Design of economic dispatch model for Gencos with thermal and wind powered generators

Geetha, K.; Deve, V. Sharmila; Keerthivasan, K.

doi:10.1016/j.ijepes.2014.12.069

Cited by 18 publications

(18 citation statements)

References 19 publications

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“…In this paper, the wind energy is selected as the renewable energy that integrates with the ED model. As suggested by Hetzer et al [2008], Geetha et al [2015], the linear cost function of the wind energy model is as follows:…”

Section: The Ed Optimisation Problemmentioning

confidence: 99%

“…(3) to (5) are converted into a single objective function, incorporating the maximum price penalty factor h max in the emission function. Following the methodology Senthil and Manikandan [2010], Subramanian and Ganesan [2010], Geetha et al [2015], Khan et al [2015], the objective function of the ED problem is follows:…”

Section: The Ed Optimisation Problemmentioning

confidence: 99%

“…According to Balancing Mechanism Reporting Systems [2015], as it is the normal routine to have breakdowns during energy generation by fuel type, any fuel type with negative values in the dataset is capped to zero of total positive generation in order to meet the energy demand. Additionally, as there is no minimum operating energy limit for wind generation, the minimum amount of wind generation is set as zero [Geetha et al, 2015]. According to Ramanathan [1994], the emission constraint is not needed to be computed as the optimality condition can be achieved by imposing the constraint of the energy balance and generator limit.…”

Section: The Ed Optimisation Problemmentioning

confidence: 99%

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Optimisation of costs and carbon savings in relation to the economic dispatch problem as associated with power system operation

Lau

Yang

Taylor

et al. 2016

Electric Power Systems Research

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In this paper, the costs and carbon savings in the Economic Dispatch (ED) problem of the power system operation are optimised. Energy demands and generation are forecast and assimilated using Ensemble Kalman Filter (EnKF). Optimisation is performed using the Ensemble-based Closed-Loop Production Optimisation Scheme (EnOpt). The real energy parameters of thermal units with green generators (wind farm) are used to test the methodology. The ability of the EnKF to predict, and the robustness of the EnOpt to optimise costs and the resultant carbon emissions are demonstrated. The proposed approach addresses the complexity and diversity of the power system and may be implemented in operational conditions of energy suppliers.

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Section: The Ed Optimisation Problemmentioning

confidence: 99%

Section: The Ed Optimisation Problemmentioning

confidence: 99%

Section: The Ed Optimisation Problemmentioning

confidence: 99%

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Optimisation of costs and carbon savings in relation to the economic dispatch problem as associated with power system operation

Lau

Yang

Taylor

et al. 2016

Electric Power Systems Research

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“…Literature [4] introduced a new general equation for power system economic scheduling model, considering conventional thermal units, wind turbine generators, and changing characteristics of wind speed and power demand. The influence the dynamic cost coefficients have on system 2 Mathematical Problems in Engineering operation costs has been analyzed in a simple testing system.…”

Section: Introductionmentioning

confidence: 99%

A Multiobjective Robust Scheduling Optimization Mode for Multienergy Hybrid System Integrated by Wind Power, Solar Photovoltaic Power, and Pumped Storage Power

Zhang

et al. 2017

Mathematical Problems in Engineering

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Wind power plant (WPP), photovoltaic generators (PV), cell-gas turbine (CGT), and pumped storage power station (PHSP) are integrated into multienergy hybrid system (MEHS). Firstly, this paper presents MEHS structure and constructs a scheduling model with the objective functions of maximum economic benefit and minimum power output fluctuation. Secondly, in order to relieve the uncertainty influence of WPP and PV on system, robust stochastic theory is introduced to describe uncertainty and propose a multiobjective stochastic scheduling optimization mode by transforming constraint conditions with uncertain variables. Finally, a 9.6 MW WPP, a 6.5 MW PV, three CGT units, and an upper reservoir with 10 MW⋅h equivalent capacity are chosen as simulation system. The results show MEHS system can achieve the best operation result by using the multienergy hybrid generation characteristic. PHSP could shave peak and fill valley of load curve by optimizing pumping storage and inflowing generating behaviors based on the load supply and demand status and the available power of WPP and PV. Robust coefficients can relieve the uncertainty of WPP and PV and provide flexible scheduling decision tools for decision-makers with different risk attitudes by setting different robust coefficients, which could maximize economic benefits and minimize operation risks at the same time.

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“…Usually, electric utilities solve the DEED with other associated tasks like unit commitment, 13,30 and due to the increasing interest in renewable energy, utilities also solve DEED with the incorporation of renewable energy sources like wind and solar power. 14,[32][33][34][35][36][37][38] In light of the advent of the smart grid and the need to convert load customers into active interacting participants who engage with the utility to reduce system demand, 15,31 we introduce a combined DEED with DR under an interactive control strategy. This would lead to the mitigation of incidences of brownouts and blackouts caused by ever increasing customer demand, which is one of the principal benefits of DR. 31 In the formulation presented in this work, the utility minimizes the generation and DR costs and determines the optimal hourly price.…”

mentioning

confidence: 99%

A combined dynamic economic emission dispatch and time of use demand response mathematical modelling framework

Nwulu¹,

Xia²

2015

Journal of Renewable and Sustainable Energy

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In this paper, we integrate a Demand Response (DR) program into the multi-objective dynamic economic emission dispatch (DEED) optimization problem. The resulting optimization problem is termed DR-DEED. The DR program is a time based program known as the Time of Use DR program. The DR program has been developed using the customers' Price Elasticity Matrices, which models the customer behavior under different conditions. An interactive control strategy between utility and consumers is proposed for the combined DR-DEED model, which determines the optimal power to be generated by minimizing fuel, emissions, and DR costs and also the optimal price. The customer in light of the utility's optimal price minimizes its electricity cost and optimally schedules power consumption. Obtained results indicate that DR programs are mutually beneficial to utility and consumers alike and can bring about desired demand reduction in the power system. V C 2015 AIP Publishing LLC.

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Design of economic dispatch model for Gencos with thermal and wind powered generators

Cited by 18 publications

References 19 publications

Optimisation of costs and carbon savings in relation to the economic dispatch problem as associated with power system operation

Optimisation of costs and carbon savings in relation to the economic dispatch problem as associated with power system operation

A Multiobjective Robust Scheduling Optimization Mode for Multienergy Hybrid System Integrated by Wind Power, Solar Photovoltaic Power, and Pumped Storage Power

A combined dynamic economic emission dispatch and time of use demand response mathematical modelling framework

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