Now showing 1 - 10 of 11
  • Publication
    Multi-objective planning model for integration of distributed generations in deregulated power systems
    (Shiraz University, 2010-01) ;
    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 effectiveness of the proposed model is demonstrated by applying it on a test distribution system and the results are presented, discussed and compared to other methods.
      380
  • Publication
    A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources
    This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models.
      835Scopus© Citations 107
  • Publication
    IGDT Based Robust Decision Making Tool for DNOs in Load Procurement Under Severe Uncertainty
    (Institute of Electrical and Electronics Engineers, 2013-06) ;
    This paper presents the application of Information Gap Decision Theory (IGDT) to help the Distribution Network Operators (DNOs) in choosing the supplying resources for meeting the demand of their customers. The three main energy resources are pool market, Distributed Generations (DGs) and the bilateral contracts. In deregulated environment, the DNO is faced with many uncertainties associated to the mentioned resources which may not have enough information about their nature and behaviors. In such cases, the classical methods like probabilistic methods or fuzzy methods are not applicable for uncertainty modeling because they need some information about the uncertainty behaviors like Probability Distribution Function (PDF) or their membership functions. In this paper, a decision making framework is proposed based on IGDT model to solve this problem. The uncertain parameters considered here, are as follows: price of electricity in pool market, demand of each bus and the decisions of DG investors. The robust strategy of DNO is determined to hedge him against the risk of increasing the total cost beyond what he is willing to pay. The effectiveness of the proposed tool is assessed and demonstrated by applying it on a test distribution network.
      818Scopus© Citations 134
  • Publication
    Hybrid immune-genetic algorithm method for benefit maximisation of distribution network operators and distributed generation owners in a deregulated environment
    (Institute of Engineering and Technology (IET), 2011-01) ; ; ;
    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 networks regarding the benefits of DNO and DGOs. The proposed model simultaneously optimises two objectives, namely the benefits of DNO and DGO and determines the optimal schemes of sizing, placement and specially the dynamics (i.e. timing) of investments on DG units and network reinforcements over the planning period. It also considers the uncertainty of electric load, electricity price and wind turbine power generation using the point estimation method. The effect of benefit sharing is investigated for steering the decisions of DGOs. An efficient two-stage heuristic method is utilised to solve the formulated planning problem and tested on a real large-scale distribution network.
      716Scopus© Citations 97
  • Publication
    Possibilistic evaluation of distributed generations impacts on distribution networks
    (Institute of Electrical and Electronic Engineers (IEEE), 2011-03-17) ; ; ;
    In deregulated power systems, the distribution network operator (DNO) is not responsible for investment in distributed generation (DG) units, and they are just concerned about the best architecture ensuring a good service quality to their customers. The investment and operating decisions related to DG units are then taken by entities other than DNO which are exposed to uncertainty. The DNO should be able to evaluate the technical effects of these uncertain decisions. This paper proposes a fuzzy evaluation tool for analyzing the effect of investment and operation of DG units on active losses and the ability of distribution network in load supply at presence of uncertainties. The considered uncertainties are related to load values, installed capacity, and operating schedule of DG units. The proposed model is applied on a test system and also a real French urban network in order to demonstrate its functionality in evaluating the distribution expansion options.
    Scopus© Citations 124  915
  • Publication
    A distribution network expansion planning model considering distributed generation options and techo-economical issues
    (Elsevier, 2010-08) ;
    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 demonstrated by various studies on an actual distribution network.
      785Scopus© Citations 101
  • Publication
    Imperialist competition algorithm for distributed generation connections
    (Institute of Engineering and Technology (IET), 2012) ;
    This study proposes an imperialist competition algorithm (ICA) to maximise the benefits of distribution network operators (DNOs) because of the existence of distributed generation (DG) units. The sum of active loss reduction and network investment deferral incentives has been considered as the objective function to be maximised in this study. The optimal location and size of DG units in the network are found considering various techno-economical issues. The application of the proposed methodology in the UK under current Ofgem financial incentives for DNOs is investigated. The ability of the proposed approach in finding the optimal solution is validated by comparing the obtained results with other methods of the literature.
      596Scopus© Citations 29
  • Publication
    A possibilistic-probabilistic tool for evaluating the impact of stochastic renewable and controllable power generation on energy losses in distribution networks - A case study
    (Elsevier, 2011-01) ;
    This paper proposes a hybrid possibilistic–probabilistic evaluation tool for analyzing the effect of uncertain power production of distributed generations (DGs) on active losses of distribution networks. The considered DG technologies are gas and wind turbines. This tool is useful for distribution network operators (DNOs) when they are faced with uncertainties which some of them can be modeled probabilistically and some of them are described possibilistically. The generation pattern of DG units changes the flow of lines and this will cause change of active losses which DNO is responsible for compensating it. This pattern is highly dependent on DG technology and also on decisions of DG operator which is an entity other than DNO. For wind turbines, this pattern is described using a weibull probability distribution function (PDF) for wind speed along with the power curve of the wind turbine but for other controllable DG technologies like gas turbines, it is not an easy job to provide a PDF to describe the generation schedule. On the other hand, the values of loads cannot be always described using a PDF so the possibilistic (fuzzy) description can be helpful in such cases. In order to demonstrate the effectiveness of the proposed tool, it is applied to a realistic distribution system and the results are analyzed and discussed.
      637Scopus© Citations 96
  • Publication
    A Probabilistic Modeling of Photo Voltaic Modules and Wind Power Generation Impact on Distribution Networks
    (Institute of Electrical and Electronics Engineers, 2011-01) ; ;
    The rapid growth in use of renewable intermittent energy resources, like wind turbines (WTs) and solar panels, in distribution networks has increased the need for having an accurate and efficient method of handling the uncertainties associated with these technologies. In this paper, the unsymmetrical two point estimate method (US2PEM) is used to handle the uncertainties of renewable energy resources. The uncertainty of intermittent generation of WT, photo voltaic cells, and also electric loads, as input variables, are taken into account. The variation of active losses and imported power from the main grid are defined as output variables. The US2PEM is compared to symmetrical two point estimate method, Gram-Charlier method, and Latin hypercube sampling method, where Monte Carlo simulation is used as a basis for comparison. The validity of the proposed method is examined by applying it on a standard radial 9-node distribution network and a realistic 574-node distribution network.
      1366Scopus© Citations 207
  • Publication
    Application of a Modified NSGA Method for Multi-Objective Static Distributed Generation Planning
    (Springer, 2011-08) ;
    The characteristics of integrating distributed generation (DG) in a distribution network have changed. These electrical resources are used as an alternative energy source to the main grid. The technical and economical benefits of such units are achieved only when they are optimally sized and placed in the network. In this paper, a static mixed integer non-linear model for distributed generation planning is defined and solved using a modified NSGA method (Non-dominated Sorting Genetic Algorithm). Different DG technologies are considered and the objective functions for minimization are defined as the total active loss, investment and operational costs, and environmental pollution. The method is applied to a test distribution network and the results are discussed in comparison with other methods.
      413Scopus© Citations 16