scholarly journals Combined Economic Emission Dispatch with Environment-Based Demand Response Using WU-ABC Algorithm

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6450
Author(s):  
Ho-Sung Ryu ◽  
Mun-Kyeom Kim
Keyword(s):  
Demand Response ◽  
Test System ◽  
Optimal Operation ◽  
Pollutant Emissions ◽  
Superior Performance ◽  
Pollutant Emission ◽  
Abc Algorithm ◽  
Penalty Factor ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

Owing to the growing interest in environmental problems worldwide, it is essential to schedule power generation considering the effects of pollutants. To address this, we propose an optimal approach that solves the combined economic emission dispatch (CEED) with maximum emission constraints by considering demand response (DR) program. The CEED consists of the sum of operation costs for each generator and the pollutant emissions. An environment-based demand response (EBDR) program is used to implement pollutant emission reduction and facilitate economic improvement. Through the weighting update artificial bee colony (WU-ABC) algorithm, the penalty factor that determines the weighting of the two objective functions is adjusted, and an optimal operation solution for a microgrid (MG) is then determined to resolve the CEED problem. The effectiveness and applicability of the proposed approach are demonstrated via comparative analyses at a modified grid-connected MG test system. The results confirm that the proposed approach not only satisfies emission constraints but also ensures an economically superior performance compared to other approaches. These results present a useful solution for microgrid operators considered environment issues.

scholarly journals Optimal Operation for Economic and Exergetic Objectives of a Multiple Energy Carrier System Considering Demand Response Program

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3995 ◽  
Author(s):  
Yu Huang ◽  
Shuqin Li ◽  
Peng Ding ◽  
Yan Zhang ◽  
Kai Yang ◽  
...  
Keyword(s):  
Demand Response ◽  
Test System ◽  
Optimal Operation ◽  
Energy Carrier ◽  
Mixed Integer ◽  
Selection Strategy ◽  
Operation Strategy ◽  
Carrier System ◽  
Energy Carriers ◽  
Scheduling Model

An MECS (multiple energy carrier system) could meet diverse energy needs owing to the integration of different energy carriers, while the distinction of quality of different energy resources should be taken into account during the operation stage, in addition the economic principle. Hence, in this paper, the concept of exergy is adopted to evaluate each energy carrier, and an economic–exergetic optimal scheduling model is formulated into a mixed integer linear programming (MILP) problem with the implementation of a real-time pricing (RTP)-based demand response (DR) program. Moreover, a multi-objective (MO) operation strategy is applied to this scheduling model, which is divided into two parts. First, the ε-constraint method is employed to cope with the MILP problem to obtain the Pareto front by using the state-of-the-art CPLEX solver under the General Algebraic Modeling System (GAMS) environment. Then, a preferred solution selection strategy is introduced to make a trade-off between the economic and exergetic objectives. A test system is investigated on a typical summer day, and the optimal dispatch results are compared to validate the effectiveness of the proposed model and MO operation strategy with and without DR. It is concluded that the MECS operator could more rationally allocate different energy carriers and decrease energy cost and exergy input simultaneously with the consideration of the DR scheme.

Multi-objective economic emission dispatch of thermal power plants based on grey relational analysis and analytic hierarchy process

2019 ◽  
Vol 31 (5) ◽  
pp. 785-812
Author(s):  
Shiyi Chen ◽  
Wei Chen ◽  
Ahsanullah Soomro ◽  
Lijuan Luo ◽  
Wenguo Xiang
Keyword(s):  
Analytic Hierarchy Process ◽  
Grey Relational Analysis ◽  
Pollutant Emission ◽  
Analytic Hierarchy ◽  
Relational Analysis ◽  
Power Dispatch ◽  
Grey Relational ◽  
Emission Dispatch ◽  
Hierarchy Process ◽  
Economic Emission Dispatch

In this paper, mathematical models for a synthesized evaluation were established according to grey relational analysis and analytic hierarchy process. The models were used to select a power dispatch scheme considering hierarchies of material consumption, electrical efficiency, exergy efficiency, and environmental benefit. Four unit dispatch schemes, i.e., proportional fair allocation dispatch, conventional economic dispatch, economic emission dispatch, and economic emission dispatch with varied weights were investigated and compared. Analytic hierarchy process decision-making approach has been employed to find the optimal Pareto solution as the best tradeoff between cost and pollutant emission. The model indicated that the economic emission dispatch was preferred as the best option and could further reduce fuel consumption and pollutant emission, followed by the economic emission dispatch with varied weights. The assessment performed serves decision makers a valuable reference for policy making in the power dispatch sector.

Hybrid PSO-SQP for solving combined heat and power dynamic economic emission dispatch problem with non-smooth cost function

2017 ◽  
Vol 8 (1) ◽  
pp. 85 ◽  
Author(s):  
A. M. Shehata
Keyword(s):  
Optimal Solution ◽  
Combined Heat And Power ◽  
Test System ◽  
Primary Objective ◽  
Global Optimal Solution ◽  
Power Dynamic ◽  
Hybrid Particle Swarm Optimization ◽  
Global Optimal ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

In this paper we propose a hybrid particle swarm optimization (PSO) and sequential quadratic programming (SQP) for solving the combined heat and power dynamic economic emission dispatch (CHPDEED) problem. The primary objective of CHPDEED is to determine the optimal heat and power generation schedule of the online generating units over a fixed interval by simultaneously minimizing the generation cost and emission level and satisfying the dynamic constraints and other constraints. Taking into account the valve point effects, CHPDEED is considered as a multi-objective optimization problem with non-smooth characteristics. In the hybrid method, PSO is used as a global search to find near global optimal solution and this solution is used as initial for the SQP to find the global optimal solution at the end. The proposed method is verified using a test system consisting of eleven units and considering transmission line losses and valve point effects. The numerical results show the effectiveness and the superiority of the introduced method over other published methods.

Dynamic Economic Emission Dispatch Using Multi-Objective Hybrid Evolutionary Algorithm

2013 ◽  
Vol 291-294 ◽  
pp. 2154-2158
Author(s):  
Lei Zhang ◽  
Jun Liu
Keyword(s):  
Evolutionary Algorithm ◽  
Power Plants ◽  
Test System ◽  
Selection Strategy ◽  
Hybrid Evolutionary Algorithm ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
Output Constraints ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

Dynamic economic emission dispatch (DEED) is an important optimization task for power plants. The problem is a highly constrained multi-objective optimization problem involving conflicting objectives with both equality and inequality constraints. This paper introduces two objective functions of DEED model: the lowest generation cost and the smallest carbon emissions with power balance constraints, unit output constraints and unit ramp rate limits. Then the paper presents a multi-objective hybrid evolutionary algorithm (MHEA) to solve the DEED model. The MHEA is a hybrid optimization algorithm based on orthogonal initialization, improved differential operation with migration strategy, parameter adaptive control, multi-objective selection strategy and analytic hierarchy process based fuzzy technique (AFT). Numerical results of one test system demonstrate the capabilities of the proposed approach. Compared with other classical methods, the proposed approach gets better result.

scholarly journals Economic emission dispatch on unit commitment-based microgrid system considering wind and load uncertainty using hybrid MGWOSCACSA

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Bishwajit Dey ◽  
Biplab Bhattacharyya ◽  
Saurav Raj ◽  
Rohit Babu
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Unit Commitment ◽  
Search Algorithm ◽  
Test System ◽  
Grey Wolf Optimizer ◽  
Generation Cost ◽  
Sine Cosine Algorithm ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

Abstract Economic emission dispatch (EED) of a three-unit stand-alone microgrid system supported by a wind farm is percolated in this paper. The adverse effects of stochastic and uncertainty nature of wind energy in raising the generation cost of the microgrid system are studied in this article. Unit commitment (UC) of the generating units is taken into account which helps in reducing the generation cost and provides relaxation time to the generation units. Three cases are contemplated for the study. For the first two cases, the generation cost of the test system was minimized without and with the involvement of wind power, respectively. The third case considered the involvement of wind power along with the UC of the conventional generation units. A novel hybrid of recently developed superior optimization algorithms, viz. grey wolf optimizer (GWO), sine–cosine algorithm (SCA) and crow search algorithm (CSA), is implemented to perform EED, and the results are compared with basic GWO and other hybrid algorithms. Results are then analysed to compare and contrast among these cases and justify the reliable and profitable one. Statistical analysis claims the superiority of the proposed hybrid MGWOSCACSA over other hybrids and GWO.

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