Risk-Constrained Profit Maximization for Microgrid Aggregators With Demand Response

Nguyen, Duong Tung; Le, Long Bao

doi:10.1109/tsg.2014.2346024

Cited by 273 publications

(110 citation statements)

References 47 publications

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“…These insights reveal fundamental limitations of the approaches adopted in [6]- [14], in dealing effectively with the high-dimensional stochastic problem faced by the DER aggregator. When such approaches consider multivariate uncertainty in a multistage context, a combinatorial explosion of the possible realizations is expected as the planning horizon expands, and the problem soon becomes intractable.…”

Section: B Motivationmentioning

confidence: 99%

“…Existing literature modeling the optimal operation of DER aggregators has mainly focused on stochastic programming (SP) approaches, employing two-stage uncertainty models [6]- [14]. A simplified representation of the uncertainty space is usually adopted, utilizing various scenario generation and reduction techniques.…”

mentioning

confidence: 99%

“…A simplified representation of the uncertainty space is usually adopted, utilizing various scenario generation and reduction techniques. In [6], a risk-constrained two-stage stochastic formulation is presented, where stochasticity is captured through a Monte-Carlo scenario based approach and uncertain parameters are assumed to follow normal zero-mean distributions. Ignoring potential dependencies among these uncertainties, 5000 scenarios are initially sampled and are then reduced to 100 for computational tractability purposes.…”

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confidence: 99%

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Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Fatouros

Konstantelos

Papadaskalopoulos

et al. 2019

IEEE Trans. Sustain. Energy

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Abstract--The operation of aggregators of distributed energy resources (DER) is highly complex, since it entails the optimal coordination of a diverse portfolio of DER under multiple sources of uncertainty. The large number of possible stochastic realizations that arise, can lead to complex operational models that become problematic in real-time market environments. Previous stochastic programming approaches resort to two-stage uncertainty models and scenario reduction techniques to preserve the tractability of the problem. However, two-stage models cannot fully capture the evolution of uncertain processes and the a priori scenario selection can lead to suboptimal decisions. In this context, this paper develops a novel stochastic dual dynamic programming (SDDP) approach which does not require discretization of either the state space or the uncertain variables and can be efficiently applied to a multi-stage uncertainty model. Temporal dependencies of the uncertain variables as well as dependencies among different uncertain variables can be captured through the integration of any linear multidimensional stochastic model, and it is showcased for a porder vector autoregressive (VAR) model. The proposed approach is compared against a traditional scenario-tree-based approach through a Monte-Carlo validation process, and is demonstrated to achieve a better trade-off between solution efficiency and computational effort.Index Terms--Aggregator, distributed energy resources, multidimensional uncertainty, stochastic dual dynamic programming, vector autoregressive modeling. I. NOMENCLATURE A. IndexesIndex of time periods, running from 1 to . Index of energy storage (ES) units, running from 1 to . Index of flexible loads (FL), running from 1 to . Index of wind turbines (WT), running from 1 to . Index of micro-generators, running from 1 to . B. ParametersEnergy market price at period . Operating cost of micro-generator . Cost of demand shedding. C. VariablesPower sold to (positive)/bought from (negative) the market at period . ,Power output of micro-generator at period . Demand shed at period ., Energy level of ES unit at period . ,Power input (positive) / output (negative) of ES unit at period . , ℎChange of demand of FL at period due to load shifting. ,Demand of FL at period after load shifting., Dispatched wind power output of WT at period . II. INTRODUCTIONA. Background FUNDAMENTAL feature of the emerging Smart Grid paradigm involves the integration of a large number of distributed energy resources (DER) storage units, in order to support the economic operation of the future low-carbon power system [1]- [2]. However, the large number, small individual size and inherent stochasticity characterizing these DER have complicated system scheduling and market coordination. Furthermore, driven by the wide integration of renewable generation in power systems, there is a general consensus to move energy trading as close as possible to real-time [3]- [4], which intensifies the complexity of DER coordination. These challenges have...

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Section: B Motivationmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Fatouros

Konstantelos

Papadaskalopoulos

et al. 2019

IEEE Trans. Sustain. Energy

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“…Besides, Demand Response Providers (DRPs) are newly emerged form of retailers which aggregate DR resources of the multiple small customers [67] and can provide a single operating profile by deployment of Advanced Metering Infrastructure (AMI) for DR resources same as a generating unit [68].…”

Section: Retail Energy Management In Presence Of Newly Emerged Entitiesmentioning

confidence: 99%

Retail Energy Management in Electricity Markets: Structure, Challenges and Economic Aspects- a Review

Golmohamadi

Keypour

2017

Technol Econ Smart Grids Sustain Energy

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In the rapidly growing global energy consumption, electrical energy plays the important role. Environmental concerns about air pollution, fossil fuels depletion and energy crisis have led policy makers of energy systems to increase the portion of electricity in the energy portfolio. On the other hand, economic crises, especially in recent years, have increased the electricity price. With decreased purchasing power, end-use consumers are encouraged to participate in Demand Side Management (DSM) programs, e.g. Demand Response Programs (DRPs), to decrease their electricity bills. In such situation, retail energy management attracts attention in both development and improvement. This paper reviews the concept of retail energy management in modern structure of electricity markets. The objectives of this study are: a) review techno-economic studies in the literature to identify the main structure of retail energy management; b) review the different retail market studies for assessing economic performance; c) present a comprehensive evaluation about the role of DRPs in retail energy management; d) carry out an extensive survey of optimization approaches, mathematical modeling and optimization software about the retail energy management. This paper provides a template for market participants to optimize energy management in the retail side of electricity markets. The proposed structure encourages the efficient development of retail electricity market while eliminating

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“…In [2], a random error term is added to the expected values of the energy price and conventional demand to represent their uncertain nature in the portfolio optimization of an aggregator participating in the forward and spot markets. In [3], the profit maximizing policy of a microgrid aggregator is derived, where scenarios about uncertain system load, wind power output and electricity prices are derived by MonteCarlo sampling. Finally, in [4] the problem of optimizing the energy procurement schedule of a DER aggregator under uncertain energy prices, load and RES output, is addressed.…”

Section: A Backgroundmentioning

confidence: 99%

A stochastic dual dynamic programming approach for optimal operation of DER aggregators

Fatouros

Konstantelos

Papadaskalopoulos

et al. 2017

2017 IEEE Manchester PowerTech

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Abstract-The operation of aggregators of distributed energy resources (DER) is a highly complex task that is affected by numerous factors of uncertainty such as renewables injections, load levels and market conditions. However, traditional stochastic programming approaches neglect information around temporal dependency of the uncertain variables due to computational tractability limitations. This paper proposes a novel stochastic dual dynamic programming (SDDP) approach for the optimal operation of a DER aggregator. The traditional SDDP framework is extended to capture temporal dependency of the uncertain wind power output, through the integration of an n-order autoregressive (AR) model. This method is demonstrated to achieve a better trade-off between solution efficiency and computational time requirements compared to traditional stochastic programming approaches based on the use of scenario trees.

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Risk-Constrained Profit Maximization for Microgrid Aggregators With Demand Response

Cited by 273 publications

References 47 publications

Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Retail Energy Management in Electricity Markets: Structure, Challenges and Economic Aspects- a Review

A stochastic dual dynamic programming approach for optimal operation of DER aggregators

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