Demand aggregator flexibility forecast: Price incentives sensitivity assessment

Kotsis, Grigorios; Moschos, Ioannis; Corchero, Cristina; Cruz-Zambrano, Miguel

doi:10.1109/eem.2015.7216756

Cited by 10 publications

(9 citation statements)

References 2 publications

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“…Various aggregator algorithms with real-time energy management systems have been defined and tested supporting the grouping of neighborhood buildings (Igualada et al, 2014;Kotsis et al, 2015).…”

Section: Smart Metering and Balancing The Energy Production With The Energy Consumptionmentioning

confidence: 99%

Smart cooling systems for the urban environment. Using renewable technologies to face the urban climate change

Kolokotsa

2017

Solar Energy

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Urban heat island and global warming increase the urban ambient temperature. Increased temperatures have a tremendous effect on the energy demand for cooling, with a great impact on peak and total electricity demand.Renewable technologies in the urban environment have been widely regarded as an increasingly important solution to deal with the climate change challenges and energy security. Significant effort is performed in the integration of photovoltaic panels (PV) and micro turbines in the urban context showing a substantial reduction in CO 2 emissions. At the same time attention is drawn to an often-overlooked aspect regarding renewable energy technologies, in that despite having low operating costs their overall benefits are often not well understood and consequently are often evaluated as being less profitable than fossil fuel alternatives, even though they are future proof about energy cost.The aim of the present paper is to describe the role of renewable energy technologies and zero carbon technologies in covering the future increased energy demand for cooling.The integration of photovoltaics in the urban environment through PV facades, pavements, and shading devices are discussed.The role of Information and Computer Technology and smart grids in the efficient management of renewables in urban scale is discussed. The role of smart metering, users 'integration and demand response capabilities for future zero energy urban neighborhoods is revealed.

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Section: Smart Metering and Balancing The Energy Production With The Energy Consumptionmentioning

confidence: 99%

Smart cooling systems for the urban environment. Using renewable technologies to face the urban climate change

Kolokotsa

2017

Solar Energy

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“… Offering prosumers flexibility through the energy market. In this sense, it is vitally important that the aggregator controls the following pillars on which its business model is based: i) customer characterisation, ii) prediction of energy consumption and generation, iii) market prediction, iv) optimisation of energy planning and v) market and customer portfolio management [16].…”

Section: Introductionmentioning

confidence: 99%

Optimisation of an aggregator’s customer portfolio based on inter-user compatibility

Cano-Martínez¹,

Peñalvo-López²,

León-Martínez³

et al. 2022

REPQJ

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This paper aims to present a methodology for optimizing the customers’ portfolio of an aggregator by analysing the compatibility between prosumers (clients). The methodology evaluates two main components: energy and socioeconomic. With this, the intention is to maximise the economic benefits of the aggregator and to establish a personalised tariff according to the user profile. Since this figure was conceived, efforts have been mainly aimed at meeting only and exclusively the energy demand requirements without taking into consideration prosumers socio-economic profiles and the synergies among them. This paper, therefore, presents a methodology in which a compatibility index based on the energy and socioeconomic profile of each client is defined. In addition, the application of this methodology to a practical case is presented.

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“…DR will have influence on different system costs and may increase the reliability of the system. By increasing network flexibility supported by bi-directional communications in the system, it will enable higher levels of penetration of small renewable energy resources [7,8]. In this context, it is also necessary to aggregate Distributed Generation (DG) units.…”

Section: Introductionmentioning

confidence: 99%

Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response

2019

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Distributed energy resources can improve the operation of power systems, improving economic and technical efficiency. Aggregation of small size resources, which exist in large number but with low individual capacity, is needed to make these resources’ use more efficient. In the present paper, a methodology for distributed resources management by an aggregator is proposed, which includes the resources scheduling, aggregation and remuneration. The aggregation, made using a k-means algorithm, is applied to different approaches concerning the definition of tariffs for the period of a week. Different consumer types are remunerated according to time-of-use tariffs existing in Portugal. Resources aggregation and remuneration profiles are obtained for over 20.000 consumers and 500 distributed generation units. The main goal of this paper is to understand how the aggregation phase, or the way that is performed, influences the final remuneration of the resources associated with Virtual Power Player (VPP). In order to fulfill the proposed objective, the authors carried out studies for different time frames (week days, week-end, whole week) and also analyzed the effect of the formation of the remuneration tariff by considering a mix of fixed and indexed tariff. The optimum number of clusters is calculated in order to determine the best number of DR programs to be implemented by the VPP.

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Demand aggregator flexibility forecast: Price incentives sensitivity assessment

Cited by 10 publications

References 2 publications

Smart cooling systems for the urban environment. Using renewable technologies to face the urban climate change

Smart cooling systems for the urban environment. Using renewable technologies to face the urban climate change

Optimisation of an aggregator’s customer portfolio based on inter-user compatibility

Multi-Period Observation Clustering for Tariff Definition in a Weekly Basis Remuneration of Demand Response

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