Network-Aware Demand-Side Management Framework With A Community Energy Storage System Considering Voltage Constraints

Mediwaththe, Chathurika P.; Blackhall, Lachlan

doi:10.1109/tpwrs.2020.3015218

Cited by 30 publications

(10 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A. Demand-side model Similar to our previous work in [13], an ETS model consists of a set of energy users A, a CES system, and a system aggregator. We assume a third-party owns the CES system, and we refer to this owner as the CES provider.…”

Section: Energy Trading System Models and Configurationsmentioning

confidence: 99%

“…Hence, both y n (t) and l n (t) may have non-zero values. The ETS model is similar to the model in [13], however, in this paper, we consider a centralised optimisation approach to determine l n (t) whereas, in [13], the system utilises a distributed approach based on game theory. By considering the amount of energy deficit at user n ∈ P at time t, the values of l n (t) are calculated such that…”

Section: Different Energy Trading System Configurationsmentioning

confidence: 99%

“…If the set P comprises either only deficit users or surplus users, we take l * n (t) = E * P (t) en(t) P en(t) once E * P (t) is found by solving (13). If both types of users exist in P, then we set l * n (t) = 0.…”

Section: Optimization Frameworkmentioning

confidence: 99%

See 2 more Smart Citations

Community Energy Storage-based Energy Trading Management for Cost Benefits and Network Support

Mediwaththe¹,

Blackhall²

2020

Preprint

Self Cite

View full text Add to dashboard Cite

In this paper, the extent to which the integration of rooftop photovoltaic (PV) power with a community energy storage (CES) system can reduce energy cost and distribution network (DN) loss is explored. To this end, three energy trading systems (ETSs) are compared; first, an ETS where PV users exchange energy with the CES system in addition to the grid, second, an ETS where PV users merely exchange energy with the CES system, and third, an ETS where PV users only exchange energy with the grid. A multi-objective optimization framework, combined with a linear distribution network power flow model, is developed to study the trade-off between the energy cost and network power loss reductions while satisfying the DN voltage and current flow limits. Simulations, with real energy demand and PV power data, highlight that enabling the energy exchange between the users and the CES system can give a better trade-off between the DN power loss and energy cost reductions. Further, simulations demonstrate that all three ETSs deliver nearly 85% DN energy loss reduction with significantly increased revenues compared to an ETS without a CES system.

show abstract

Section: Energy Trading System Models and Configurationsmentioning

confidence: 99%

Section: Different Energy Trading System Configurationsmentioning

confidence: 99%

See 1 more Smart Citation

Community Energy Storage-based Energy Trading Management for Cost Benefits and Network Support

Mediwaththe¹,

Blackhall²

2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…One identified limitation of the current literature on community market is that the grid constraints are oftentimes neglected [8], or embedded with oversimplified models [11], [13]. Nonetheless, a high penetration of DERs (e.g., PV) in LV grid could lead to many technical issues, especially overvoltage problems [13]- [15].…”

Section: Introductionmentioning

confidence: 99%

A Three-Stage Strategy With Settlement for an Energy Community Management Under Grid Constraints

Putratama

Rigo‐Mariani

Mustika

et al. 2023

IEEE Trans. Smart Grid

View full text Add to dashboard Cite

This paper focuses on a local energy market where a group of households in a low voltage (LV) grid is organized as an energy community. A three-stage management strategy is proposed under the French collective self-consumption framework. In the first day-ahead stage, households coordinate with the community manager to minimize the overall energy bills for the next day. Then, real-time operation (second stage) focuses on the mitigation of forecast uncertainties and voltage violation, by utilizing the reserve of the local production/storage assets. Finally, the third stage contractually allocates the community energy among the households on 30 min basis (based on the French regulation), in order to ensure fair individual cost reduction and possibly create economic surplus in the community. The proposed community management strategy is evaluated on a LV grid with 55 households, and the results show the proposed strategy achieve an average of 30 % individual cost reduction among the users compared to the base scenarios. Furthermore, different pricing scenarios are compared through sensitivity studies and scalability tests are run on larger systems.

show abstract

“…Existing studies of NSBs have focused on the development of algorithms that optimise NSB operations for techno-economic objectives, such as maximising owner pro ts 15 , minimising customers collective costs 16,17 , managing voltage 18 , and maximising decarbonisation 19,20 . These studies typically disregard potential limitations on access to consumer data and presuppose clear -and in our view narrowly de ned -customer desires.…”

mentioning

confidence: 99%

An interdisciplinary exploration of responsible algorithm design in the era of distributed energy resources

Ransan-Cooper¹,

Sturmberg

Shaw

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

While the governance of algorithms is of growing societal concern, the energy sector has been slow to engage with this issue. We argue that there are at least three systemic concerns to the design and operation of algorithms in the new, digital energy era. Namely, reliance on algorithms can bias considerations towards the easily quantifiable, that they can inhibit explainability, transparency and trust, and that they could undermine energy users’ autonomy and control. We examine these tensions through an interdisciplinary study that reveals the diversity and materiality of algorithms. Our study focuses on neighbourhood-scale batteries (NSBs) in Australia as a case study of new energy algorithms. We conducted qualitative research with energy sector professionals and citizens to understand the range of perceived benefits and risks of NSBs and the algorithms that drive their behaviour. Issues raised by stakeholders were integrated into our development of multiple NSB optimisation algorithms, whose impacts on NSB owners and customers we quantified through techno-economic modelling. Our results show the allocation of benefits and risks vary considerably between different algorithm designs. This insight a need to improve energy algorithm governance, enabling accountability and responsiveness across the design and use of algorithms so that the digitisation of energy technology does not lead to adverse public outcomes. Taken together, our study underscores the importance for researchers and developers of new algorithms to take a holistic view of stakeholders and public benefit, and demonstrates one method to practice responsible algorithm design.

show abstract

Network-Aware Demand-Side Management Framework With A Community Energy Storage System Considering Voltage Constraints

Cited by 30 publications

References 26 publications

Community Energy Storage-based Energy Trading Management for Cost Benefits and Network Support

Community Energy Storage-based Energy Trading Management for Cost Benefits and Network Support

A Three-Stage Strategy With Settlement for an Energy Community Management Under Grid Constraints

An interdisciplinary exploration of responsible algorithm design in the era of distributed energy resources

Contact Info

Product

Resources

About