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Current feed‐in‐tariff (FIT) schemes for photovoltaic (PV) generators are set in the long term, thus they do not provide optimal dynamic price signals on the operational state of the distribution system. This work presents a transactive energy scheme to jointly optimise the operation of smart distribution networks, residential flexible loads and di...
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... The only other customer segment reported for all four prosumer subcategories is the pure consumer. [115,118,121,123,127,128,137,138] Pure consumer [61,76,79,83,93,94,104,108,132,[147][148][149][150][151] [119,120,[123][124][125][126][127]129,132,140,145,152,154,158,166,167,[171][172][173][174][175] Representative [90] - [141,145,146,157,176,177] Retailer [37,59,78,92,148,151] - [130,167,168,171,178] Grid operator [55] - [112,119,120,124,125,129,145,154,161,166,168,174,[179][180][181] a Entry refers to a paper that contains more than one energy market model. ...
... The only other customer segment reported for all four prosumer subcategories is the pure consumer. [115,118,121,123,127,128,137,138] Pure consumer [61,76,79,83,93,94,104,108,132,[147][148][149][150][151] [119,120,[123][124][125][126][127]129,132,140,145,152,154,158,166,167,[171][172][173][174][175] Representative [90] - [141,145,146,157,176,177] Retailer [37,59,78,92,148,151] - [130,167,168,171,178] Grid operator [55] - [112,119,120,124,125,129,145,154,161,166,168,174,[179][180][181] a Entry refers to a paper that contains more than one energy market model. ...
... The only other customer segment reported for all four prosumer subcategories is the pure consumer. [115,118,121,123,127,128,137,138] Pure consumer [61,76,79,83,93,94,104,108,132,[147][148][149][150][151] [119,120,[123][124][125][126][127]129,132,140,145,152,154,158,166,167,[171][172][173][174][175] Representative [90] - [141,145,146,157,176,177] Retailer [37,59,78,92,148,151] - [130,167,168,171,178] Grid operator [55] - [112,119,120,124,125,129,145,154,161,166,168,174,[179][180][181] a Entry refers to a paper that contains more than one energy market model. ...
... The only other customer segment reported for all four prosumer subcategories is the pure consumer. [115,118,121,123,127,128,137,138] Pure consumer [61,76,79,83,93,94,104,108,132,[147][148][149][150][151] [119,120,[123][124][125][126][127]129,132,140,145,152,154,158,166,167,[171][172][173][174][175] Representative [90] - [141,145,146,157,176,177] Retailer [37,59,78,92,148,151] - [130,167,168,171,178] Grid operator [55] - [112,119,120,124,125,129,145,154,161,166,168,174,[179][180][181] a Entry refers to a paper that contains more than one energy market model. ...
The emergence of peer-to-peer, collective or community self-consumption, and transactive energy concepts gives rise to new configurations of business models for local energy trading among a variety of actors. Much attention has been paid in the academic literature to the transition of the underlying energy system with its macroeconomic market framework. However, fewer contributions focus on the microeconomic aspects of the broad set of involved actors. Even though specific case studies highlight single business models, a comprehensive analysis of emerging business models for the entire set of actors is missing. Following this research gap, this paper conducts a systematic literature review of 135 peer-reviewed journal articles to examine business models of actors operating in local energy markets. From 221 businesses in the reviewed literature, nine macro-actor categories are identified. For each type of market actor, a business model archetype is determined and characterised using the business model canvas. The key elements of each business model archetype are discussed, and areas are highlighted where further research is needed. Finally, this paper outlines the differences of business models for their presence in the three local energy market models. Focusing on the identified customers and partner relationships, this study highlights the key actors per market model and the character of the interactions between market participants.
... within distribution networks, whereas TE markets operate at all scales. Whilst there are examples of small TE markets [45][46][47][48], there are also examples of TE markets which trade over entire electricity networks [49][50][51]. P2P and CSC markets often aim to incentivise the use of local generation [25,26,31,34,[52][53][54] or other local resources [26,38,55,56,56]. ...
... Papers presenting TE markets frequently aim to create a secure and efficient energy supply [57,58]. They do this by focusing on the balance of energy supply and demand [45,46,[49][50][51][59][60][61][62][63], and the integration of flexible loads or storage devices [58,[63][64][65][66][67][68][69]. ...
... TE markets can also operate as a sub-system of existing markets [67]. TE systems are set up in a market-based environment [48,59,62,64,69,78,81] aligning participants' interests with those of the wider energy system [50] by using economic incentives [48,49,57,59,63,78,81,86]. The use of locational marginal pricing [61,67,87] and the response to price signals [46,66,87,88] can optimise load behaviour. More details on markets structure and price formation can be found in Sections 3.2 and 3.3, respectively. ...
Peer-to-peer, community or collective self-consumption, and transactive energy markets offer new models for trading energy locally. Over the past five years, there has been significant growth in the amount of academic literature examining how these local energy markets might function. This systematic literature review of 139 peer-reviewed journal articles examines the market designs used in these energy trading models. A modified version of the Business Ecosystem Architecture Modelling framework is used to extract market model information from the literature, and to identify differences and similarities between the models. This paper examines how peer-to-peer, community self-consumption and transactive energy markets are described in current literature. It explores the similarities and differences between these markets in terms of participation, governance structure, topology, and design. This paper systematises peer-to-peer, community self-consumption and transactive energy market designs, identifying six archetypes. Finally, it identifies five evidence gaps which require future research before these markets could be widely adopted. These evidence gaps are the lack of: consideration of physical constraints; a holistic approach to market design and operation; consideration about how these market designs will scale; consideration of information security; and, consideration of market participant privacy.
... Literature which compares the profitability of traditional and P2P electricity markets finds that participants are more profitable in P2P markets [10]- [12]. However, most of the literature examining P2P electricity market design assumes participants can accurately predict their supply and demand for energy [12]- [17]. In reality this is unlikely to be the case [18], [19]. ...
Peer-to-peer electricity markets allow small producers and consumers of energy to trade directly. Energy imbalances, the difference between predicted and actual supply or demand for energy, may be higher in peer-to-peer markets than in traditional markets. High energy imbalances could increase the total cost of the electricity system, both inside and outside the peer-to-peer market, because the system operator must take expensive corrective actions at short notice. This paper examines the effect of imbalance charges on peer-to-peer electricity markets. A new symmetric imbalance charge mechanism is proposed which penalises market participants irrespective of the direction of their energy imbalance. The symmetric imbalance charge mechanism provides a financial incentive for peer-to-peer market participants to reduce their energy imbalances. For illustrative purposes, this paper uses a simulation to show that the current imbalance charge mechanism in Great Britain does not provide a financial incentive for peer-to-peer market participants to reduce their energy imbalances. The imbalance charge is close to zero under the current British imbalance charge mechanism when averaged over hundreds of settlement periods or more. When subject to the symmetric imbalance charge mechanism, the simulation shows that peer-to-peer market participants are given a strong financial incentive to reduce their energy imbalances. Finally, this paper discussed how the symmetric imbalance charge mechanism could be implemented only within the bounds of a peer-to-peer market, or within the whole electricity system.
... In [6], the authors propose a dynamic price scheme to minimize average system cost and rebound peaks through load scheduling with individualized prices for each user and evaluate results considering the integration of renewable energy sources. Reference [7] proposes a dayahead dynamic pricing method to maximize economic, social welfare of both distribution system operators and prosumers considering network constraints. Results are tested in a radial test feeder with photovoltaic (PV) generators and batteries, scheduling flexible loads. ...
This paper proposes a novel dynamic pricing scheme for demand response with individualized tariffs by consumption profile, aiming to benefit both customers and utility. The proposed method is based on the genetic algorithm, and a novel operator called mutagenic agent is proposed to improve algorithm performance. The demand response model is set by using price elasticity theory, and simulations are conducted based on elasticity, demand, and photovoltaic generation data from Brazil. Results are evaluated considering the integration effects of renewable energy sources and compared with other two pricing strategies currently adopted by Brazilian utilities: flat tariff and time-of-use tariff. Simulation results show the proposed dynamic tariff brings benefits to both utilities and consumers. It reduces the peak load and average cost of electricity and increases utility profit and load factor without the undesirable rebound effect.
... In this sense, the tariff systems must be as simple as possible to guarantee that each actor can understand the aim of the methodology and respond to the tariff system in a harmonic manner. Thus, simplicity is a very important feature in tariff systems, as seen in current practices [2,3]. ...
... These tariff systems are generally called volumetric [8], as the cost of energy and network are represented in one single charge. As a volumetric tariff is the simplest way electricity can be priced, it is widely used in practice [2,3]. ...
... In one hand, various approaches have represented cost recovery and efficiency systematically, but with complex mathematical formulations that complicates regulatory implementations. On the other hand, various actual implementations maintain a level of simplicity that allows its regulatory applicability [2,3]; however, most of these approaches are based in volumetric tariffs that overlook cost recovery and efficiency in the presence of DG. Thus, this work proposes a tariff system considering the trade-off between mathematical complexity and regulatory applicability. ...
In a scenario where distributed generation infrastructure is increasing, the impact of that integration on electricity tariffs has captured particular attention. As the distribution sector is mainly regulated, tariff systems are defined by the authority. Then, tariffs must be simple, so the methodology, criteria, and procedures can be made public to ensure transparency and responsiveness of the customers to price signals. In the aim of simplicity, tariff systems in current practices mostly consist of volumetric charges. Hence, the reduction of the energy purchased from the distribution network jeopardizes the ability of the tariff system to ensure recovery of the total regulated costs. Although various works have captured this concern, most proposals present significant mathematical complexity, contrasting with the simplicity of current practices and limiting its regulatory applicability. This work develops a tariff system that captures the basic elements of distribution systems, trying to maintain the simplicity of current practices, ensuring recovery of the total regulated cost under the penetration of distributed generation, and incentivizing through price signals operational efficiency. A simulation will be presented to discuss numerical results.
