Optimal scheduling of distributed energy resources in microgrid systems based on electricity market pricing strategies by a novel hybrid optimization technique

Dey, Bishwajit; Raj, Saurav; Mahapatra, Sheila; Márquez, Fausto Pedro García

doi:10.1016/j.ijepes.2021.107419

Cited by 77 publications

(17 citation statements)

References 51 publications

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“…The three algorithms, Modified Grey wolf algorithm (MGWO), sine cosine algorithm (SCA), and crow search algorithm (CSA) were combined together to form a new hybrid MGWO-SCA-CSA algorithm. The position cum iteration updating equation from MGWO-CSA and the hunting equation from MGWO-SCA are used in the Modified GWO-SCA-CSA [23][24][25] method. The parameters 'AP' of CSA and 'a' of MGWO ensure that the algorithm is explored and exploited.…”

Section: Modified Gwo-sca-csamentioning

confidence: 99%

“…2 Fixed electricity market price Unlike scenario 1, where the grid buys and sells power on time of usage (TOU) based dynamic electricity market pricing strategy, a fixed pricing strategy of electricity is considered in this scenario. This concept is adopted from [21,24], where the authors state that TOU based market pricing strategy reduces the operating cost of a microgrid to a greater extent compared to fixed price strategy. The reason for adopting this concept is to analyse the effect of grid pricing while evaluating environmental constrained economic dispatch of a microgrid system.…”

Section: Scenario Features Detailed Descriptionmentioning

confidence: 99%

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Demand side management for solving environment constrained economic dispatch of a microgrid system using hybrid MGWOSCACSA algorithm

Basak

Dey

Bhattacharyya

2022

CAAI Trans on Intel Tech

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Microgrids are a type of restricted power distribution systems in which electricity is generated, transmitted, and distributed within a small geographic region. They are used to ensure that renewable energy sources are used to their full potential. Microgrids provide further benefits, such as lowering transmission losses and the expenses associated with them. This research compares and contrasts the aims of economic dispatch, emission dispatch, fractional programing based combined economic emission dispatch, and environmental restricted economic dispatch (ECED). A low-voltage microgrid system is investigated for three different scenarios. As a study optimization tool, an innovative, resilient, and strong hybrid swarm-intelligence optimization algorithm is utilised, which is based on combining the properties of the traditional grey-wolf optimiser, sine-cosine algorithm, and crow search algorithm. The employment of a time-of-use energy market pricing approach instead of a fixed pricing plan resulted in a 15% decrease in generation costs throughout the course of the research. When ECED was assessed with a 15%-20% demand side management based restructured load demand model for the microgrid system, the generation costs were reduced even further. K E Y W O R D S demand side management, energy management, MGWOSCACSA, microgrid 1 | INTRODUCTION 1.1 | General overviewIn Economic Load Dispatch (ELD), Renewable Energy Sources (RES) are employed primarily. According to ELD, many units interconnected in a power system network do not produce the same quantity of power to meet the load demand, but rather deliver according to their fuel costs, that is, the production cost per unit of production will fluctuate from one unit to the next. Total energy output, on the other hand, must meet total demand [1]. On the basis of load demand, ELD is divided into two types: static ELD (SELD) and dynamic ELD (DELD). Dynamic ELD (DELD) is the case where the load varies over the time, it is known as SELD presents less complexity and contains limited constraints, for example, such as prohibited operating zones, ramp rates, etc, than DELD [2,3]. But DELD is a more complex problem. DELD has more constraints associated with the Distributed Energy Resources (DER) and time periods along with the constraints of SELD [4]. DELD must tackle problems such as the charging/ discharging condition of energy storage systems, DER shut down timings, startup, and so on. | Literature reviewMany research papers are being published to provide the best cost-efficient distribution of renewable energy generation. The main objective is to offer a reference to the economy of the This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Modified Gwo-sca-csamentioning

confidence: 99%

Section: Scenario Features Detailed Descriptionmentioning

confidence: 99%

Demand side management for solving environment constrained economic dispatch of a microgrid system using hybrid MGWOSCACSA algorithm

Basak

Dey

Bhattacharyya

2022

CAAI Trans on Intel Tech

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“…References [27]- [31] used a combination of bio-inspired approaches to solve the reactive power-source planning problem. Reference [32] presented a hybrid metaheuristic approach to reduce the cost of microgrid systems. References [33][34] proposed a modified version of the original whale optimization approach and the Harris hawk optimizer to solve complex optimization problems.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Latency- and Power-Aware Approach for Beyond Fifth-Generation Internet-of-Things Edge Systems

Kaushik

Al-Raweshidy

2022

IEEE Access

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Fifth-generation (5G) empowered internet of things (IoT) edge networks suffer from latency in delay-sensitive applications. To fulfil the low latency requirements of beyond fifth-generation (B5G)-IoT applications and provide quality of service (QoS) to IoT-edge communication, it is important to minimize server delay. Furthermore, 5G-IoT systems consume more power than their predecessors, which is a concern given the growing size of future IoT networks. This research presents a hybrid latency and power-aware approach for B5G-IoT networks (HLPA B5G-IoT) that minimizes latency with minimum overhead on battery-constrained IoT nodes while simultaneously providing a power-efficient solution for B5G-IoT-edge networks. HLPA B5G-IoT has a novel algorithm classifier tool (ACT) for selecting appropriate optimization algorithms based on the characteristics and requirements of B5G-IoT systems. The ACT matrix not only parametrically compares HLPA B5G-IoT with existing approaches but also identifies crucial parameters that enable algorithm selection for load balancing and energy efficiency. In this paper, metaheuristic algorithms, i.e., biogeography-based optimization (BBO) and grey wolf optimization (GWO), are tailored to meet the requirements of load balancing and power efficiency in IoT-edge systems. The proposed load-balancing algorithm reduces latency and improves overall network performance by 33.33%, 27.45%, 23.52%, 21.56%, 13.72%, 11.76%, and 7.84% compared with simulated annealing (SA), genetic algorithm (GA), particle swarm optimization (PSO), bacteria foraging algorithm (BFA), ant colony optimization (ACO), bat algorithm (BA), and genetic SA PSO (GSP), respectively. The power-efficiency algorithm consumes 46.6%,

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“…Chaotic PSO has been applied for fractional order fuzzy control of HPS in reference 19. The performance of an isolated HPS model that consists of a WTG and a DEG has been studied in reference 20 using intelligent technique. A robust adaptive LFC mechanism for micro‐grids has been studied in reference 21.…”

Section: Introductionmentioning

confidence: 99%

Load frequency stabilization of stand‐alone hybrid distributed generation system using QOHS algorithm

Shiva¹,

Vedik²,

Mahapatra

et al. 2022

Int J Numerical Modelling

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The proposed work studies the frequency stability of the identified hybrid power network (HPS) model with the integration of RESs and ESDs. The research work depicted here includes load frequency issue pertaining to isolated mode of operations with uncertainties in power oscillations of wind and solar energy. The studied HPS model is constitute of three wind turbine generators, two solar thermal generators, three diesel engine generators, an aqua electrolyzer and two fuel-cells as generating units while battery energy storage system, flywheel energy storage system and ultra-capacitor as back-up energy sources. A centralized control scheme using PID controller is employed for the controller design problem and its parameters are tuned by a nature inspired Quasi-oppositional Harmony Search (QOHS) algorithm. The three scenarios as step change, step change with stochastic effects and firm model of wind velocity, solar radiation and load demand are studied for the load frequency control dynamic performance. The execution of suggested QOHS based PID controller is contrasted with the studied optimization techniques. It may be inferred that the RESs and ESDs feeding isolated loads are properly operated to attain the coveted level of system frequency by using the QOHS technique.

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Optimal scheduling of distributed energy resources in microgrid systems based on electricity market pricing strategies by a novel hybrid optimization technique

Cited by 77 publications

References 51 publications

Demand side management for solving environment constrained economic dispatch of a microgrid system using hybrid MGWOSCACSA algorithm

Demand side management for solving environment constrained economic dispatch of a microgrid system using hybrid MGWOSCACSA algorithm

A Hybrid Latency- and Power-Aware Approach for Beyond Fifth-Generation Internet-of-Things Edge Systems

Load frequency stabilization of stand‐alone hybrid distributed generation system using QOHS algorithm

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