Pricing flexibility of shiftable demand in electricity markets

Werner, Lucien; Wierman, Adam; Low, Steven H.

doi:10.1145/3447555.3464847

Cited by 12 publications

(7 citation statements)

References 27 publications

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“…However, it is argued that the current market design lacks adequate incentives for flexible loads. In [55], a new multi‐interval market design is proposed which corrects the demand‐side incentive incompatibility.…”

Section: Pricing With Multi‐interval Dispatchmentioning

confidence: 99%

Extensions of the locational marginal price theory in evolving power systems: A review

Tan

Cheng

Liu

et al. 2022

IET Generation Trans & Dist

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The locational marginal price (LMP) theory is the foundation of nowadays electricity markets. With the rapid growth of intermittent renewable generation, new features are emerging in power systems, such as the uncertainty of power supply, the scarcity of flexibility, and the increase of distributed generation. In this situation, the electricity pricing scheme needs to be augmented with new features to meet requirements of incentive compatibility, cost causation-awareness, revenue adequacy, and transparency in a new market environment. Though a broad spectrum of literature has investigated extensions of the LMP addressing different challenges, a panorama of these extension directions is absent. To this end, this paper provides a systematic review of existing LMP extension research from four aspects, including pricing with non-convexity, pricing with multiple intervals, pricing with uncertainty, and pricing in distribution systems. These extension directions are derived from the impacts of the power system evolution on dispatch and pricing models. For each extension direction, the motivation and basic problem setup are introduced, followed by a critical survey of related research progress. Future directions and research gaps of the LMP extension are also indicated in this paper.

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Section: Pricing With Multi‐interval Dispatchmentioning

confidence: 99%

Extensions of the locational marginal price theory in evolving power systems: A review

Tan

Cheng

Liu

et al. 2022

IET Generation Trans & Dist

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show abstract

“…Other papers investigated the load rebound effect by solving the market with 24-hour lookahead, but with a fixed price assumption making it difficult to fully maximise the market surplus [13]. The recent work of Werner et al considers the timecoupling nature of load shifting in all periods [46]. However, the prosumers' price-responsiveness was ignored, while the overall comfort was maintained by meeting the expected demand at all times.…”

Section: Related Workmentioning

confidence: 99%

“…Pricing structure within a local market has mostly centered around two main schemes: a two-price market for purchase and sale of electricity [3,26], or one consensus price for both buyers and sellers [19,46]. While the former group resembles the current retail structure, where there are separate tariffs for buying and selling energy [24], the latter pricing scheme loosely represents 'wholesale prices' such that buying prices are equal to selling prices [31,32].…”

Section: Related Workmentioning

confidence: 99%

Optimal sizing and scheduling of community battery storage within a local market

Dinh

Pourmousavi

Karimi-Arpanahi

et al. 2022

Proceedings of the Thirteenth ACM International Conference on Future Energy Systems

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The ever-increasing uptake of distributed energy resources necessitates the introduction of local electricity markets at the residential level. Electric retailers, who are adversely affected by these changes, can make a profit by operating local trading platforms and offering services through community-level battery storage. In this work, we propose a Stackelberg game-based approach for sizing the centralized battery unit under the operation of a multi-interval local market. The optimization is formulated as a bilevel program, where the leader is the market aggregator responsible for determining the local prices and battery charging/discharging schedules. Also, the followers in the bilevel program are prosumers, who can vary electricity consumption with respect to their comfort and cost of electricity. Upon obtaining the optimal capacity of the community storage, we modify the algorithm to efficiently operate the battery on a daily basis. The applicability of the proposed model is evaluated using real-world data of residential prosumers with rooftop photovoltaic systems for two different pricing schemes, which represents the profit trade-off between the aggregator and prosumers. The results show the profitability of the proposed model for community storage installation, where a relatively short payback period can be achieved via either pricing scheme.

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“…In particular, using smart meter data to understand household level energy use is an ongoing challenge, and with it comes the difficulties in developing meaningful interventions that can ease burdens on the grid while maintaining customer engagement and satisfaction [12]. For example, one such motivation for household-level energy interventions is to reduce greenhouse gas emissions from nonrenewable generation sources (e.g., natural gas "peaker" power plants) during periods of high demand, while also expanding the potential for customers to change their energy behaviors and appliance purchases to save money on their energy bills [13].…”

Section: Introductionmentioning

confidence: 99%

Constructing dynamic residential energy lifestyles using Latent Dirichlet Allocation

Chen,

Zanocco,

Flora

et al. 2022

Preprint

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The rapid expansion of Advanced Meter Infrastructure (AMI) has dramatically altered the energy information landscape. However, our ability to use this information to generate actionable insights about residential electricity demand remains limited. In this research, we propose and test a new framework for understanding residential electricity demand by using a dynamic energy lifestyles approach that is iterative and highly extensible. To obtain energy lifestyles, we develop a novel approach that applies Latent Dirichlet Allocation (LDA), a method commonly used for inferring the latent topical structure of text data, to extract a series of latent household energy attributes. By doing so, we provide a new perspective on household electricity consumption where each household is characterized by a mixture of energy attributes that form the building blocks for identifying a sparse collection of energy lifestyles. We examine this approach by running experiments on one year of hourly smart meter data from 60,000 households and we extract six energy attributes that describe general daily use patterns. We then use clustering techniques to derive six distinct energy lifestyle profiles from energy attribute proportions. Our lifestyle approach is also flexible to varying time interval lengths, and we test our lifestyle approach seasonally (Autumn, Winter, Spring, and Summer) to track energy lifestyle dynamics within and across households and find that around 73% of households manifest multiple lifestyles across a year. These energy lifestyles are then compared to different energy use characteristics, and we discuss their practical applications for demand response program design and lifestyle change analysis.

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Pricing flexibility of shiftable demand in electricity markets

Cited by 12 publications

References 27 publications

Extensions of the locational marginal price theory in evolving power systems: A review

Extensions of the locational marginal price theory in evolving power systems: A review

Optimal sizing and scheduling of community battery storage within a local market

Constructing dynamic residential energy lifestyles using Latent Dirichlet Allocation

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