A Short-Term Dynamic Electricity Market Model with Memory Effect

Kërçi, Taulant; Tzounas, Georgios; Dassios, Ioannis; Murad, Mohammed Ahsan Adib; Milano, Federico

doi:10.1109/pesgm46819.2021.9637934

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…We can conclude that beside electricity markets, the proposed method can be used in the studies of other similar models where the memory effect appears. In fact, this type of operator is a very useful tool for time scale analysis with applications in macroeconomic problems, [37][38][39] electrical power systems, 40 and energy storage models. 41 As a further extension of this article, we aim to study the stability of the equilibriums of this system, perturbation methods, and construct optimization techniques in order to obtain optimal solutions for the case of existence but not uniqueness of solutions for this system.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Fractional‐order dynamical model for electricity markets

Dassios

Kërçi

Băleanu

et al. 2021

Math Methods in App Sciences

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In this article, we use a generalized system of differential equations of fractional-order to incorporate memory into an electricity market model. By using this idea, essential information from the past, such as the behavior of market participants, namely, suppliers and consumers, can be used and have impact on future decisions. We construct the fractional-order dynamical model, study its solutions, and provide closed formulas of solutions. Finally, we provide an application by using the proposed formula of solutions as well as a numerical example which also compares the proposed model with a conventional, integer-order electricity market model. Results indicate that the inclusion of memory leads market participants to adopt a conservative behavior.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Fractional‐order dynamical model for electricity markets

Dassios

Kërçi

Băleanu

et al. 2021

Math Methods in App Sciences

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Joint contribution of RTEM and AGC system for frequency stabilisation in renewable energy integrated power system

Debbarma,

Roy

et al. 2024

IET Energy Syst Integration

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Increasing penetration of variable renewable generations will diminish system inertia thereby degrading the conventional frequency regulation capability. As a result, maintaining frequency stability will be more and more challenging with traditional approaches. Even though renewable sources integration would jeopardise the grid stability, it also presents several opportunities as well. For example, converter‐interfaced generators can bid in real‐time electricity markets (RTEM) and provide short‐time dispatch to minimise load‐generation mismatch. In this paper, an integrated approach that accommodates discrete automatic generation control (AGC) system with a regulation mileage framework and RTEM model to balance generation and consumption is proposed. The RTEM model is assumed to have a five‐minute dispatch trading interval which is to some extent comparable to the discrete AGC system. Furthermore, a fractional order PID (FOPID) controller is equipped in the AGC system whose parameters are tuned using a novel metaheuristic‐based optimisation called Lichtenberg Algorithm (LA). The proposed framework is tested in a three‐area system under several operating conditions to reveal the improvement in the dynamic performance of the system. The objective function is also incorporated with mileage payment that allows a fair compensation rule for all the units.

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Power system modelling as stochastic functional hybrid differential‐algebraic equations

Milano

Liu

Murad³

et al. 2022

IET Smart Grid

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This paper presents the software tools developed for the research project Advanced Modelling for Power System Analysis and Simulation (AMPSAS) funded by Science Foundation Ireland from 2016 to 2021. The main objective of AMPSAS was the development of novel analytical and computational tools to understand, efficiently design, and optimise ever-changing modern power systems and smart grids, through modelbased approaches. In particular, the paper discusses (i) stochastic differential equations for modelling power systems, which are subject to large stochastic perturbations (e.g. wind and solar generation); (ii) the effect of controller and modelling imperfections, for example, delays, discontinuities, and digital signals, on both local and area-wide regulators in power systems; and (iii) the stability analysis and dynamic performance of power systems modelled through stochastic, delay and hybrid implicit differential-algebraic equations. The software tool developed during the execution of AMPSAS integrates areas of applied mathematics, automatic control, and computer science. Several implementation features and open challenges of this software tool are also discussed in the paper. A variety of examples that illustrates the features of this software tool are based on a dynamic model of the all-island Irish transmission system.

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A Short-Term Dynamic Electricity Market Model with Memory Effect

Cited by 4 publications

References 16 publications

Fractional‐order dynamical model for electricity markets

Fractional‐order dynamical model for electricity markets

Joint contribution of RTEM and AGC system for frequency stabilisation in renewable energy integrated power system

Power system modelling as stochastic functional hybrid differential‐algebraic equations

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