Robust Short-Term Scheduling of Integrated Heat and Power Microgrids

Nazari-Heris, Morteza; Mohammadi‐Ivatloo, Behnam; Gharehpetian, Gevork B.; Shahidehpour, Mohammad

doi:10.1109/jsyst.2018.2837224

Cited by 91 publications

(52 citation statements)

References 30 publications

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“…Extensive research has been devoted to methods suggesting microgrids to improve the framework of power systems. In [1] and [2], it is shown that microgrids offer an effective way of managing uncertainty of the generation and demand balance. Matching the load to generation at the local level is an ideal method for precisely maintaining the balance and minimizing losses associated with transmission lines.…”

Section: Load Balancingmentioning

confidence: 99%

A New Method for Peer-to-Peer Energy Exchange in Distribution Grids

2020

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In this paper, distribution-level peer-to-peer energy exchange is proposed that allows increased matching between load and generation nodes. Contributions of the proposed improved matching system between the local load and generation nodes aim at making efficient use of unused power generation, reducing the cost of electrical energy for consumers, and assisting utility companies by reducing transmission line congestion. The proposed system for matching the load and generation nodes consists of a financial layer and technical layer. In the financial layer, nodes with an excess of energy provide a price to sell energy, while the nodes needing energy bid on a price to purchase energy. A market-clearing mechanism using pool clearing is applied to determine a final price for peer-to-peer exchange. The technical layer determines the connection of energy transfer between the generation and load nodes while considering the distance, power flow constraints, and specified time windows. The proposed approach is verified in a five-node system and the results are discussed.

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Section: Load Balancingmentioning

confidence: 99%

A New Method for Peer-to-Peer Energy Exchange in Distribution Grids

2020

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“…The system in the proposed STHS model is responsible to satisfy the daily load demand and is capable to sell the surplus generated power to the market where, 1 t  and  are dual variables. Accordingly, the robust formulation of the problem is obtained using the Karush-Kuhn-Tucker (KKT) condition, which is provided as follows [30]:…”

Section: The Proposed Robust Stochastic Scheduling Of Hydrothermal Symentioning

confidence: 99%

“…The system operation cost includes fuel cost of thermal units considering ignorable operation cost of hydropower units. Accordingly, the objective function of the introduced framework can be stated as[30]: uncertain power market price at t th time interval is defined by , power sold to the market at t th time interval is indicated by , The inner problem can be reformulated to an equivalent formulation as follows[30]:…”

mentioning

confidence: 99%

Robust stochastic optimal short-term generation scheduling of hydrothermal systems in deregulated environment

Nazari-Heris

Mohammadi‐Ivatloo²,

Asadi

2018

Journal of Energy Systems

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Hydrothermal systems play a significant role in electric energy systems as important power generation units, which have been studied in previous researches considering remarkable efforts. The optimal short-term hydrothermal scheduling (STHS) aims to attain optimal production scheduling of thermal and hydro plants for determining minimum operation cost of providing demand in the determined time interval. Different constraints should be studied in the solution of such issue containing limitations associated with water discharge, water storage, power production of plants, power balance of the system and water balance of hydro plants. In addition, valve impacts of thermal plants and complex hydraulic coupling of hydro plants are the other operational and technical constraints. In this study, the robust stochastic STHS is studied considering market price and demand uncertainties. Accordingly, robust optimization method is employed in this study to model price uncertainties. In addition, the uncertainties of load demand are handled using scenario-based modeling procedure. The scheduling problem of hydrothermal system is studied in a deregulated environment, where the hydrothermal system belongs to the private company and is capable to sell the surplus generated power to the market. Accordingly, the company aims to obtain maximum profit by selling power to market in addition to supplying power demand of the company. The introduced scheme for stochastic robust STHS is simulated and the provided solutions are investigated to verify the effectiveness of the scheme.

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“…To resolve the issues mentioned above, various methods and techniques have been studied and utilized to control the outcomes caused by possible uncertainty in the behavior of parameters. Previously implemented techniques according to [2] are possibilistic technique [3], probabilistic technique [4], hybrid possibilisticprobabilistic techniques [5], robust optimization technique [6,7], information gap decision theory (IGDT) [8,9] and interval analysis [10]. The mentioned approaches and techniques are briefly illustrated in Fig.…”

Section: Introductionmentioning

confidence: 99%

Application of information gap decision theory in practical energy problems: A comprehensive review

2019

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The uncertainty and risk modeling is a hot topic in operation and planning of energy systems. The system operators and planners are decision makers that need to handle the uncertainty of input data of their models. As an example, energy consumption has always been a critical problem for operators since the forecasted values, and the actual consumption is never expected to be the same. The penetration of renewable energy resources is continuously increasing in recent and upcoming years.These technologies are not dispatch-able and are highly dependent on natural resources. This would make the real-time energy balancing more complicated. Another source of uncertainty is related to energy market prices which are determined by the market participants' behaviors. To consider these issues, the uncertainty modeling should be performed. Various approaches have been previously utilized to model the uncertainty of these parameters such as probabilistic approaches, possibilistic approaches, hybrid possibilisticprobabilistic approach, information gap decision theory, robust and interval optimization techniques. This paper reviews the research works that used information gap decision theory for uncertainty modeling in energy and power systems.

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Robust Short-Term Scheduling of Integrated Heat and Power Microgrids

Cited by 91 publications

References 30 publications

A New Method for Peer-to-Peer Energy Exchange in Distribution Grids

A New Method for Peer-to-Peer Energy Exchange in Distribution Grids

Robust stochastic optimal short-term generation scheduling of hydrothermal systems in deregulated environment

Application of information gap decision theory in practical energy problems: A comprehensive review

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