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Tracing Local Energy Markets: A Literature Review

  • MK Consulting - Vattenfall Trading GmbH - Karlsruhe Institute of Technology

Abstract and Figures

We conduct a structured literature review on the concept of local electricity markets (LEMs). Local energy markets have gained increasing attention in the last two decades. Yet, a holistic, common definition and clear demarcation of LEMs to microgrid electricity markets and peer-to-peer trading is still missing in research literature. The literature review shows current works to shift their focus from conceptual implementation and design approaches to increasingly realistic and practical applications of electricity trading. Recent work puts more emphasis on the community approach of electricity trading of prosumers and consumers. Current research gaps of the inclusion of network constraints, integrated energy systems, agent-centric LEM designs, and a holistic comparison of market mechanisms are identified by the literature review.
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Tracing Local Energy Markets: A Literature Review
1st Esther Mengelkamp, 2nd Julius Diesing, 3rd Christof Weinhardt
Karlsruhe Institute of Technology, Karlsruhe, Germany
AbstractWe conduct a structured literature review on
the concept of local electricity markets (LEMs). Local
energy markets have gained increasing attention in the
last two decades. Yet, a holistic, common definition and
clear demarcation of LEMs to microgrid electricity mar-
kets and peer-to-peer trading is still missing in research
literature. The literature review shows current works to
shift their focus from conceptual implementation and
design approaches to increasingly realistic and practical
applications of electricity trading. Recent work puts more
emphasis on the community approach of electricity trading
of prosumers and consumers. Current research gaps of
the inclusion of network constraints, integrated energy
systems, agent-centric LEM designs, and a holistic compar-
ison of market mechanisms are identified by the literature
Index Terms—Local energy market, review, microgrid energy
market, peer-to-peer trading, energy sharing, energy community.
With the increasing share of renewable and thus (mostly)
volatile distributed generation worldwide, small-scale energy
producers, prosumers and energy-affine consumers become
more and more involved in the overall energy system [1].
These small-scale actors were formerly excluded from the
energy market, as legislative restrictions about generation size
and legal stipulations prohibited them from actively taking part
in the bidding process. Local electricity markets (LEMs) solve
this issue by providing a local market platform to residential
actors within a community [2], [3]. They empower small-
scale electricity producers, prosumers, and consumers and
offer economic, ecologic and social incentives for creating
local electricity balances [4]. Yet, definitions of LEMs, their
concepts and market mechanisms are mostly case-driven in-
stead of holistic. To organize the existing LEM research, we
conduct a structured literature review of high-quality academic
research according to [5]. The objective of our work is to
provide an overview of existing research streams and trends.
Furthermore, we develop categories based on our findings, that
structure the existing literature to better observe the current
research objectives and research gaps.
Based on a thorough structured literature review from
January 2000 to September 2018, we answer the following
research question: In the emerging field of local electricity
markets, (i) what is the status of current scientific research
and how did it develop, (ii) where are knowledge gaps in this
The paper is structured as follows: Section II explains the
used methodology. Then, Section III presents the literature
review and its main results. Section IV shortly discusses
the results and brings forth future research questions, before
Section V concludes the paper.
We use the renowned approach to a structured literature
review from [5]. After identifying the main contributions in
leading journals, a backward and forward search is conducted
on the citations and recitations of those contributions. The
review only includes studies that directly consider LEMs
and/or trading with a certain sense of locality in the market
mechanism. The literature review covers the time of Jan 2000–
Sept 2018. The turn of the millennium also marks the start of
scientific LEM research [6]. The used keywords center around
the search terms of “local energy/electricity market”, energy
trading”, “energy sharing”, “peer-to-peer” and “community
energy”. The keyword search was conducted by connecting
all search terms with the non-exclusive ‘OR’ operator on
the scientific search engine Google Scholar. All variations of
writing were used directly, or expressed by shortcuts, e. g. ‘*’.
We specifically exclude publications that only deal with
the optimization of power flows or centralized optimization
of energy efficiency management in smart grids. These topics
lack the idea of locality and a market mechanism between
individual agents that LEMs focus on. To further increase the
quality of the review, we only consider publications in journal
or conference outlets with a high scientific journal ranking.
Operationally, this restricts the considered outlets to journals
of an h-index of 50 and conferences with a h index of 10.1
We use the rankings of the Scimago Institutions Ranking2from
November 2018.
Based on solely the keyword and backwards/forward
searches, 73 high-impact journal entries and conference pro-
ceeding papers have been identified as being part of the
relevant LEM literature. By considering the title, abstract,
introduction and conclusion of the found papers, we narrowed
the list down to 46 academic papers. A conclusive list and
categorization of the considered papers is provided in Table I.
The process of choosing the finally analyzed 46 papers was
conducted as follows: First, all relevant papers need to cover
1The h-index measures the outlet’s number of articles (h) that have received
at least hcitations. It thus represents a scientific impact number.
2The Scimago Institutions Rankings can be found here: https://www. Accessed on 04.12.18.
Fig. 1. Development of high-impact publications.
a certain degree of locality as this work is tracing develop-
ments in local electricity markets. Second, all selected articles
describe a market or trading mechanism that defines how
electricity is traded. Therefore, articles that only deal with the
optimization of power flows or the maximization of energy
efficiency in smart grids are excluded from the detailed anal-
ysis. In the process of identifying the most relevant articles,
eleven have been excluded because of a missing electricity
trading mechanism, four because of a missing locality and
twelve articles have been excluded as a result of low h-index.
In the end, 34 journal entries and 12 conference proceedings
were derived for the detailed analysis. Figure 1 provides an
overview of when the journal and conference papers were
published. The publication trend is exponentially increasing
over the time of the literature review, with very few papers
being published before 2011 and quite a lot since then.
A detailed analysis of the 46 identified relevant articles is
shown in Table I. The papers have been evaluated regarding:
1) Concept: LEMs versus Microgrid Electricity Markets
(MEM), who focus more on the physical grid constraints
within a microgrid, but still consider enough local trad-
ing to be related to LEMs, and Peer-to-Peer Electricity
Trading (P2P), which focuses on direct trading between
agents (local or non-local).
2) Methodology of the Paper: Methodology is divided
into Case Studies (CS), Literature Reviews (LR), Opti-
mization (O), Simulation (S), Regulatory Considerations
(R), Game Theory (GT) and Theoretical concepts (Th).
3) Trading Design: Defines if electricity is conducted
via an Aggregator (Ag) trading for several end users,
Auction Mechanism (Au), a Direct Trading Mechanism
(DT) between agents, a Flexibility Market Mechanism
(FM), Inter-Market/Microgrid Trading (IM), Traditional
Electricity Market Design (EM) that is adapted to a
local market context, or a Real-Time Pricing Mechanism
4) Agent Design: Defines whether Zero Intelligent Agents
(ZIA) or Intelligent Agents (IA) with a learning strategy
are used.
5) Transactional Object: Defines the transactional object:
Electricity (El), Energy (En), Flexibility (F), Heat (H)
or Reserve Energy (RE). When energy is traded, but
the paper makes it clear that electricity is meant, it is
specified by En (El).
6) Participants: Defines the main participating LEM stake-
holders: Aggregators (A), Consumers (C), Distribution
Companies (DCo), Energy Utilities (EU), Local Gov-
ernance (G), Microgrid agents (M), Market Operators
(MO), Local Producers (P), Prosumers (Ps), Storage
Devices (SD) and System Operators (SO).
Beginning in the early 2000s, [7] publish the first relevant
LEM paper. It argues that the then present liberalization
of the electricity sector would end up in LEMs. [8] use
LEMs to model the integration of electricity production from
fluctuating renewable energy resources into the existing energy
market. [9] discusses the need for LEMs in Denmark. Since
all these early publications deal with the idea of integrating
local markets into the electricity sector or design options for
those, they are assigned to the LEM concept. Whereas [10]
contributes by finding a way to integrate local renewable
energy production in microgrids with the use of price signals
for influencing the behaviour of distributed resources, [11]
are the first to actually design a local market which makes
it possible for consumers and local producers to directly trade
power and heat. They implement an allocation mechanism
based on a double auction and use an open order book call
market to let the end users negotiate the energy demand and
supply. Thus, they are a basis for a lot of subsequent work.
[12] are the first authors to investigate the behaviour of market
participants in a local market environment by using an agent-
based simulation. They simulate multiple broker agents that
are learning their strategies based on market conditions.
a) Electricity Trading Design Approaches: [13] add to
the previous research by introducing a new auction model for
a local reserve energy market designed to accommodate the
special needs of non-expert bidders such as private households.
[14] extend this approach in designing a new market for
flexibility with two planning and scheduling mechanisms.
The first is an ahead-planning market, where flexibility of
prosumers is accumulated taking into account load profiles.
The second is a real-time dispatching market in that the system
operator first tenders voluntary generation profile management
through price signals and if needed decides on a compulsory
generation profile management. [15] choose an aggregator
for trading flexible energy usage and flexibility services. In
order to execute those trades, [16] design a market platform
for flexibility, where electricity consumers’ and prosumers’
offers for flexibility are collected by a smart service provider
platform and purchased by the service provider if needed. It
is similar to the market designed by [14].
[17] give an overview of inter-microgrid electricity trading
(IM). They introduce game theoretic methods for addressing
challenges posed in the smart grid. [18] have a more detailed
approach IM trading, as they introduce an optimization prob-
lem for microgrids operating in an islanding mode. First, they
conduct a centralized optimization by a market controller and
then find an iterative solution by solving the local subproblems
within the microgrids that converges to the centralized opti-
mization. Furthermore, [19] analyze how the trading possibili-
ties between microgrids can increase the participants’ welfare.
[20] extend the microgrid trading approach by an agent-based
simulation with intelligent agents to model electricity buyers
and sellers on the LEM.
Several authors, including [21], [22] and [23] use the NO-
BEL market model, a project supported by the European Com-
mission, to simulate and test agent behavior in a continuous
double auction. [24] discuss different design options for local
electricity markets and conclude, that a continuous double-
sided auction with private information suits the best for their
proposed market. [25] take a similar approach in comparing
two market designs in a local electricity market. The first is
a P2P market that focuses on trades between randomly paired
consumers and prosumers based on pay-as-bid transactions.
The second is an order book market with a double auction
determining a uniform price calculated by a central comput-
ing entity. Compared to the earlier local electricity market
research, [26] put more emphasis on the direct trading within
a close geographic area between neighbors. [3] set their focus
on prosumers becoming active participants in the local market
and the smart grid. [1] propose direct trading via a local energy
exchange with a real-time pricing mechanism. They state that
an advantage of LEMs is allowing local funds to stay within
the community. Other authors including [27] also underline the
rise of local acceptance of energy projects in the community as
advantages of LEMs. In order to analyze economic benefits a
local trading mechanism brings to communities, [28] design a
trading framework within neighborhoods considering actively
participating users as well as community storage devices to
simulate realistic test cases.
b) P2P Electricity Trading: This review’s first P2P con-
cept is presented by [29]. In an extending work, [30] simulate
electricity sharing between consumers and prosumers using
game theory and analyze the results through case studies
In the P2P concept many authors review existing projects
and trading options [31]. [32] describe and compare global
projects.Moreover, they clearly define the distinction of the
P2P concept from the LEM and the MEM concept, as they
point out that ”Many of these trails designed business models
and marketplace for P2P energy trading, but ignored the
possibility of local energy markets in Microgrids (. . . ).” ( [32]
S. 2568). [33] assess the feasibility of P2P electricity trading
and introduce a three-level P2P electricity trading structure for
inter- and intra-Microgrid trading. In a successive work, [34]
develop a P2P real-time pricing mechanism which ensures that
all prosumers and consumers within a community are better
off participating in the P2P sharing due to a compensatory
price. A key finding of [35] is that P2P electricity sharing has
the potential to substantially reduce electricity costs and raise
a communitys self sufficiency.
[36] propose a general evaluation framework for comparing
the performance of P2P electricity sharing models. They
evaluate the electricity sharing model of [37], who design a
supply and demand ratio mechanism for electricity sharing
between prosumers in a microgrid instead of feeding into the
utility grid. It comprises a real-time pricing mechanism that
sets incentives to shift loads for overall electricity cost savings.
[36] conclude that the supply and demand ratio mechanism has
a high performance because the dynamic pricing mechanism
induces electricity sharing and demand response. [38] propose
a consortium blockchain based electricity trading system that
uses an auction mechanism for charging and discharging
electric vehicles. The blockchain technology secures privacy
protection without the need of a trusted third party, whereas
the auction mechanism is implemented to maximize social
welfare. [39] discuss the use of blockchain technology for P2P
trading in a microgrid market.
Another important issue regarding electricity trading on a
local level is the regulation and legal framework. Whereas [40]
deal with the regulation of flexibility management options at
a local level, few publications have been made regarding the
regulation of pricing mechanisms and possible peer-to-peer
trading mechanisms at a local level. Regulatory scenarios need
to be further investigated.
Firstly, we identify a need to consolidate the existing defini-
tions of LEMs. The wide spread and differing understandings
of LEMs frequently allow confusion with the similar termi-
nologies of microgrids, P2P trading, energy sharing and energy
communities. While we only observe the literature, we suggest
that the consolidated definition should focus on residential
local electricity trading, which is not specified to take place
in direct P2P transactions, but would most often use auction
mechanisms. Further, a LEM should be a virtual market place,
independent from the actual physical implementation, e. g.
from a microgrid or public grid. Ideally, grid constraints would
be included in the LEM. However, a solely virtual LEM should
also be possible. Secondly, a comprehensive comparison of the
impacts of different trading designs (especially market mech-
anisms) should be carried out. Thirdly, the focus on network
constraints and congestion management is widely mentioned,
but not investigated in-depth. It should be extended in the
future. Fourthly, the end customer focus of LEMs is pointed
out by several authors. Yet, a direct end customer focus, or a
specific analysis of end customer motivations, objectives and
strategies in LEMs is missing. Especially social satisfaction
of the LEM participants [34], economic profitability for the
different stakeholders [15], price elasticity [4], cost fairness
and the social engagement in LEMs [31] are derived as current
research gaps. Fifthly, sustainable business models for LEM
stakeholders need to be developed. Sixthly, research on LEMs
is majorly centering on electricity trading. Sector coupling and
integrated energy systems (e. g. heat and electricity) or other
forms of energy should be intensively considered in future
work. Moreover, regulatory frameworks and legal conditions
should be considered.
Author (Year) Concept Methodology Trading Design Agents Transactional Object Participants
[41] LEM R, Th El, H C, DCo, EU, G
[8] LEM S EM El, H C, P, SD
[9] LEM R EM El C, DCo, EU, G
[11] MEM LR, O Au El, H C, P, MO
[12] LEM S DT, RTP IA El C, P, MO, SO
[18] MEM O IM En (El) M, MO
[17] MEM GT,LR IM El C, P, EU
[21] LEM S Au, 15 min El C, P, Ps
[42] LEM O, GT Ag, DT El A, C, EU
[43], [44] MEM CS, O, S Au, RTP / 30 min El C, P, SD
[20] MEM CS, S Au, IM / 15 min IA El C, M, P, SD, SO
[13] LEM S Au / 1h IA RE, F Ps, SO
[22] MEM CS, O Au El MO, Ps
[26] LEM CS, S DT, IA El C, EU, Ps, SD
[24] LEM CS, S Au / 15 min ZIA El, RE C, MO, Ps
[45] LEM LR En (El) C, M, P, SD
[19] MEM O, S IM / 1h El M
[23] LEM CS, S Au, DT / 15 min ZIA El C, P, Ps
[46] MEM R Au RE EU, Ps, SO
[47] MEM LR, R El G
[1] MEM LR DT, RTP El, RE, F A, EU, Ps, SO
[48] MEM LR El A, C, MO, P, SO
[27] LEM LR El C, DCo, MO, P
[14] LEM O, Th Ag, FM, RTP F A, MO, Ps, SO
[29], [30] P2P CS, S, GT Au, DT / 30 min El MO, P, Ps, SO
[40], [49] LEM LR, R Ag, FM F A, C, DCo, P, SO
[3] LEM CS, O Au, DT / 15 min En (El) A, C, EU, P, SO
[25] LEM S Au, DT / 15 min IA, ZIA El C, PS
[38] P2P CS, O Ag, Au El A, Ps, SD
[37] P2P CS, O DT, RTP El Ps, SO
[31] P2P CS, LR El C, P, Ps
[32] P2P LR En (El) C, MO, P, Ps, SO
[36] P2P CS, O, S DT, RTP / 1h IA El C, MO, Ps
[33]–[35] P2P CS, O DT, IM, RTP El, RE C, P
[50] MEM O DT, IM El C, M, P, SO
[39] MEM CS, LR Au / 15 min El C, Ps
[15], [16] LEM CS, O, S Ag, FM F A, C, P, Ps, SO
[28] LEM O, S, GT 30 min El MO, Ps, SD
[4] MEM CS, O, S Au / 1h ZIA El A, C, P, Ps
We conduct a structured literature review on high-impact
LEM trading research publications. Research on LEMs is
exponentially increasing since the beginning of the 2000s. Yet,
most research is case study centered, whereas a holistic under-
standing of LEMs is just recently evolving to be considered in
a structured way. We identify six main research gaps with the
help of the structured literature review. This work is to be seen
as a summary and interpretation of existing LEM research.
Building upon the existing research and filling the derived
research gaps will help LEM research to thrive in the future
in a more concentrated way.
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... Local energy markets (LEMs) were introduced in the last few decades as a result of the challenges arising from increasing distributed renewable energy resources and to enable small-scale producers, prosumers, and consumers to become involved in the electricity market [1]. LEM has also achieved quite a loud interest in countries such as Germany where there is high support for renewable energy integration because of the ability of LEM to support local renewable energy integration and create more savings for distributed energy resources owners [2]. ...
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Local energy markets (LEMs) provide opportunity to handle the challenges arising from the lower grid level while using the traditional top-down approach to manage distributed generated renewable energy resources. Blockchain based local energy markets (LEMs) have been introduced in recent years as a way to enable local consumers/prosumers to trade their energy locally in a distributed and highly secured manner in an LEM. However, there are still some challenges regarding the main factors that can drive local consumers/prosumers to participate in a blockchain based LEM, optimal community size and prosumer to consumer ratio for an efficient LEM. Also, there is still no information on how the quantifying factors for participation on a blockchain based LEM can affect the performance of an LEM. This paper presents a survey and simulation based analysis of quantifying factors for participation in a blockchain based LEM. The survey was distributed among local consumers/prosumers and a total of 261 responses were received from the responders. The results from the responders were analyzed using a Python code based statistical analysis model. The simulation based analysis was conducted using a community based LEM model and evaluated using data received from a combination of German household profiles and standard load profiles. The survey results showed that the major drive for local consumers/prosumers to participate on blockchain based LEM is their willingness to support renewable energy integration, transparency and trust offered by a blockchain network. On the other hand, the simulation based analysis showed that small and medium communities with prosumers to consumer ratios between 0.3 to 0.5 create more economic and technical benefits for local consumers/prosumers compared to large communities. The community based simulation results were modelled together with the survey results to determine how the individual quantifying factors for participating in a blockchain based LEM can affect the performance of an LEM.
With the development of decentralized sources of electricity generation, different ways of organizing electricity exchanges at the local level have been developed. The literature has studied extensively over the past decade how local exchanges can take place. This has resulted in different concepts reflecting different perimeters of study. However, the perimeters of these different concepts are not always well defined in the literature, which can lead to some con- fusion about the organization of the local market under study. There is a lack of harmonization because different terms may be used for the same concept or the same term may be used for several concepts. This paper aims to propose a harmonization of the different concepts for the study of local markets including local energy markets, peer-to-peer trading, local flexibility markets, microgrids, energy communities and transactive energy. These concepts are com- pared by identifying the characteristics of each. For this purpose, a literature review was per- formed in order to understand the context in which these concepts emerged and to identify their specific characteristics. Moreover, this paper proposes to analyze the economic challenges of local exchanges by identifying the economic incentives and solutions developed to make business models viable.
The development of distributed energy sources will challenge the management of the electrical system. Local flexibility markets (LFMs) are a promising solution to coordinate the dispatch of distributed energy sources. The LFM development is in its infancy, and numerous challenges should be addressed. This study focuses on four topics for LFM success: the governance model, coordination issues, inc-dec gaming, and competition. Based on a review of current projects, we identify challenges related to the four topics and discuss solutions to overcome these challenges. The proposed solutions are crucial to achieving market efficiency and cannot be considered independently.
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Triggered by the increased fluctuations of renewable energy sources, the European Commission stated the need for integrated short-term energy markets (e.g., intraday), and recognized the facilitating role that local energy communities could play. In particular, microgrids and energy communities are expected to play a crucial part in guaranteeing the balance between generation and consumption on a local level. Local energy markets empower small players and provide a stepping stone towards fully transactive energy systems. In this paper we evaluate such a fully integrated transactive system by (1) modelling the energy resource management problem of a microgrid under uncertainty considering flexible loads and market participation (solved via two-stage stochastic programming), (2) modelling a wholesale market and a local market, and (3) coupling these elements into an integrated transactive energy simulation. Results under a realistic case study (varying prices and competitiveness of local markets) show the effectiveness of the transactive system resulting in a reduction of up to 75/% of the expected costs when local markets and flexibility are considered. This illustrates how local markets can facilitate the trade of energy, thereby increasing the tolerable penetration of renewable resources and facilitating the energy transition.
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Peer-to-peer (P2P) energy sharing allows the surplus energy from distributed energy resources (DERs) to trade between prosumers in a community Microgrid. P2P energy sharing is being becoming more attractive than the conventional peer-to-grid (P2G) trading. However, intensive sensing and communication infrastructures are required either for information flows in a local market or for building a central control system. Moreover, the existing pricing mechanisms for P2P energy sharing could not ensure all the P2P participants gain economic benefits. This work proposed a two-stage aggregated control to realize P2P energy sharing in community Microgrids, where only the measurement at the point of common coupling (PCC) and one-way communication are required. This method allows individual prosumers to control their DERs via a third party entity, so called energy sharing coordinator (ESC). In the first stage, a constrained non-linear programming (CNLP) optimization with a rolling horizon was used to minimize the energy costs of the community. In the second stage, a rule based control was carried out updating the control set-points according to the real-time measurement. The benefits of P2P energy sharing were assessed from the community’s as well as individual customers’ perspective. The proposed method was applied to residential community Microgrids with photovoltaic (PV) battery systems. It was revealed that P2P energy sharing is able to reduce the energy cost of the community by 30% compared to the conventional P2G energy trading. The modified supply demand ratio based pricing mechanism ensures every individual customer be better off, and can be used as a benchmark for any P2P energy sharing model. For consumers, the electricity bill is reduced by ∼12.4%, and for prosumers, the annual income is increased by ∼£57 per premises.
Conference Paper
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The energy transition from a formerly centralized, fossil-fuel based system towards a sustainable system based on a large share of renewable generation calls for a decentralization and regionalization of the electricity system. Local electricity markets (LEMs), on which prosumers and consumers can trade locally produced electricity, meet these requirements and simultaneously enable formerly excluded residential customers to actively take part in the electricity market. However, trading can be complex and time intensive. Therefore, it should be automated. We provide an analysis of intelligent learning strategies for agents of residential electricity customers in LEMs. To this end, we conduct a multi-agent-based simulation of a LEM with a merit order market design based on the current German electricity spot market. LEM agents maximize their individual utility via reinforcement learning. We expand existing approaches of reinforcement learning with generation and storage states as well as time-dependent learning. The evaluation of the strategies is based on the agents' and community electricity storage's revenues, costs, and consumption of local electricity. The results show that for fixed sell prices, time-dependent reinforcement learning of buy bids is the best strategy. It facilitates a market self-consumption of 54 %. For learning buy and sell prices, traditional reinforcement learning with generation states is the dominant strategy.
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This paper presents a general description of local flexibility markets as a marketbased management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids' hosting capacity.
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P2P energy trading refers to direct energy trading among prosumers and consumers. • A P2P system architecture was developed. • A P2P energy trading platform, Elecbay, was designed. • P2P energy trading was simulated based on game theory. • Results prove that P2P energy trading facilitates local power and energy balance. A B S T R A C T Peer-to-Peer (P2P) energy trading represents direct energy trading between peers, where energy from small-scale Distributed Energy Resources (DERs) in dwellings, offices, factories, etc, is traded among local energy prosumers and consumers. A hierarchical system architecture model was proposed to identify and categorize the key elements and technologies involved in P2P energy trading. A P2P energy trading platform was designed and P2P energy trading was simulated using game theory. Test results in a LV grid-connected Microgrid show that P2P energy trading is able to improve the local balance of energy generation and consumption. Moreover, the increased diversity of generation and load profiles of peers is able to further facilitate the balance.
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The peer to peer (P2P) electricity trading without the need for utilities is expected to increase as the awareness of the shared economy has grown and the microgrid has spread. Furthermore, the development of renewable energy technology and the Internet technology will accelerate the dissemination of the new system. In this light, this study compares the major P2P electricity trading cases being promoted and reviews the potential development and future challenges. Since there have been little case studies of P2P electricity trading published, this study could be used as valuable information for government and corporations that are promoting or pursuing P2P electricity trading business.
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The increasing penetration of distributed energy resources in the distribution grid is producing an ever-heightening interest in the use of the flexibility on offer by said distributed resources as an enhancement for the distribution grid operator. This paper proposes an optimization problem which enables satisfaction of distribution system operator requests on flexibility. This is a decision-making problem for a new aggregator type called Smart Energy Service Provider (SESP) to schedule flexible energy resources. This aggregator operates a local electricity market with high penetration of distributed energy resources. The optimization operation problem of SESP is formulated as an MILP problem and its performance has been tested by means of the simulation of test cases in a local market. The novel problem has also been validated in a microgrid laboratory with emulated loads and generation units. The performed tests produced positive results and proved the effectiveness of the proposed solution.
With the increasing installation of distributed generation at the demand side, an increasing number of consumers become prosumers, and many peer-to-peer (P2P) energy sharing models have been proposed to reduce the energy bill of the prosumers through stimulating energy sharing and demand response. In this paper, a three-stage evaluation methodology is proposed to assess the economic performance of P2P energy sharing models. First of all, joint and individual optimization are established to identify the value contained in the energy sharing region. The overall energy bill of the prosumer population is then estimated through an agent-based modelling with reinforcement learning for each prosumer. Finally, a performance index is defined to quantify the economic performance of P2P energy sharing models. Simulation results verify the effectiveness of the proposed evaluation methodology, and compare three existing P2P energy sharing models in a variety of electricity pricing environments.
The cooperation of multiple networked microgrids (MGs) can alleviate the mismatch problem between distributed generation and demand and reduce the overall cost of the power system. Energy management with direct energy exchange among MGs is a promising approach for improving energy efficiency. However, existing methods on microgrid cooperation usually overlook the underlying distribution network with operating constraints (e.g., voltage tolerance and power flow constraints). Hence the results may not be applicable to actual systems. This paper studies the energy management problem of multiple MGs that are interconnected by both the direct current (DC) energy exchange network and the alternating current (AC) traditional distribution networks. In our problem, each MG is equipped with renewable energy generators as well as distributed storage devices. In order to handle the non-convex power flow constraints, we exploit the recent results of the exact optimal power flow (OPF) relaxation method which can equivalently transform the original non-convex problem into a second-order cone programming problem and efficiently determine the optimal solution successfully. The objective of our problem is to minimize the overall energy cost in a distribution network consisting of multiple MGs, with the practical operating constraints (e.g., power balance and the battery’s operational constraints) explicitly incorporated. Considering the privacy and scalability, we propose a distributed algorithm with convergence assurance based on the alternating direction method of multipliers (ADMM). We also implement our method based on the model predictive control (MPC) approach in order to handle the forecasting errors of the renewable energy generation. Simulations are made for different MG exchange topologies on three radial distribution network testbeds. Numerical results demonstrate that certain topologies are more favorable than others, and the cooperation strategy for the energy exchange is significantly affected by the MGs’ locations in the distribution network.