Impact of the Uncertainty of Distributed Renewable Generation on Deregulated Electricity Supply Chain

Yi, Hanling; Hajiesmaili, Mohammad H.; Zhang, Ying; Chen, Minghua; Lin, Xiaojun

doi:10.1109/tsg.2017.2705289

Cited by 29 publications

(5 citation statements)

References 17 publications

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“…The second is on the impact of load uncertainty. This includes modeling the real-time electricity imbalance and the impact of demand uncertainty [23]. It is observed that load uncertainty will affect utilities' cost and the electricity market equilibrium [15], [24], and renewable penetration is likely to deteriorate prediction errors and consequently the cost of utilities [23], [25]- [27].…”

Section: B Related Workmentioning

confidence: 99%

Efficient and Robust Equilibrium Strategies of Utilities in Day-ahead Market with Load Uncertainty

Zhao¹,

Yi²,

Chen³

et al. 2019

Preprint

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We consider the scenario where N utilities strategically bid for electricity in the day-ahead market and balance the mismatch between the committed supply and actual demand in the real-time market. Each utility aims at minimizing its own cost of per-unit electricity by optimizing the bidding strategy, with uncertainty in demand and local renewable generation taken into account. The per-unit electricity cost of a utility is a function of both the day-ahead clearing price and the real-time spot price affected by the market-level supply-demand mismatch. We model the interactions among utilities as a non-cooperative game and study the equilibrium strategies. We show that all utilities bidding according to (net load) prediction is a unique pure strategy Nash Equilibrium with two salient properties. First, it incurs no loss of efficiency; hence, the competition among utilities does not increase the social cost. Second, it is robust and (0, N − 1)-immune. Irrational fault behaviors of any subset of the utilities only help reduce the costs of other rational utilities. We prove the results hold for correlated prediction errors and a general class of real-time spot pricing models, which capture the relationship between the spot price, the day-ahead clearing price, and the marketlevel mismatch. Simulations based on real-world traces corroborate our theoretical results. Our study highlights that the market operator can design real-time pricing schemes according to the sufficient conditions derived in our paper, such that the day-ahead market admits a unique and efficient pure strategy Nash Equilibrium and it is robust to irrational fault behaviors.

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Section: B Related Workmentioning

confidence: 99%

Efficient and Robust Equilibrium Strategies of Utilities in Day-ahead Market with Load Uncertainty

Zhao¹,

Yi²,

Chen³

et al. 2019

Preprint

Self Cite

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“…Therefore, extensive system characterization and impact of Wind Turbine (WT) integration are essential for identifying challenges offered by wind DG units in DS [6]. In [7], the effect of varying load demand and intermittent output power of DGs has been considered vital to assess the impact of DG units on the utility grid. In [8], different technical and environmental parameters have been considered as critical parameters for determining the effect of DG integration in DS.…”

Section: Introductionmentioning

confidence: 99%

A Novel Framework to Determine the Impact of Time Varying Load Models on Wind DG Planning

Ahmed

Khan

et al. 2021

IEEE Access

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Distributed Generation (DG) based on Renewable Energy Sources (RES) are considered as an effective and economical technology for the advancement of an Electric Power System (EPS) to fulfill the load demand. Mostly, studies pertaining to DG planning are performed while considering constant load demand and DG generation. However, these considerations may provide misleading and inconsistent values for loss reduction, voltage profile, power quality, and other operational parameters. Therefore, this paper proposes a novel framework to determine the impact of different Time Varying Voltage Dependent (TVVD) load models on wind DG planning study. Firstly, wind DG optimal allocation is performed using Salp Swarm Algorithm (SSA) for different TVVD load models. Afterwards, impact of different TVVD load models on wind DG planning is investigated. Comparative evaluation of various impact indices, real and reactive power (losses and intakes), penetration level, and apparent power support provided due to integration of wind DG are discussed for various TVVD loads. The analysis of results indicates that TVVD loads have a significant impact on performance of distribution system and DG planning studies. INDEX TERMS Distributed generation, impact indices, salp swarm algorithm, time varying voltage dependent loads.

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“…Accordingly, different trading schemes have emerged to incentivise prosumers to participate in local markets, e.g., peer-to-peer scheme [2] and aggregator scheme [3]. No matter which scheme market participants (MPs) choose, they have to face the uncertainty brought by their DREs [4]. Since generating a perfect forecast remains a challenge under current technologies [5],…”

Section: Introductionmentioning

confidence: 99%

A distributed incremental update scheme for probability distribution of wind power forecast error

Jia

Shen

Wang

2020

International Journal of Electrical Power & Energy Systems

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Impact of the Uncertainty of Distributed Renewable Generation on Deregulated Electricity Supply Chain

Cited by 29 publications

References 17 publications

Efficient and Robust Equilibrium Strategies of Utilities in Day-ahead Market with Load Uncertainty

Efficient and Robust Equilibrium Strategies of Utilities in Day-ahead Market with Load Uncertainty

A Novel Framework to Determine the Impact of Time Varying Load Models on Wind DG Planning

A distributed incremental update scheme for probability distribution of wind power forecast error

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