scholarly journals Clean-development-mechanism-based optimal hydropower capacity design

2018 ◽  
Vol 20 (6) ◽  
pp. 1401-1418 ◽  
Author(s):  
Amir Hatamkhani ◽  
Hosein Alizadeh
Keyword(s):  
Optimal Design ◽  
Clean Development Mechanism ◽  
Thermal Power ◽  
Market Price ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Hydropower Project ◽  
Thermal Plant ◽  
Modelling Framework ◽  
Development Mechanism

Abstract This paper deals with optimal design of a hydropower project's capacity when an analyst may take into account different economic analysis approaches and considerations including market price method, alternative thermal power plant method, externalities and clean development mechanism (CDM). We formulate the problem using mixed-integer nonlinear programming including an economic objective function and governing hydropower constraints. Due to non-convexity of the program, we employ an effective simulation-optimization approach coupling particle swarm optimization (PSO) and Water Evaluation and Planning (WEAP) software which we customize for hydropower simulation using scripting capabilities of the software. The developed modelling framework is applied to the Karun II hydropower project in Iran, where we aim CDM-based optimal design of the project and also compare two economic hydropower analysis methods, i.e. market price and alternative thermal plant. Results show how inclusion of externality and CDM can affect the project's design and measures.

scholarly journals A Multi-Objective Approach toward Optimal Design of Sustainable Integrated Biodiesel/Diesel Supply Chain Based on First- and Second-Generation Feedstock with Solid Waste Use

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2261
Author(s):  
Evgeniy Ganev ◽  
Boyan Ivanov ◽  
Natasha Vaklieva-Bancheva ◽  
Elisaveta Kirilova ◽  
Yunzile Dzhelil
Keyword(s):  
Supply Chain ◽  
Optimal Design ◽  
Solid Waste ◽  
Second Generation ◽  
Agricultural Land ◽  
Optimization Problems ◽  
Biodiesel Production ◽  
Mixed Integer ◽  
Economic Criterion ◽  
Multi Objective

This study proposes a multi-objective approach for the optimal design of a sustainable Integrated Biodiesel/Diesel Supply Chain (IBDSC) based on first- (sunflower and rapeseed) and second-generation (waste cooking oil and animal fat) feedstocks with solid waste use. It includes mixed-integer linear programming (MILP) models of the economic, environmental and social impact of IBDSC, and respective criteria defined in terms of costs. The purpose is to obtain the optimal number, sizes and locations of bio-refineries and solid waste plants; the areas and amounts of feedstocks needed for biodiesel production; and the transportation mode. The approach is applied on a real case study in which the territory of Bulgaria with its 27 districts is considered. Optimization problems are formulated for a 5-year period using either environmental or economic criteria and the remainder are defined as constraints. The obtained results show that in the case of the economic criterion, 14% of the agricultural land should be used for sunflower and 2% for rapeseed cultivation, while for the environmental case, 12% should be used for rapeseed and 3% for sunflower. In this case, the price of biodiesel is 14% higher, and the generated pollutants are 6.6% lower. The optimal transport for both cases is rail.

scholarly journals Profit-Based Unit Commitment for a GENCO Equipped with Compressed Air Energy Storage and Concentrating Solar Power Units

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 576
Author(s):  
Mostafa Nasouri Gilvaei ◽  
Mahmood Hosseini Imani ◽  
Mojtaba Jabbari Ghadi ◽  
Li Li ◽  
Anahita Golrang
Keyword(s):  
Energy Storage ◽  
Solar Power ◽  
Unit Commitment ◽  
Thermal Power ◽  
System Structure ◽  
Compressed Air ◽  
Mixed Integer ◽  
Compressed Air Energy Storage ◽  
Concentrating Solar Power ◽  
Unit Commitment Problem

With the advent of restructuring in the power industry, the conventional unit commitment problem in power systems, involving the minimization of operation costs in a traditional vertically integrated system structure, has been transformed to the profit-based unit commitment (PBUC) approach, whereby generation companies (GENCOs) perform scheduling of the available production units with the aim of profit maximization. Generally, a GENCO solves the PBUC problem for participation in the day-ahead market (DAM) through determining the commitment and scheduling of fossil-fuel-based units to maximize their own profit according to a set of forecasted price and load data. This study presents a methodology to achieve optimal offering curves for a price-taker GENCO owning compressed air energy storage (CAES) and concentrating solar power (CSP) units, in addition to conventional thermal power plants. Various technical and physical constraints regarding the generation units are considered in the provided model. The proposed framework is mathematically described as a mixed-integer linear programming (MILP) problem, which is solved by using commercial software packages. Meanwhile, several cases are analyzed to evaluate the impacts of CAES and CSP units on the optimal solution of the PBUC problem. The achieved results demonstrate that incorporating the CAES and CSP units into the self-scheduling problem faced by the GENCO would increase its profitability in the DAM to a great extent.

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