Micro market based optimisation framework for decentralised management of distributed flexibility assets

Paladin, Andrea; Das, Ridoy; Wang, Yue; Ali, Zunaib; Kötter, Richard; Putrus, Ghanim; Turri, Roberto

doi:10.1016/j.renene.2020.10.003

Cited by 25 publications

(14 citation statements)

References 25 publications

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“…In reference [15], authors proposed a micro energy market for smart domestic energy trading in low voltage distribution systems in the context of high penetration of photovoltaic systems and battery energy storage systems. In addition, a micro-balancing market was proposed to address the congestions due to unforeseen energy imbalance.…”

Section: A Background Studies Of P2p Energy Tradingmentioning

confidence: 99%

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A Novel Scheme for P2P Energy Trading Considering Energy Congestion in Microgrid

et al. 2021

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Section: A Background Studies Of P2p Energy Tradingmentioning

confidence: 99%

“…It can be defined as demand objective. (15) It should be considered that the prosumer with higher energy efficiency should not be disconnected. The energy efficiency of prosumer can be defined as the ratio of D p,n and S p,n .…”

Section: Maximize K Subject To N∈n Smentioning

confidence: 99%

A Novel Scheme for P2P Energy Trading Considering Energy Congestion in Microgrid

et al. 2021

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“…The power of the incompetence of end-users in mitigating energy loss could be one of the most inscrutable phenomena of the modern demand-side management of electricity (DSM), but it certainly has an impact. At this point, the demand for electricity will play a crucial role in upcoming smart grids that aim to link end-users and energy consumption decentralised hybrid renewable electricity systems End-users' access to sustainable energy 132 islands in Philippines (2019) [22] Centralised and decentralised electricity supply options Interconnect renewables to submarine cable hybrid system Europe North Sea Region (2021) [13] Reinforcing grid infrastructure to manage distributed energy storage systems A micro-energy market for smart energy trading with sustainable implementation Great Britain (2020) [23] Decentralised demand-side energy planning, effective real-time demand and forecasting measures Energy plans for assets operating in domestic houses and small communities Table 1. Cont.…”

Section: Introductionmentioning

confidence: 99%

Energy Loss Impact in Electrical Smart Grid Systems in Australia

Zaghwan

Gunawan

2021

Sustainability

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This research draws attention to the potential and contextual influences on energy loss in Australia’s electricity market and smart grid systems. It further examines barriers in the transition toward optimising the benefit opportunities between electricity demand and electricity supply. The main contribution of this study highlights the impact of individual end-users by controlling and automating individual home electricity profiles within the objective function set (AV) of optimum demand ranges. Three stages of analysis were accomplished to achieve this goal. Firstly, we focused on feasibility analysis using ‘weight of evidence’ (WOE) and ‘information value’ (IV) techniques to check sample data segmentation and possible variable reduction. Stage two of sensitivity analysis (SA) used a generalised reduced gradient algorithm (GRG) to detect and compare a nonlinear optimisation issue caused by end-user demand. Stage three of analysis used two methods adopted from the machine learning toolbox, piecewise linear distribution (PLD) and the empirical cumulative distribution function (ECDF), to test the normality of time series data and measure the discrepancy between them. It used PLD and ECDF to derive a nonparametric representation of the overall cumulative distribution function (CDF). These analytical methods were all found to be relevant and provided a clue to the sustainability approach. This study provides insights into the design of sustainable homes, which must go beyond the concept of increasing the capacity of renewable energy. In addition to this, this study examines the interplay between the variance estimation of the problematic levels and the perception of energy loss to introduce a novel realistic model of cost–benefit incentives. This optimisation goal contrasted with uncertainties that remain as to what constitutes the demand impact and individual house effects in diverse clustering patterns in a specific grid system. While ongoing effort is still needed to look for strategic solutions for this class of complex problems, this research shows significant contextual opportunities to manage the complexity of the problem according to the nature of the case, representing dense and significant changes in the situational complexity.

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“…The literature indicates that decentralized load balancing can help integrate (I-RE) production, avoid grid expansion, decrease the need for central balancing systems [5,[14][15][16], and reduce the dependency on fossils [1,12]. Overall, balance can be improved by using four main options: namely, flexible RE production, smart grid technology, curtailment, and storage [3,4,6].…”

Section: Introductionmentioning

confidence: 99%

Local Balancing of the Electricity Grid in a Renewable Municipality; Analyzing the Effectiveness and Cost of Decentralized Load Balancing Looking at Multiple Combinations of Technologies

et al. 2021

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With the integration of Intermitted Renewables Energy (I-RE) electricity production, capacity is shifting from central to decentral. So, the question is if it is also necessary to adjust the current load balancing system from a central to more decentral system. Therefore, an assessment is made on the overall effectiveness and costs of decentralized load balancing, using Flexible Renewable Energy (F-RE) in the shape of biogas, Demand Side Management (DSM), Power Curtailment (PC), and electricity Storage (ST) compared to increased grid capacity (GC). As a case, an average municipality in The Netherlands is supplied by 100% I-RE (wind and solar energy), which is dynamically modeled in the PowerPlan model using multiple scenarios including several combinations of balancing technologies. Results are expressed in yearly production mix, self-consumption, grid strain, Net Load Demand Signal, and added cost. Results indicate that in an optimized scenario, self-consumption of the municipality reaches a level of around 95%, the total hours per year production matches demand to over 90%, and overproduction can be curtailed without substantial losses lowering grid strain. In addition, the combination of balancing technologies also lowers the peak load to 60% of the current peak load in the municipality, thereby freeing up capacity for increased demand (e.g., electric heat pumps, electric cars) or additional I-RE production. The correct combination of F-RE and lowering I-RE production to 60%, ST, and PC are shown to be crucial. However, the direct use of DSM has proven ineffective without a larger flexible demand present in the municipality. In addition, the optimized scenario will require a substantial investment in installations and will increase the energy cost with 75% in the municipality (e.g., from 0.20€ to 0.35€ per kWh) compared to 50% (0.30€ per kWh) for GC. Within this context, solutions are also required on other levels of scale (e.g., on middle or high voltage side or meso and macro level) to ensure security of supply and/or to reduce overall costs.

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Micro market based optimisation framework for decentralised management of distributed flexibility assets

Cited by 25 publications

References 25 publications

A Novel Scheme for P2P Energy Trading Considering Energy Congestion in Microgrid

A Novel Scheme for P2P Energy Trading Considering Energy Congestion in Microgrid

Energy Loss Impact in Electrical Smart Grid Systems in Australia

Local Balancing of the Electricity Grid in a Renewable Municipality; Analyzing the Effectiveness and Cost of Decentralized Load Balancing Looking at Multiple Combinations of Technologies

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