Power Economic Dispatch Problems Considering Prohibited Operating Zones and Spinning Reserve: A Hybrid Differential Evolution

2012 ◽  
Vol 229-231 ◽  
pp. 2701-2707
Author(s):  
Chao Lung Chiang
Keyword(s):  
Differential Evolution ◽  
Economic Dispatch ◽  
Inequality Constraints ◽  
Small Population ◽  
Computational Results ◽  
Fuel Cost ◽  
Spinning Reserve ◽  
Prohibited Operating Zones ◽  
Equality And Inequality Constraints ◽  
Power Economic

This paper proposes a hybrid differential evolution (HDE) for power economic dispatch (PED) considering units with prohibited operating zones (POZ) and spinning reserve. The HDE equipped with an accelerated operation and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the equality and inequality constraints of the system. To show the advantages of the proposed algorithm, one example is investigated, and the computational results of the proposed method are compared with that of the previous methods. The proposed approach integrates the HDE and the MU, revealing that the proposed approach has the following merits - ease of implementation; applicability to non-convex fuel cost functions; better effectiveness than previous methods; better efficiency than differential evolution with the MU (DE-MU), and the requirement for only a small population in applying the optimal PED problem of generators with POZ and spinning reserve.

Hybrid Differential Evolution Based Multi-Objective Approach for Hydrothermal Power Systems

2012 ◽  
Vol 212-213 ◽  
pp. 1009-1014 ◽  
Author(s):  
Chao Lung Chiang
Keyword(s):  
Power Systems ◽  
Differential Evolution ◽  
Inequality Constraints ◽  
Small Population ◽  
Previous Method ◽  
Fuel Cost ◽  
Emission Level ◽  
Multi Objective ◽  
Equality And Inequality Constraints ◽  
Emission Dispatch

This paper develops a hybrid differential evolution based multi-objective approach for the optimal economic emission dispatch (EED) of the hydrothermal power system (HPS), considering non-smooth fuel cost and emission level functions. The hybrid differential evolution (HDE) equipped with an accelerated operation and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the equality and inequality constraints of the HPS, and the ε-constraint technique is employed to manage the multi-objective problem. To show the advantages of the proposed algorithm, one example addressing the best compromise is applied to test the EED problem of the HPS. The proposed approach integrates the HDE, the MU and the ε-constraint technique, revealing that the proposed approach has the following merits - ease of implementation; applicability to non-smooth fuel cost and emission level functions; better effectiveness than the previous method; better efficiency than differential evolution (DE) with the MU (DE-MU), and the requirement for only a small population in applying the optimal EED problem of the HPS.

Improved Differential Evolution for Combined Heat and Power Economic Dispatch

2016 ◽  
Vol 17 (2) ◽  
pp. 151-163 ◽  
Author(s):  
C. Jena ◽  
M. Basu ◽  
C. K. Panigrahi
Keyword(s):  
Differential Evolution ◽  
Economic Dispatch ◽  
Solution Process ◽  
Random Variable ◽  
Combined Heat And Power ◽  
Efficient Global Optimization ◽  
Search Efficiency ◽  
Mutation Process ◽  
Prohibited Operating Zones ◽  
Power Economic

Abstract This paper presents an improved differential evolution to solve non-smooth non-convex combined heat and power economic dispatch (CHPED) problem. Valve-point loading and prohibited operating zones of conventional thermal generators are taken into account. Differential evolution (DE) exploits the differences of randomly sampled pairs of objective vectors for its mutation process. Consequently the variation between vectors will outfit the objective function toward the optimization process and therefore provides efficient global optimization capability. However, although DE is shown to be precise, fast as well as robust, its search efficiency will be impaired during solution process with fast descending diversity of population. This paper proposes Gaussian random variable instead of scaling factor which improves search efficiency. The effectiveness of the proposed method has been verified on four test systems. The results of the proposed approach are compared with those obtained by other evolutionary methods. It is found that the proposed improved differential evolution based approach is able to provide better solution.

Immune-Based Algorithm for Power Economic Emission Dispatch

2013 ◽  
Vol 470 ◽  
pp. 785-789 ◽  
Author(s):  
Chao Lung Chiang
Keyword(s):  
Immune System ◽  
Artificial Immune System ◽  
Inequality Constraints ◽  
Small Population ◽  
Previous Method ◽  
Fuel Cost ◽  
Artificial Immune ◽  
Emission Level ◽  
Equality And Inequality Constraints ◽  
Emission Dispatch

This paper proposes an artificial immune system for the economic environmental dispatch (EED) of the hydrothermal power system (HPS), considering non-smooth fuel cost and emission level functions. The artificial immune system (AIS) equipped with an accelerated operation and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to handle the equality and inequality constraints of the HPS, and the ε-constraint technique is employed to manage the constraints of HPS. To show the advantages of the proposed algorithm, one example addressing the best compromise is applied to test the EED problem of the HPS. The proposed algorithm integrates the AIS, the MU and the ε-constraint technique, revealing that the proposed approach has the following merits – 1)ease of implementation; 2)applicability to non-smooth fuel cost and emission level functions; 3)better effectiveness than the previous method, and 4)the requirement for only a small population in applying the optimal EED problem of the HPS.

scholarly journals Multiple Fuel Machines Power Economic Dispatch Using Stud Differential Evolution

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1393 ◽  
Author(s):  
Naila ◽  
Shaikh Haroon ◽  
Shahzad Hassan ◽  
Salman Amin ◽  
Intisar Sajjad ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Economic Dispatch ◽  
Power Economic

Implementation of Smooth and Non-Smooth Fuel Cost Function for Economic Load Dispatch using Cuckoo Search Method

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Apurva Gautam ◽  
Anupam Masih
Keyword(s):  
Cost Function ◽  
Power Plants ◽  
Search Algorithm ◽  
Inequality Constraints ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Economic Load Dispatch ◽  
Fuel Cost ◽  
Practical Applications ◽  
Equality And Inequality Constraints

Economic Load Dispatch (ELD) is an important topic in the operation of power plants which can help to build up effecting generating management plans. The ELD problem has no smooth cost function with equality and inequality constraints which make it difficult to be effectively solved. The paper presents an application of Cuckoo Search Algorithm (CSA) to solve Economic Load Dispatch (ELD) problems with smooth and non-smooth fuel cost objective functions. Main objective of ELD is to determine the most economic generating dispatch required to satisfy the predicted load demands including line losses over a certain period of time while relaxing various equality and inequality constraints. The unit Min/Max operational constraints, effects of valve-point loading ripples and line losses are considered for the practical applications. This paper describes the implementation of smooth and non smooth fuel cost function by CSA Method and its comparison with BAT method. We have used 6 and 12 bus system for calculating their total fuel cost.

Hybrid Differential Evolution Harmony Search Algorithm for Power Economic Dispatch Problems

2013 ◽  
Vol 415 ◽  
pp. 345-348
Author(s):  
Hong Gang Xia ◽  
Qing Zhou Wang
Keyword(s):  
Differential Evolution ◽  
Recent Literature ◽  
Search Algorithm ◽  
Economic Dispatch ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
System Experiment ◽  
Mutagenic Factor ◽  
Key Parameter ◽  
Power Economic

In this paper, a hybrid differential evolution harmony search (HDEHS) algorithm was presented for solving power economic dispatch problems. In this algorithm, mutation and crossover operation instead of harmony memory consideration and pitch adjustment operation, this improved the algorithm convergence rate. Moreover, dynamically adjust the key parameter (e.g. mutagenic factor F, crossover rate CR) to balance the local and global search. Based on a 13 units power system experiment simulations, the HDEHS has demonstrated stronger convergence and stability than original harmony search (HS) algorithm and its three improved algorithms (IHS, GHS and NGHS) that reported in recent literature.

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