Congestion management in smart grids with flexible demand considering the payback effect

Esmat, Ayman; Usaola, Julio; Fernández, Andrés Martínez

doi:10.1109/isgteurope.2016.7856233

Cited by 10 publications

(7 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another type of risk associated with demand-side uncertainty is the rebound effect [34] which is also known as the payback effect [35]. We can observe the rebound effect in the demand profile of a power system when the demand-side participation exits.…”

Section: • Network Availability Capacity Uncertainty and Investments ...mentioning

confidence: 98%

Characterization of flexible electricity in power and energy markets

Kara,

Tomasgard,

Farahmand

2021

Preprint

View full text Add to dashboard Cite

The authors provide a comprehensive overview of flexibility characterization along the dimensions of time, spatiality, resource, and risk in power systems. These dimensions are discussed in relation to flexibility assets, products, and services, as well as new and existing flexibility market designs. The authors argue that flexibility should be evaluated based on the dimensions under discussion. Flexibility products and services can increase the efficiency of power systems and markets if flexibility assets and related services are taken into consideration and used along the time, geography, technology, and risk dimensions. Although it is possible to evaluate flexibility in existing market designs, a local flexibility market may be needed to exploit the value of the flexibility, depending on the dimensions of the flexibility products and services. To locate flexibility in power grids and prevent incorrect valuations, the authors also discuss TSO-DSO coordination along the four dimensions, and they present interrelations between flexibility dimensions, products, services, and related market designs for productive usage of flexible electricity.

show abstract

Section: • Network Availability Capacity Uncertainty and Investments ...mentioning

confidence: 98%

Characterization of flexible electricity in power and energy markets

Kara,

Tomasgard,

Farahmand

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…In this work, the DR flexibility is exclusively described in a power and energy domain, and it is modeled similarly to generic storage with a unitary efficiency. Then, additional constraints should be introduced to compute the "virtual state of charge" SOC DR t and keep it between the bounds (typically 0 and 100%) during the studied interval (8).…”

Section: Problem Formulationmentioning

confidence: 99%

“…The above-mentioned constraints force system operators to use any options for ensuring the load connection on short and mid-term horizons. Such alternatives for network reinforcement consist of using flexibilities from controllable distributed generation, storage, demand-side management [8], or Dynamic Thermal Rating (DTR) [9,10]. For instance, the expensive reinforcement of a primary substation transformer can be postponed by the coordinated control of Distributed Energy Resources (DER) and/or by considering the real thermal rating of power equipment.…”

Section: Introductionmentioning

confidence: 99%

Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime

et al. 2021

View full text Add to dashboard Cite

(1) Background: This paper proposes a strategy coupling Demand Response Program with Dynamic Thermal Rating to ensure a transformer reserve for the load connection. This solution is an alternative to expensive grid reinforcements. (2) Methods: The proposed methodology firstly considers the N-1 mode under strict assumptions on load and ambient temperature and then identifies critical periods of the year when transformer constraints are violated. For each critical period, the integrated management/sizing problem is solved in YALMIP to find the minimal Demand Response needed to ensure a load connection. However, due to the nonlinear thermal model of transformers, the optimization problem becomes intractable at long periods. To overcome this problem, a validated piece-wise linearization is applied here. (3) Results: It is possible to increase reserve margins significantly compared to conventional approaches. These high reserve margins could be achieved for relatively small Demand Response volumes. For instance, a reserve margin of 75% (of transformer nominal rating) can be ensured if only 1% of the annual energy is curtailed. Moreover, the maximal amplitude of Demand Response (in kW) should be activated only 2–3 h during a year. (4) Conclusions: Improvements for combining Demand Response with Dynamic Thermal Rating are suggested. Results could be used to develop consumer connection agreements with variable network access.

show abstract

“…Accordingly, DSOs are not allowed to own power generation or consumption units [36]. Proposals in which DSOs can directly control DERs in order to mitigate congestions or manipulate voltages [37], or in which the DSO acts as a market operator [38], are not compatible with this principle. Services that make aggregators directly responsible for keeping voltages and currents at specific grid nodes within an allowed range [39] have also been proposed.…”

Section: Literature Review Of Local Flexibility Marketsmentioning

confidence: 99%

EcoGrid 2.0: A large-scale field trial of a local flexibility market

et al. 2020

View full text Add to dashboard Cite

The number of distributed energy resources installed in distribution networks is steadily increasing. Their flexibility can be leveraged by aggregators and used in the wholesale markets. However, the utilization of this flexibility cannot neglect the operating conditions of distribution networks, and thus some form of coordination between distribution and transmission system operators must exist. The idea of operating local flexibility markets has been proposed to address these issues, but experience from real-life demonstrations is still missing. The Danish project EcoGrid 2.0 has designed, implemented and tested a local flexibility market with 800 participating customers, which runs in parallel with the wholesale markets. First, this paper presents a method to identify and quantify the value of possible flexibility services that are beneficial to the distribution system operator. Next, it provides insight from the operation of a real local flexibility market, with a large number of controllable loads. Results show that aggregators are able to reliably shape the load of residential heating units to deliver flexibility services, despite the presence of large uncertainties. Services can act as an insurance policy against rare but consequential network overloadings and outages. In these rare cases flexibility services can increase social welfare significantly. However, such services should be carefully selected to avoid adverse effects. Finally, we provide with guidelines and some general remarks on the nature and the desirable characteristics of those markets and services.

show abstract

Congestion management in smart grids with flexible demand considering the payback effect

Cited by 10 publications

References 10 publications

Characterization of flexible electricity in power and energy markets

Characterization of flexible electricity in power and energy markets

Demand Response Coupled with Dynamic Thermal Rating for Increased Transformer Reserve and Lifetime

EcoGrid 2.0: A large-scale field trial of a local flexibility market

Contact Info

Product

Resources

About