Solution to Economic Emission Dispatch problem using Lagrangian relaxation method

Shalini, S.P.; Lakshmi, K.

doi:10.1109/icgccee.2014.6922314

Cited by 15 publications

(8 citation statements)

References 7 publications

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“…In these types of dispatch problems, minimization of pollutants such as SO 2 and NO 2 gases is also considered along with fuel cost reduction objective. A Lagrange Multiplier Method (LMM) has also been used to solve ELD problems with high accuracy [48]. However, it has a slow convergence rate due to the iterative process, which involves many variables.…”

Section: Related Workmentioning

confidence: 99%

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

et al. 2018

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This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity market that involves the varying power demand bids and generates a required amount of energy in addition with reserve capacity. The lost opportunity cost is also considered and incorporated within the context of expected load not served. Then, the effects of combined and separate dispatching the energy and reserve are investigated. The nonlinear cost curves have been addressed by optimizing the objective function using robust optimization technique. Finally, various cases in accordance with underlying parameters have been considered in order to conduct and evaluate numerical results. Simulation results show the effectiveness of proposed scheduling model in terms of reduced cost and system stability.

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Section: Related Workmentioning

confidence: 99%

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

et al. 2018

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“…In [26], an improved pattern search-based method has been employed for the dynamic emission dispatch and for the multiobjective DEED problem where one of the main contributions has been the preservation of RRLs during the transition to the next day. LR-based methods have been used in [12,13,33] for the CEED problem where generator limits, line flow, and transmission line losses have been considered. The proposed methods have been tested by using IEEE 14-bus and IEEE 30-bus systems.…”

Section: Reviews For Various Optimization Techniques In Economic Disp...mentioning

confidence: 99%

“…Generally, these techniques can be classified into three categories as shown in Figure 1, which are conventional or traditional methods, non-conventional methods and hybrid methods. Over the last two decades, conventional techniques such as the LR method [12][13][14], the GS algorithm [15], the branch-and-bound algorithm (BBA) [16], the Lambda Iteration (LI) method [17][18][19][20][21][22][23][24][25], the PS algorithm [26], the QP technique [27][28][29], the classical technique based on coordination equations (CTBCE) [30], Linear Programming (LP) [31,32], Non-Linear Programming (NLP) [33], NLCNFP [34], Homogeneous Linear Programming (HLP) [35], Newton-Raphson (NR) [36][37], weighted mini-max (WMM) [38] and interior point method (IPM) [39] have been applied to solve the CEED problem.…”

Section: Introductionmentioning

confidence: 99%

Combined Economic Emission Dispatch with and without Consideration of PV and Wind Energy by Using Various Optimization Techniques: A Review

et al. 2022

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Combined economic emission dispatch (CEED) problems are among the most crucial problems in electrical power systems. The purpose of the CEED is to plan the outputs of all production units available in the electrical power system in such a way that the cost of fuel and polluted emissions are minimized while respecting the equality and inequality constraints of the system and efficiently responding to the power load required. The rapid depletion of these sources causes limitation and increases the price of fuel. It is therefore very important that scientific research in the last few decades has been oriented toward the integration of renewable energy systems (RES) such as wind and PV as an alternative source. Furthermore, the CEED problem including RES is the most important problem with regard to electrical power field optimization. In this study, a classification of optimization techniques that are widely used, such as traditional methods, non-conventional methods, and hybrid methods, is summarized. Many optimization methods have been presented and each of them has its own advantages and disadvantages for solving this complex CEED problem, including renewable energy. A review of different optimization techniques for solving this CEED problem is explored in this present paper. This review will encourage researchers in the future to gain knowledge of the best approaches applicable to solve CEED problems for practical electrical systems.

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“…The main important mathematical-based methods that are addressed in the literature are Lagrange Relaxation [8] lambda iteration [9], Newton-Raphson [10], and interiorpoint [11] methods. The lack of specific parameters to adjust is the main advantage of these techniques, and although they may be trapped in a local optimum, high sensitivity to the initial solutions is their most significant drawback.…”

Section: Related Workmentioning

confidence: 99%

Environmental/Economic Dispatch Using a New Hybridizing Algorithm Integrated with an Effective Constraint Handling Technique

Nourianfar

Abdi

2022

Sustainability

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This work tackles a relatively new issue in power system operation, known as the Environmental/Economic Dispatch problem. For this purpose, the combination of two powerful heuristic algorithms, namely, the Exchange Market Algorithm (EMA) and Adaptive Inertia Weight Particle Swarm Optimization (AIWPSO), was employed. Additionally, the Multiple Constraint Ranking (MCR) technique was used to address the system constraints such as prohibited operating zones and ramp rate limits. Furthermore, the mutation operator was used to improve the performance of the global search mechanism. The main purpose of combining these two algorithms was utilizing the EMA’s high performance to explore the global optimum and local exploitation ability of AIWPSO. The algorithm performance was evaluated on six standard benchmark functions and was scrutinized on several different test systems, including 6–40 units. By using the proposed method, the minimum values of the reduction in annual costs, with equal or less emissions, compared to other methods, were USD 17,520, 8760 and 10,801,080, respectively, for the 6-unit, 10-unit, and 40-unit test systems (assuming the same load profile throughout the year). Similarly, in the 14-unit test system for 1750, 2150, and 2650 (MW) load demands, these values were USD 229,879, 148,438, and 4483, respectively.

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Solution to Economic Emission Dispatch problem using Lagrangian relaxation method

Cited by 15 publications

References 7 publications

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

Combined Economic Emission Dispatch with and without Consideration of PV and Wind Energy by Using Various Optimization Techniques: A Review

Environmental/Economic Dispatch Using a New Hybridizing Algorithm Integrated with an Effective Constraint Handling Technique

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