A traffic light system for enhancing the utilization of demand response in LV distribution networks

Medved, Tomi; Prislan, B.; Zupančič, Jernej; Gubina, Andrej F.

doi:10.1109/isgteurope.2016.7856303

Cited by 4 publications

(4 citation statements)

References 4 publications

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“…The 'traffic light' concept has been discussed in several other works including: [5] where DSO-TSO cooperation in each system state (green/amber/red) is considered but not demonstrated; [23] and [24] where implementations are outlined without any test case demonstrations; [25] and [26] where implementations are demonstrated at LV but with limited consideration of DSO-TSO interaction.…”

Section: Traffic Light Conceptmentioning

confidence: 99%

Design of a DSO‐TSO balancing market coordination scheme for decentralised energy

Edmunds

Galloway

Elders

et al. 2020

IET Generation, Transmission & Distribution

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The proliferation of distributed generation and the electrification of heat and transport pose significant challenges to distribution system operators (DSOs), and transmission system operators (TSOs). These challenges include the choice between network upgrades or operating increasingly constrained networks, with a reliance on the flexibility of distributed energy resources (DERs). This paper presents a novel market based coordination scheme, which allows both the DSO and TSO to access DER flexibility, while respecting distribution system limits. The DSO's objective in this work is to minimise the cost incurred by DSO adjustments to DERs, required to ensure stable distribution network operation. The methodology presented has the advantages of being compatible with existing TSO balancing market operation, and scalable enough to include multiple DSO markets coordinating with the TSO. The approach is demonstrated on a section of GB distribution network, using high DER growth scenario data for the year 2030. The case studies demonstrate the proposed DSO market mechanism to maintain thermal and voltage limits during periods of peak demand and DER output. The DSO is given priority in using DERs to solve distribution network constraints, however, significant flexibility remains for the TSO even during periods of peak demand and maximum export.

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Section: Traffic Light Conceptmentioning

confidence: 99%

Design of a DSO‐TSO balancing market coordination scheme for decentralised energy

Edmunds

Galloway

Elders

et al. 2020

IET Generation, Transmission & Distribution

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show abstract

“…The concept used in our simulations is the advanced TLS developed in Project INCREASE where the DSO checks the feasibility of the aggregator's proposed DR unit schedule 15 min ahead of the power delivery using a power flow algorithm (INCREASE FP7 project, 2015;Medved, Prisaln, Zupan ci c, & Gubina, 2016). If the power flow results indicate no network limit violations, the DR schedule is accepted.…”

Section: Traffic Light Systemmentioning

confidence: 99%

The use of intelligent aggregator agents for advanced control of demand response

Medved

Artač

Gubina

2018

WIREs Energy & Environment

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With the integration of distributed renewable energy sources (DRES) and active demand (e.g., units providing demand response, DR) in the distribution grid, the importance of monitoring the network conditions, managing the line congestions and observing the voltage levels is increasing. The distribution system operator (DSO) needs a mechanism, such as the traffic light system, to screen and approve the proposed operation schedules of the flexible active resources in the distribution grid. Their aggregated control will require the aggregators to employ advanced scheduling algorithms. The DR scheduling algorithms can be set to pursue various goals, for example, maximization of profit or cost reduction, grid support, or provision of the ancillary services. In the paper, we present a new DR scheduling approach suitable for the aggregation agent using approximate Q‐learning (AQL) algorithm scheduling. We present the AQL algorithm and the associated assumptions used in simulations on a real‐world low‐voltage (LV) grid model, comparing the AQL approach results to those of the economic scheduling and the energy scheduling approaches. Our assumption was that the AQL approach could outperform the energy or economic approaches as the AQL agent would be able to learn to avoid the scheduling penalties. The results of our research show that the aggregator agent using the economic approach shows the best economic performance, but causes the most schedule violations. The energy scheduling approach improves the network voltage profile but lowers the aggregator's profit. The AQL approach results in the agent's economic performance between the former two approaches with minimal schedule violations, confirming our research hypothesis. This article is categorized under: Concentrating Solar Power > Systems and Infrastructure Energy Systems Economics > Systems and Infrastructure Energy Infrastructure > Systems and Infrastructure Energy Efficiency > Economics and Policy

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“…The authors of Deutsch et al (2014), Medved et al (2016) propose an implementation of the yellow state based on forecasts. In case of a predicted power quality problem, the market mechanisms are used to buy flexibility for this time window.…”

Section: Grid Constraints Versus Energy Marketsmentioning

confidence: 99%

“…In case of a predicted power quality problem, the market mechanisms are used to buy flexibility for this time window. An updated version of the traffic light concept is introduced in Medved et al (2016) which may be used by the DSO to control Demand Response (DR) units. The proposed approach depends on information from power flow calculation based on the joint load schedule of DR units and the residual loads.…”

Section: Grid Constraints Versus Energy Marketsmentioning

confidence: 99%

Enhancing power quality in electrical distribution systems using a smart charging architecture

et al. 2018

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The electrification of the mobility sector comes with multiple challenges such as the lack of information on when, where, how long and how fast charging processes of electric vehicles will take place. In order to keep up with increasing power demand of charging processes, besides better predictions also the active control of charging processes will be necessary to minimize infrastructure costs. This work deals with a realtime mechanism for supporting the Power Quality (PQ) in electric distribution grids in terms of congestion and voltage management. In the paper, we propose a distributed smart charging approach that considers real-time conditions of the distribution grid provided by an event-driven architecture that collects data from different points in the grid. Our approach adopts the traffic light model, which allows smooth changing of the charging power to avoid drastic changes of the grid state. In order to be ready for real-world application, the algorithm is validated by a series of experiments on two setups: Pure software (co-)simulation and Power Hardware In the Loop (PHIL) where physical charging stations and electric cars are controlled in a laboratory setup.

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A traffic light system for enhancing the utilization of demand response in LV distribution networks

Cited by 4 publications

References 4 publications

Design of a DSO‐TSO balancing market coordination scheme for decentralised energy

Design of a DSO‐TSO balancing market coordination scheme for decentralised energy

The use of intelligent aggregator agents for advanced control of demand response

Enhancing power quality in electrical distribution systems using a smart charging architecture

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