Optimal Dispatch Strategy of a Virtual Power Plant Containing Battery Switch Stations in a Unified Electricity Market

Bai, Hongliang; Miao, Shihong; Ran, Xiaohong; Chang, Ye

doi:10.3390/en8032268

Cited by 61 publications

(37 citation statements)

References 34 publications

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“…In [10] is shown how the MG submits, in the day-ahead energy market, bidding curves price-quantity consistent with the results obtained by the optimal management problem [11,12]. In this work, indeed, the bidding strategy is limited to the submission, in the day-ahead energy and reserve markets, of the only one value of the optimal hourly powers exchanged with main grid, obtained in correspondence to the most probably hourly market price profiles.…”

Section: The Bidding Strategy and Literature Reviewsupporting

confidence: 53%

Bidding strategy of a micro grid for the day-ahead energy and spinning reserve markets: the problem formulation

Ferruzzi¹,

Rossi²,

Bracale³

2017

IJHT

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The paper is addressed to the construction of an optimally bidding for a Micro Grid (MG) that takes part to both day-ahead energy and spinning reserve markets. The work shows that the decision about the amount of power to offer, related to the expected prices and different risk tolerances, must be taken contextually through a joint approach. For that purpose, an optimization problem is formulated. In order to help the decision maker to understand the potential impact of different sub-optimal choices, the model evaluates also the risk associated with the uncertainty of variable power to offer in the both markets. The risk associated is evaluated by the expected utility theory that takes into account the attitude of individuals with regard to risk (adversion, neutrality or propensity) to make decision that minimize negative returns. The effectiveness of the proposed model is assessed through the analysis of a MG composed by traditional power plants, combined heat and power (CHP) plants, and heat production plants (boilers). The presence of storages systems is also accounted for. Moreover, it is considered that both generators and loads can take part in the reserve market and the demand participation happens through both shiftable and curtailable loads.

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Section: The Bidding Strategy and Literature Reviewsupporting

confidence: 53%

Bidding strategy of a micro grid for the day-ahead energy and spinning reserve markets: the problem formulation

Ferruzzi¹,

Rossi²,

Bracale³

2017

IJHT

View full text Add to dashboard Cite

show abstract

“…Therefore, the concept of the active distribution network coordinating the operation of distributed generation, active load and energy storage came into being [1]. However, due to the complexity of the renewable energy output characteristics, the different types of energy storage units and controllable load, as well as the continuous development and changes of the power grid architecture and operation control strategies, the optimization operation of the distribution network has become more and more complicated and is attracting increasing attention [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

et al. 2018

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Abstract:In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM) and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP), and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL), are still imperfect, which make it difficult for the active distribution network (ADN) to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified.

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“…The authors in [15] establish the day-ahead market clearing model considering the mean adjustment cost of the real-time market, which is calculated based on definite cost coefficients of thermal generators instead of uncertain clearing prices. In [16], a unified market for the day-ahead and real-time markets is proposed for the dispatch strategy of VPP, which utilizes definite real-time prices. In fact, the forecasted real-time prices are uncertain due to the fact that it is difficult to predict real-time prices accurately and obtain their correct probability distribution function since they are always subject to many factors, such as uncontrolled market conditions, balance between supply and demand, flow congestion, and so on [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

2017

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Abstract:In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO) is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle swarm algorithm (QPSO). Finally, the impacts of associated parameters on the separate trading and unified trading model are analyzed to verify the superiority of the proposed model and algorithm.

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Optimal Dispatch Strategy of a Virtual Power Plant Containing Battery Switch Stations in a Unified Electricity Market

Cited by 61 publications

References 34 publications

Bidding strategy of a micro grid for the day-ahead energy and spinning reserve markets: the problem formulation

Bidding strategy of a micro grid for the day-ahead energy and spinning reserve markets: the problem formulation

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

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