the power system created by electric vehicles, we develop a charging coordination model based on German mobility data. We extend the prior work by explicitly accounting for both the temporal and the spatial dimension. We are thus able to analyze the loads from price-based EV fleet charging while at the same time accounting for distribution grid constraints. Furthermore, we propose a heuristic charging strategy based on limited trip and price information. Our results show that the sole use of time-based electricity prices for the coordination of electric vehicle charging produces high load spikes independent of the charging strategies and power levels. These peaks are induced by simultaneous charging activity and may cause stability problems within distribution grids in residential areas. To mitigate these load spikes, we introduce a spatial price component that reflects local capacity utilization. These local prices induce both a temporal and spatial shift of charging activity that mitigates the load spikes.

Improving Electric Vehicle Charging Coordination Through Area Pricing

Meeting charging demands of large electric vehicle fleets will raise electrical load significantly and may pose challenges for today's power system. Appropriate coordination of electric vehicle charging can reduce these threats. Acknowledging the interdependency between the transportation and the power system created by electric vehicles, we develop a charging coordination model based on German mobility data. We extend the prior work by explicitly accounting for both the temporal and the spatial dimension. We are thus able to analyze the loads from price-based EV fleet charging while at the same time accounting for distribution grid constraints. Furthermore, we propose a non-optimal heuristic charging strategy based on limited trip and price information.Our results show that the sole use of time-based electricity prices for the coordination of electric vehicle charging produces high load spikes for different strategies and charging power levels. These peaks are induced by simultaneous charging activity and may cause stability problems within distribution grids in residential areas. To mitigate these load spikes we introduce a spatial price component which reflects local capacity utilization. Such local prices induce both a temporal and spatial shift of charging activity which mitigates the load spikes.

Flexible Charging Optimization for Electric Vehicles Considering Distribution Grid Constraints

In this paper, the basic functions of an electric vehicle charging service provider are described with a focus on the associated optimization problems. A novel method of planning the charging of electric drive vehicles including electricity grid constraints, both voltage and power, is shown. The method establishes an individual charging plan for each vehicle and avoids distribution grid congestion while satisfying the requirements of the individual vehicle owners. The concepts proposed in this paper are tested on a simulated electricity grid. It is shown that both power and voltage constraints due to electric vehicle charging can be avoided using the proposed method.