A novel behavioral real time pricing scheme for the active energy consumers’ participation in emerging flexibility markets

Steriotis, Konstantinos; Τσαούσογλου, Γεώργιος; Efthymiopoulos, Nikolaos; Makris, Prodromos; Varvarigos, Emmanouel

doi:10.1016/j.segan.2018.05.002

Cited by 57 publications

(34 citation statements)

References 43 publications

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“…A study by the Energy Networks Association (ENA) demonstrated that both time-based and market price-based tariffs have a positive effect on peak-demand reduction compared to a flat-tariff [10]. Sterioitis et al [11] showed that tariffs could be tailored down to individual customers based on their consumption behaviour.…”

Section: Smart and Fair Tariffs For Active Demand Managementmentioning

confidence: 99%

Network capacity charge for sustainability and energy equity: A model-based analysis

Khalilpour

Lusis

2020

Applied Energy

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It is long known that the afternoon peak demand accounts for over-investment in the electricity network assets. This results in a high price of delivered electricity which does not fairly differentiate between peak and non-peak users. Energy tariff is proven to be one of the best demand-side management (DSM) tools for shaping consumers' behaviour. While electricity pricing models, such as inclining block and time-of-use tariffs, have received decent attention as successful mechanisms, there are little discussions about another efficient tariff known as a rollover network capacity charge. It is a penalty for the highest recorded power usage over the previous reading cycle (or year) which is introduced to commercial users in some jurisdictions. With recent price reduction in distributed generation and storage (DGS) systems, the interest has increased in devising policies for directing the household and commercial consumers' behaviour towards using DGS systems in line with DSM objectives. In this paper, we have integrated the rollover network capacity charge into DGS systems investment analysis. The results from a few case studies show the positive impact of capacity charge in directing the peak-consumers' investment decisions towards DSM tools (e.g., energy storage) to curb their peak demands. This not only improves the resilience of the network but also promises as an effective mechanism in energy-justice nexus by avoiding the transfer of the associated costs of peak demand to all users.

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Section: Smart and Fair Tariffs For Active Demand Managementmentioning

confidence: 99%

Network capacity charge for sustainability and energy equity: A model-based analysis

Khalilpour

Lusis

2020

Applied Energy

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“…The load profile, L(t), of the locality is shown in Real-time electricity prices usually depend on the wholesale electricity market and vary over time. In this study, those varied price-rates are considered due to their effectiveness over others [23]. The purchasing and selling RTP are represented by C(t) (cents/kW h) and considered identical, i.e C buy (t) = C sell (t) = C(t), for simplicity purpose.…”

Section: Loads and Grid Utilitymentioning

confidence: 99%

Energy Management of Community Microgrids Considering Uncertainty using Particle Swarm Optimisation

Ma¹,

Chakrabortty²,

Ryan³

et al. 2020

Preprint

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Although energy management of a microgrid is generally performed using a day-ahead scheduling method, its effectiveness has been questioned by the research community due to the existence of high uncertainty in renewable power generation, power demand and electricity market. As a result, real-time energy management schemes are recently developed to minimise the operating cost of a microgrid while high uncertainty presents in the network. This paper develops modified particle swarm optimisation (MPSO) algorithms to solve optimisation problems of energy management schemes for a community microgrid and proposes a scheduling approach after taking into consideration high uncertainty to effectively minimise the operational cost of the microgrid. The optimisation problems are formulated for real-time and scheduling approaches, and solution methods are developed to solve the problems. It is observed that the scheduling program demonstrates superior performance in all the cases, including uncertainty in prediction, as compared to the other energy management approaches, although solutions have significant deviations due to prediction errors.

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“…For that purpose, different dynamic pricing systems can be introduced according to the objectives to be achieved. As a matter of fact, on the basis of existing rate schemes, the suitable options can be grouped into four main categories: Time Of Use (TOU); Critical Peak Pricing (CPP); Peak Time Rebate (PTR); Real Time Pricing (RTP) [45][46][47][48].…”

Section: Contract or Marked Basedmentioning

confidence: 99%

Analysis on the potential of an energy aggregator for domestic users in the Italian electricity system

Santoli

Mancini

Basso

2019

Second International Conference on Material Science, Smart Structures and Applications: Icmss-2019

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This study is focused on the definition of an energy aggregator model for domestic users, offering the Demand Response (DR) optimization and additional services. The research project is based on the Italian electricity system analysis pointing out the renewables high contribution, the poor domestic users' electrification and the need to figure out those issues by a demand flexibility system implementation. Moreover, the characterization of Italian domestic users' energy loads allowed to identify the suitable strategies to get higher flexibility degree. Thus, three case studies have been considered to assess the achievable economic savings due to the DR implementation, accounting for the revenue for dispatching services as well as the intraday energy price variations on the Italian market. It emerged that the demand side flexibility implementation offers benefits to the Italian electricity system but entails small economic benefits for the endusers. Additionally, the adoption of such a system is quite complicated due to the lack of suitable and reliable automation devices. For that reason, a potential energy aggregator for domestic users will have to search funds for its own operation providing customers with additional services, such as energy saving and assisted-living, by using of ICT along with automation within each dwelling.

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A novel behavioral real time pricing scheme for the active energy consumers’ participation in emerging flexibility markets

Cited by 57 publications

References 43 publications

Network capacity charge for sustainability and energy equity: A model-based analysis

Network capacity charge for sustainability and energy equity: A model-based analysis

Energy Management of Community Microgrids Considering Uncertainty using Particle Swarm Optimisation

Analysis on the potential of an energy aggregator for domestic users in the Italian electricity system

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