Search for: multiobjective-models
Article International Journal of Electrical Power and Energy Systems ; Volume 43, Issue 1 , 2012 , Pages 1094-1105 ; 01420615 (ISSN) ; Ehsan, M ; Fattahi Meyabadi, A ; Sharif University of Technology
This paper presents a dynamic multi objective model for distribution network expansion, considering the distributed generators (DGs) and network reinforcements. The proposed model simultaneously optimizes three objective functions namely, total cost, emission cost and technical satisfaction (voltage profile) by finding the optimal schemes of timing, sizing, placement and DG technologies in a long term planning period (dynamic planning). The importance of each objective function can be changed in the interactive steps. The calculation algorithm is based on Chaotic Local Search with Modified Honey Bee Mating Optimization (CLSMHBMO). The effectiveness of the proposed model and the calculation...
Probabilistic dynamic multi-objective model for renewable and non-renewable distributed generation planning, Article IET Generation, Transmission and Distribution ; Volume 5, Issue 11 , 2011 , Pages 1173-1182 ; 17518687 (ISSN) ; Caire, R ; Hadjsaid, N ; Ehsan, M ; Sharif University of Technology
This study proposes a probabilistic dynamic model for multi-objective distributed generation (DG) planning, which also considers network reinforcement at presence of uncertainties associated with the load values, generated power of wind turbines and electricity market price. Monte Carlo simulation is used to deal with the mentioned uncertainties. The planning process is considered as a two-objective problem. The first objective is the minimisation of total cost including investment and operating cost of DG units, the cost paid to purchase energy from main grid and the network reinforcement costs. The second objective is defined as the minimisation of technical risk, including the probability...
Hybrid immune-genetic algorithm method for benefit maximisation of distribution network operators and distributed generation owners in a deregulated environment, Article IET Generation, Transmission and Distribution ; Volume 5, Issue 9 , 2011 , Pages 961-972 ; 17518687 (ISSN) ; Ehsan, M ; Caire, R ; Hadjsaid, N ; Sharif University of Technology
In deregulated power systems, distribution network operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components. The event of distributed generation (DG) has introduced new challenges to these distribution networks. The role of DG units must be correctly assessed to optimise the overall operating and investment cost for the whole system. However, the distributed generation owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This study presents a long-term dynamic multi-objective model for planning of distribution...
Article IEEE Transactions on Power Systems ; Volume 26, Issue 1 , May , 2011 , Pages 470-478 ; 08858950 (ISSN) ; Hosseini, S. H ; Oloomi Buygi, M ; Shahidehpour, M ; Sharif University of Technology
The unbundling of the electricity industry introduced new uncertainties and escalated the existing ones in transmission expansion planning. In this paper, a multi-stage transmission expansion methodology is presented using a multi-objective optimization framework with internal scenario analysis. Total social cost (TSC), maximum regret (robustness criterion), and maximum adjustment cost (flexibility criterion) are considered as three optimization objectives. Uncertainties are considered by defining a number of scenarios. To overcome the difficulties in solving the nonconvex and mixed integer optimization problem, the genetic-based Non-dominated Sorting Genetic Algorithm (NSGA II) is used....
A distribution network expansion planning model considering distributed generation options and techo-economical issues, Article Energy ; Volume 35, Issue 8 , 2010 , Pages 3364-3374 ; 03605442 (ISSN) ; Ehsan, M ; Sharif University of Technology
This paper presents a dynamic multi-objective model for distribution network expansion, considering the distributed generations as non-wire solutions. The proposed model simultaneously optimizes two objectives namely, total costs and technical constraint satisfaction by finding the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on DG units and/or network reinforcements over the planning period. An efficient heuristic search method is proposed to find non-dominated solutions of the formulated problem and a fuzzy satisfying method is used to choose the final solution. The effectiveness of the proposed model and search method are assessed and...
Multi-objective planning model for integration of distributed generations in deregulated power systems, Article Iranian Journal of Science and Technology, Transaction B: Engineering ; Volume 34, Issue 3 , 2010 , Pages 307-324 ; 10286284 (ISSN) ; Ehsan, M ; Sharif University of Technology
This paper presents a long-term dynamic multi-objective model for distributed generation investment. The proposed model optimizes three objectives, namely active losses, costs and environmental emissions and determines the optimal schemes of sizing, sitting of DG units and specially the dynamics of investment over the planning period. The Pareto optimal solutions of the problem are found using a GA algorithm and finally a fuzzy satisfying method is applied to select the optimal solution considering the desires of the planner. The solutions of Pareto optimal front are analyzed to extract general useful information for planners about the appropriate DG technologies and placement schemes. The...