A pricing scheme for electric utility's participation in day-ahead and real-time flexibility energy markets

Abstract

Liberalized electricity markets, smart grids and high penetration of renewable energy sources (RESs) led to the development of novel markets, whose objective is the harmonization between production and demand, usually noted as real time of flexibility markets. This necessitates the development of novel pricing schemes able to allow energy service providers (ESPs) to maximize their aggregated profits from the traditional markets (trading between wholesale/day-ahead and retail markets) and the innovative flexibility markets. In the same time, ESPs have to offer their end users (consumers) competitive (low cost) energy services. In this context, novel pricing schemes must act, among others, as automated demand side management (DSM) techniques that are able to trigger the desired behavioral changes according to the flexibility market prices in energy consumption curves (ECCs) of the consumers. Energy pricing schemes proposed so far, e.g. realtime pricing, interact in an efficient way with wholesale market. But they do not provide strong enough financial incentives to consumers to modify their energy consumption habits towards energy cost curtailment. Thus, they do not interact efficiently with flexibility markets. Therefore, we develop a flexibility real-time pricing (FRTP) scheme, which offers a dynamically adjustable level of financial incentives to participating users by fairly rewarding the ones that make desirable behavioral changes in their ECCs. Performance evaluation results demonstrate that the proposed FRTP is able to offer a 15%-30% more attractive trade-off between the stacked profits of ESPs, i.e. the sum of the profits from retail and flexibility markets, and the satisfaction of the consumers.

Implications of Growing Wind and Solar Penetration in Retail Electricity Markets with Gradual Demand Response

“…(2) a real-time pricing (RTP) scheme, which provides a more accurate price signal to consumers [33][34][35][36][37][38][39][40], and (3) a critical peak pricing that extends a TOU pricing scheme to incorporate a certain number of critical peak hours within a year [41][42][43][44].…”

A Fair Pricing Mechanism in Smart Grids for Low Energy Consumption Users

“…Based on simulation results, they performed a comparative analysis, and it was proven that the proposed B-RTP mechanism is beneficial for energy consumers in terms of energy bills reduction. Another behavioral RTP strategy, namely Fair RTP (FRTP) [24], has been proposed. This scheme fairly and dynamically adjusts incentives offered to participating energy consumers.…”

“…For example, [11], [12], [14]- [18], [20], [21] treated HECs and LECs at the same place without considering the fact that peak is only created due to LECs. Several previous studies [23], [24] proposed behavioral pricing strategy that can benefit consumers who actively participate in DR strategies even they cause peaks in different hours, and another study [25] proposed a pricing mechanism that only benefits utility companies in terms of peak alleviation. However, the peaks are only generated by HECs; thus, why are the LECs charged higher during peak hours?…”

Investigating the Electrical Demand-Side Management Potential of Industrial Steam Supply Systems Using Dynamic Simulation

“…273-277). The costs of energy consumption can be profitable for energyflexibility measures if the market offers dynamic pricing, which means that prices for electric energy varies over time for the consumer (industrial site) [32][33][34]. In the German electricity market, mainly large companies can profit from dynamic pricing models.…”