Optimal power flow solution including the syncronous generator capability curve constraints with a convex relaxation method

Fernandes, Italo G.; Paucar, V. Leonardo; Saavedra, Osvaldo R.

doi:10.1109/urucon.2017.8171891

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…active and reactive power markets). Many studies have not considered opportunity costs when scheduling active and reactive powers [19][20][21][22][23][24][25][26][27][28][29][30][31]. In certain studies the opportunity cost is defined in different ways [18,[33][34][35].…”

Section: Status Of the Literaturementioning

confidence: 99%

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An AC optimal power flow framework for active–reactive power scheduling considering generator capability curve

Vaishya

2023

Energy Conversion and Econom

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This paper presents a simplified optimal power flow (OPF) framework to facilitate co‐optimised active and reactive power scheduling for synchronous generators and price‐sensitive demands. The proposed framework creates an opportunity for generators and loads to simultaneously participate in a combined market for active and reactive power. The co‐optimisation of active and reactive power generation is constrained by the interdependence of the active and reactive power capacities, which is represented by the generator capability curve. Thus, a detailed mathematical derivation of the opportunity costs across various regions of the generator capability curve is presented. This study considers a detailed generator capability curve that considers the armature, field, under‐excitation, and prime mover limits. The interdependence of active and reactive power consumption for demand is modelled using the concept of power‐factor. The OPF problem for generator and load scheduling is formulated as a non‐linear optimisation task, leveraging the inherent properties of the generator capability curve, that is, piecewise smoothness, continuity, and the monotonically increasing slope magnitudes. Furthermore, to simplify the OPF formulation, the non‐linear capability curve is represented as a combination of the linear curves. To demonstrate the effectiveness of the proposed OPF methodologies, suitable case studies are conducted using different test systems.

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Section: Status Of the Literaturementioning

confidence: 99%

“…Furthermore, the price‐sensitive demands were not considered. In references [20] and [21], capability curve constraints were incorporated into the ACOPF problem as convex constraints. Reactive power locational marginal pricing was proposed in reference [22]; however, only the armature limit was considered.…”

Section: Introductionmentioning

confidence: 99%

An AC optimal power flow framework for active–reactive power scheduling considering generator capability curve

Vaishya

2023

Energy Conversion and Econom

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“…• Diesel generator active and reactive power limits for each time slot (Generator capability curves) [38], [39]: a) Prime-mover limits for each time slot: Limits on the mechanical power input from the primemover impose constraints on the active power generation and scheduled reserve.…”

Section: ) First Stage Inequality Constraintsmentioning

confidence: 99%

Data Driven Stochastic Energy Management for Isolated Microgrids Based on Generative Adversarial Networks Considering Reactive Power Capabilities of Distributed Energy Resources and Reactive Power Costs

et al. 2021

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This paper proposes a two-stage stochastic energy management (EM) in an isolated microgrid (MG) to decide for the day-ahead optimal dispatch. The dispatch aims to effectively manage the MG power sources, including intermittent renewable energy sources (RESs), battery energy storage systems (BESSs), and diesel generators such that the expected operation costs, reactive power costs, spinning reserve, and load shedding are minimized. The Generative Adversarial Networks (GANs) is utilized in this paper as a data driven scenario generation method to model the uncertainties in the output power of the RESs to be used in the stochastic programming formulation. Then, the fast forward scenario reduction algorithm is used to reduce the number of scenarios with the help of SCENRED/GAMS software. Usually, fuel consumption costs of diesel generators are considered to be dependent on active power generation only. However, neglecting the related reactive power costs might result in increased operation costs and deviations in the dispatches from the optimal solutions. Hence, this paper co-optimizes the costs related to both active and reactive powers of diesel generators. In addition, this study considers the reactive power capability of inverter-interfaced distributed energy resources (DERs). Moreover, the detailed models for the different resources are presented, especially for diesel generators where the actual capability curves are used instead of the widely used box constraints. The problem is formulated as a nonlinear programming problem in the General Algebraic Modeling System (GAMS) software and is solved by the CONOPT solver.

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A Multi-Temporal Optimal Power Flow Model for Normal and Contingent Operation of Microgrids

Javadi

Gouveia

Carvalho

2022

2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Syst

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Optimal power flow solution including the syncronous generator capability curve constraints with a convex relaxation method

Cited by 7 publications

References 11 publications

An AC optimal power flow framework for active–reactive power scheduling considering generator capability curve

An AC optimal power flow framework for active–reactive power scheduling considering generator capability curve

Data Driven Stochastic Energy Management for Isolated Microgrids Based on Generative Adversarial Networks Considering Reactive Power Capabilities of Distributed Energy Resources and Reactive Power Costs

A Multi-Temporal Optimal Power Flow Model for Normal and Contingent Operation of Microgrids

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