Showing 10 results for Planning
H. Abdi, M. Parsa Moghaddam, M. H. Javidi,
Volume 1, Issue 3 (7-2005)
Abstract
Restructuring of power system has faced this industry with numerous
uncertainties. As a result, transmission expansion planning (TEP) like many other problems
has become a very challenging problem in such systems. Due to these changes, various
approaches have been proposed for TEP in the new environment. In this paper a new
algorithm for TEP is presented. The method is based on probabilistic locational marginal
price (LMP) considering electrical loss, transmission tariffs, and transmission congestion
costs. It also considers the load curtailment cost in LMP calculations. Furthermore, to
emphasize on competence of competition ability of the system, the final plan(s) is (are)
selected based on minimization of average of total congestion cost for transmission system.
T. Barforoushi, M. P. Moghaddam, M. H. Javidi, M. K. Sheik-El-Eslami,
Volume 2, Issue 2 (4-2006)
Abstract
Medium-term modeling of electricity market has essential role in generation
expansion planning. On the other hand, uncertainties strongly affect modeling and
consequently, strategic analysis of generation firms in the medium term. Therefore, models
considering these uncertainties are highly required. Among uncertain variables considered
in the medium term generation planning, demand and hydro inflows are of the greatest
importance. This paper proposes a new approach for simulating the operation of power
market in medium-term, taking into account demand and hydro inflows uncertainties. The
demand uncertainty is considered using Monte-Carlo simulations. Standard Deviation over
Expected Profit (SDEP) of generation firms based on simulation results is introduced as a
new index for analyzing the influence of the demand uncertainty on the behavior of market
players. The correlation between capacity share of market players and their SDEP is also
demonstrated. The uncertainty of inflow as a stochastic variable is dealt using scenario tree
representation. Rational uncertainties as strategic behavior of generation firms, intending to
maximize their expected profit, is considered and Nash-Equilibrium is determined using the
Cournot model game. Market power mitigation effects through financial bilateral contracts
as well as demand elasticity are also investigated. Case studies confirm that this
representation of electricity market provides robust decisions and precise information about
electricity market for market players which can be used in the generation expansion
planning framework.
S. Najafi Ravadanegh,
Volume 10, Issue 1 (3-2014)
Abstract
Optimal distribution substation placement is one of the major components of optimal distribution system planning projects. In this paper optimal substation placement problem is solved using Imperialist Competitive Algorithm (ICA) as a new developed heuristic optimization algorithm. This procedure gives the optimal size, site and installation time of medium voltage substation, using their related costs subject to operating and optimization constraints. A multistage and pseudo-dynamic expansion planning is applied to consider dynamic of the system parameters for example, load forecasting uncertainty, asset management and geographical constraints. In order to evaluate the effectiveness of the proposed method a sensitivity analysis of ICA parameters on obtained results is done. A graphical representation of obtained results is used to show the efficiency and capability of the proposed method both from the planning view and graphical aspects. The results show the efficiency and capability of the proposed method which has been tested on a real size distribution network.
H. Rajabi Mashhadi, M. A. Armin,
Volume 11, Issue 3 (9-2015)
Abstract
Utilization of wind turbines as economic and green production units, poses new challenges to the power system planners, mainly due to the stochastic nature of the wind, adding a new source of uncertainty to the power system. Different types of distribution and correlation between this random variable and the system load makes conventional method inappropriate for modeling such a correlation. In this paper, the correlation between the wind speed and system load is modeled using Copula, a mathematical tool recently used in the field of the applied science. As the effect of the correlation coefficient is the main concern, the copula modeling technique allows simulating various scenarios with different correlations. The conducted simulations in this paper reveals that the wind speed correlation with the load has significant effect on the system reliability indices, such as expected energy not served (EENS) and loss of load probability (LOLP). Moreover, in this paper the effect of the correlation coefficient on the effective load carrying capability (ELCC) of the wind turbines is analyzed, too. To perform the aforementioned simulations and analyses, the modified RBTS with an additional wind farm is used.
H. Kiani Rad, Z. Moravej,
Volume 15, Issue 3 (9-2019)
Abstract
In this paper, a new method is conducted for incorporating the forecasted load uncertainty into the Substation Expansion Planning (SEP) problem. This method is based on the fuzzy clustering, where the location and value of each forecasted load center is modeled by employing the probability density function according to the percentage of uncertainty. After discretization of these functions, the location and value of each of the new load centers are determined based on the presented fuzzy clustering based algorithm. A Genetic Algorithm (GA) is used to solve the presented optimization problem in which the allocations and capacities of new substations as well as the expansion requirements for the existing ones are determined. With the innovative presented method, the impact of uncertainty of the power and location of the predicted loads on the results of SEP is measured, and finally, it is possible to make a proper decision for the SEP. The significant features of this method can be outlined as its applicability to large-scale networks, robustness to load changes, the comprehensiveness and also, the simplicity of applying this method to various problems. The effectiveness of proposed method is demonstrated by application on a real sub-transmission system.
H. Shayeghi, Y. Hashemi,
Volume 17, Issue 3 (9-2021)
Abstract
The main idea of this paper is proposing a model to develop generation units considering power system stability enhancement. The proposed model consists of two parts. In the first part, the indexes of generation expansion planning are ensured. Also, small-signal stability indexes are processed in the second part of the model. Stability necessities of power network are supplied by applying a set of robustness and performance criteria of damping. Two parts of the model are formulated as two-objective function optimization that is solved by adaptive non-dominated sorting genetic method-III (ANSGM-III). For better decision-making of the final solution of generation units, a set of Pareto-points have been extracted by ANSGM-III. To select an optimal solution among Pareto-set, an analytical hierarchy style is employed. Two objective functions are compared and suitable weights are allocated. Numerical studies are carried out on two test systems, 68-bus and 118-bus power network. The values of generation expansion planning cost and system stability index have been studied in different cases and three different scenarios. Studies show that, for example, in the 68-bus system for the case of system load growth of 5%, the cost of generation expansion planning for the proposed model increased by 7.7% compared to the previous method due to stability modes consideration and the small-signal stability index has been improved by 6.7%. The proposed model is survived with the presence of a wide-area stabilizer (WAS) for damping of oscillations. The effect of WAS latency on expansion programs is evaluated with different amounts of delay times.
T. Barforoushi, R. Heydari,
Volume 18, Issue 2 (6-2022)
Abstract
Curtailment of the production of wind resources due to uncertainty can affect the expansion of the transmission networks. The issue that needs to be addressed is how to expand the transmission network, which is accompanied by increasing wind energy utilization. In this paper, a new framework is proposed to solve the transmission expansion planning (TEP) problem in the presence of wind farms, considering wind curtailment cost. The proposed model is a risk-constrained stochastic bi-level problem that, the difference between the expected social welfare and investment cost is maximized at the upper level where optimal decisions on expansion plans are adopted by the independent system operator (ISO). To make the best use of wind generation resources, a new term called wind power curtailment cost is added to the upper level. Also, the risk index is included in expansion decisions. The market-clearing is considered at the lower level, aiming at maximizing social welfare. Uncertainties relating to wind power and the forecasted demand are modeled by sets of scenarios. Using duality theory, the proposed framework is modeled as mixed-integer linear programming (MILP) problem. The model is examined using the classical Garver’s six-bus test system and the IEEE 24-bus reliability test system (RTS). The results show that by considering the wind curtailment cost, the transmission network is expanded in a way that increases the wind energy utilization factor from 92.05% to 95.17%.
P. Paliwal,
Volume 18, Issue 4 (12-2022)
Abstract
This paper presents a multi-stage planning framework for analysis of stochastic distributed energy resources (DERs) comprising of solar, wind, and battery storage. The existing models do not consider penetration level analysis in conjunction with sizing, placement, and economic assessment. The main objective of this research is to embed all these dimensions of system planning in one structure. The first stage involves reliability constrained component sizing. The second stage pertains to placement of DERs based on loss minimization and voltage profile. The third stage is the main thrust of this work which provides exhaustive economic evaluation and cost-benefit analysis. The novelty of this work lies in the consideration of penetration level in backdrop of all three stages. The proposed formulation is implemented on a 33-Bus radial distribution feeder located in Jaisalmer, Rajasthan, India. Four penetration levels viz. 10, 20, 40, and 60 percent have been investigated and analyzed under different planning scenarios. The results facilitate the determination of optimum penetration level.
N. Thakkar, P. Paliwal,
Volume 18, Issue 4 (12-2022)
Abstract
In the last decade, there has been a lot of focus on sustainable development in the electrical power industry to meet the growing energy demand. This has led to an increase in the integration of renewable energy sources (RES). In addition to being abundantly available, the RES offers advantages such as low environmental impact and increased social development of rural communities which are imperative for a sustainable society. However, the selection of a particular generating resource or resource mix (RM) for an autonomous micro-grid is a complex problem that involves multiple conflicting factors. In this paper, a planning strategy for selecting an appropriate RM has been proposed. Seven RMs comprising different combinations of four generation/storage technologies such as solar photovoltaic array (SPVA), wind turbine (WT), diesel generator (DG) and battery storage (BS) have been considered. The planning is initiated with the determination of optimal component sizing for all seven RMs. The RMs are then analyzed with respect to four primary sustainability parameters i.e. economic, social, technical and environmental. The analysis is further enhanced by investigation of 13 sub-parameters as well. Thereafter, prioritization of RMs is carried out using two MCDM methods: Best worst method (BWM) and PROMETHEE II. Finally, to assert the importance of weight assignment on RM ranking, sensitivity analysis is performed. In order to impart the practical aspect to analysis, the planning formulation is applied to a case study of the Thar desert, India. The results suggest that a combination of SPVA and BS provides the most optimum RM solution.
Majid Golkhatab, Aref Shahmansoorian, Mohsen Davoudi,
Volume 21, Issue 4 (11-2025)
Abstract
This paper presents a novel hybrid navigation approach for autonomous mobile robots in obstacle-rich environments. The method integrates artificial potential fields for obstacle avoidance with fuzzy logic for path planning, which is optimized by a genetic algorithm to enhance adaptability and robustness to sensor uncertainties. Experimental results demonstrate significant improvements over traditional artificial potential field methods and are validated through real-time implementation on a ROS-based mobile robot.
