Bus Selection Research Articles

Intra-urban mobility: the place of para-transit operations in the ancient town of Ile-Ife, Nigeria

This study examined the effectiveness of para-transit transport activities by identifying the socioeconomic characteristics of both the passengers and drivers of public transport and the factors confronting their operation. It utilised primary and secondary data. A purposive sampling technique was employed which entailed the identification of all the motor parks, the selection of buses, minibuses and cars at the motor parks, major bus stops and conducting a survey using a structured questionnaire cum interview. Questionnaires were administered to 354 respondents to obtain information about their socioeconomic, trip characteristics and the unconventional public transport operations, of which a total of 312 questionnaires were duly completed and returned. Data collected were analysed using simple descriptive techniques and correlation analysis. The results showed that the majority of the passengers (61.4%) were within the 21 – 30 years age bracket while 43.7% of the drivers were within the 31-40 years age bracket, the patrons and the operators of the public transport are predominantly low-income earners as large proportion of the passengers (42.1%) earned below ₦10,000 per month while 46.9% of the drivers earned between ₦10,001 and ₦20,000 per month. The results of the correlation analysis indicated both the drivers’ and passengers’ perspectives, factors such as public transport conditions, road quality and drainage system are highly correlated between their paired variables. Hence, effort should be made by the government and public transport operators to improve the transport infrastructural facilities in the study area.

A slack-bus-independent loss sensitivity approach for optimal day-ahead generation scheduling

In a power system, the incurred transmission loss and the associated sensitivity factors are dependent on the selection of the slack bus and the dispatch. In this paper, a fast two-stage, hydro-thermal generation scheduling process, which is also inclusive of the system power loss, is proposed. A novel approach towards estimating power loss sensitivity factors is presented which is independent of the choice/location of the slack bus in the network. In addition to this, the approach identifies the loss incurred by the operation of different market players including the generation and distribution companies for penalizing. Mixed integer linear programming is used to model the said optimal day-ahead scheduling problem. The two-stage process employed is such that the first stage is applied only in the planning stage, while second is a fast responsive algorithm suitable for very short-term applications. A real network, Vietnam Power Grid, is used for testing this proposed approach, and the results obtained demonstrated that there is significant reduction in the electricity cost and total transmission loss.

The school bus routing problem with student choice: a bilevel approach and a simple and effective metaheuristic

AbstractThe school bus routing problem (SBRP) involves interrelated decisions such as selecting the bus stops, allocating the students to the selected bus stops, and designing the routes for transporting the students to the school taking into account the bus capacity constraint, with the objective of minimizing the cost of the routes. This paper addresses the SBRP when the reaction of students to the selection of bus stops is taken into account, that is, when students are allowed to choose the selected bus stop that best suits them. A bilevel optimization model with multiple followers is formulated, and its transformation into a single‐level mixed integer linear programming (MILP) model is proposed. A simple and effective metaheuristic algorithm is also developed to solve the problem. This algorithm involves solving four MILP problems at the beginning, which can be used to obtain tight upper bounds of the optimal solution. Extensive computational experiments on SBRP benchmark instances from the literature show the effectiveness of the proposed algorithm in terms of both the quality of the solution found and the required computing time.

STUDY ON DYNAMIC INFLUENCE OF PASSENGER FLOW ON INTELLIGENT BUS TRAVEL SERVICE MODEL

To improve the service quality and convenience of bus travel services, this paper proposes the Intelligent Bus Travel Service Model (IBTSM). The IBTSM makes it possible to provide a travel strategy considering every aspect of bus travel, specifically, delay in the peak period arising from limited carrying-capacities of buses. A three-step approach was executed toward implementing the IBTSM. First, the bus travel-time was predicted using Long Short-Term Memory (LSTM). Next, the crowding level in the bus was evaluated using a fuzzy expert system, based on which a reasonable start-off time was planned, and the delay caused by large passenger flow was circumvented. The k-Nearest Neighbours (k-NN) algorithm was used to provide input data of passenger flow. In this study, the correlation between passenger flow variation and bus services was investigated to extend the provisions of the travel strategy to include start-off time scheduling and target bus selection, rather than only bus running-time estimation. The proposed model was evaluated using a bus in China as a case study, and its reliability and positive impact on promoting both the quality of bus services and development of intelligent travel were demonstrated.

Planning multi-terminal direct current grids based graphs theory

Transmission expansion planning in AC power systems is well known and employs a variety of optimization techniques and methodologies that have been used in recent years. By contrast, the planning of HVDC systems is a new matter for the interconnection of large power systems, and the interconnection of renewable sources in power systems. Although the HVDC systems has evolved, the first implementations were made considering only the needs of transmission of large quantities of power to be connected to the bulk AC power system. However, for the future development of HVDC systems, meshed or not, each AC system must be flexible to allow the expansion of these for future conditions. Hence, a first step for planning HVDC grids is the planning and development of multi-terminal direct current (MTDC) systems which will be later transformed in a meshed system. This paper presented a methodology that use graph theory for planning MTDC grids and for the selection of connection buses of the MTDC to an existing HVAC transmission system. The proposed methodology was applied to the Colombian case, where the obtained results permit to migrate the system from a single HVDC line to a MTDC grid.

Optimal Load Shedding to Avoid Risks of Voltage Collapse Using Black Hole Algorithm

This paper proposes a novel methodology for the optimization of load shedding based on voltage-dependent load model accounting stability constraints using Black Hole (BH) optimization technique under emergency conditions. Line voltage stability index relation is derived for the selection of load bus. Load buses for load shedding are identified on the basis of large sensitivity of minimum value of line voltage stability index with respect to the system load. The load shedding has been optimized subject to stability constraints using BH algorithm. Testing of the developed algorithm has been done using IEEE 14, 25 and 118 bus power systems. The optimized results of the proposed algorithm have been compared on the basis of statistical inference with results obtained using well-established optimization techniques. Simulation results authenticate that the proposed methodology mitigates a considerable amount of load shedding and the system can be prevented from blackouts.

Candidate bus selection for dynamic VAR planning towards voltage stability enhancement considering copula‐based correlation of wind and load uncertainties

Candidate bus selection for dynamic VAR planning towards voltage stability enhancement considering copula‐based correlation of wind and load uncertainties

Secondary and Tertiary Voltage Control of a Multi-Region Power System

This paper presents techniques for the application of tertiary and secondary voltage control through the use of intelligent proportional integral derivative (PID) controllers and the wide area measurement system (WAMS) in the IEEE 39 bus system (New England system). The paper includes power system partitioning, pilot bus selection, phasor measurement unit (PMU) placement, and optimal secondary voltage control parameter calculations to enable the application of the proposed voltage control. The power system simulation and analyses were performed using the DIgSILENT and MATLAB software applications. The optimal PMU placement was performed in order to apply secondary voltage control. The tertiary voltage control was performed through an optimal power flow optimization process in order to minimize the active power losses. Two different methods were used to design the PID secondary voltage control, namely, genetic algorithm (GA) and neural network based on genetic algorithm (NNGA). A comparison of system performances using these two methods under different operating conditions is presented. The results show that NNGA secondary PID controllers are more robust than GA ones. The paper also presents a comparison between system performance with and without secondary voltage control, in terms of voltage deviation index and total active power losses. The graph theory is used in system partitioning, and sensitivity analysis is used in pilot bus selection, the results of which proved their effectiveness.

A cost-causal marginal participation method using min-max fairness for transmission services cost allocation

We consider the problem of fair allocation of the cost of a transmission system among load and generation entities using the marginal participation approach. We show that a cost-causal approach involving capacity-based line cost rate and a min-max fair economic slack bus selection for price-taking entities leads to a rigorously fair and more accurate implementation of marginal participation method. In the existing methods the counter-flows are masked, which is a compromise with fairness and linearity. However, if the counter-flows are incentivized then it can lead to pay-offs to some entities. The proposed approach solves the problem of pay-offs without masking the counter-flows. This is achieved by separation of the total transmission services cost into usage, reliability and residual capacity components. The allocation of the first two components is based on the min-max fairness policy, and the residual capacity costs are allocated on a pro-rata basis. Simulation results on multiple IEEE test systems, Indian utility power systems and extensive comparative evaluations for the contemporary methods demonstrate the claims made.

Implementation of Distributed Generation with Solar Plants in a 132 kV Grid Station at Layyah Using ETAP

Decentralized power generation efficaciously merges technological advances in a rapidly changing face of power networks introducing new power system components, advanced control, renewable sources, elegant communication, and web technology paving the way for the so called smart grids. Distributed generation technology lies at the intersection point of power systems, power electronics, control engineering, renewable energy, and communication systems which are not mutually exclusive subjects. Key features of renewable integration in a distribution network include loss minimization, voltage stability, power quality improvement, and low-cost consumption resulting from abundant natural resources such as solar or wind energy. In this research work, a case study has been carried out at a 132 kV grid station of Layyah, Pakistan, which has active losses, reactive losses, low power factor, low voltage on the demand side, and overloaded transformers and distribution lines. As a result, power outage issue is frequent on the consumer side. To overcome this issue, a simulation of load flow of this system is performed using the Newton-Raphson method due to its less computational time, fewer iterations, fast convergence, and independence from slack bus selection. It finds the harsh condition in which there were 23 overloaded transformers, 38 overloaded distribution lines, poor voltage profile, and low power factor at the demand side. There is a deficit of 24 MW in the whole system along with 4.58 MW active and 12.30 MVAR reactive power losses. To remove power deficiency, distributed generation using solar plants is introduced to an 11 kV distribution system with a total of 24 units with each unit having a capacity of 1 MW. Consequently, active and reactive power losses are reduced to 0.548 MW and 0.834 MVAR, respectively. Furthermore, the voltage profile improves, the power factor enhances, and the line losses reduce to a great extent. Finally, overloaded transformers and distribution lines also return to normal working conditions.

Electric Bus Selection with Multicriteria Decision Analysis for Green Transportation

Multicriteria decision-making tools are widely used in complex decision-making problems. There are also numerous points of decision-making in transportation. One of these decision-making points regards clean technology vehicle determination. Clean technology vehicles, such as electric buses, have some advantages compared to other technologies like internal combustion engine vehicles. Notably, electric vehicles emit zero tailpipe emissions, thereby ensuring cleaner air for cities and making these clean technologies preferable to other technologies, especially in highly populated areas for better air quality and more livable cities. In this study, we propose a multicriteria decision-making process using analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in the context of an electric bus in the center of Ankara. Six potential electric bus alternatives were evaluated under seven specific criteria. Overall, EV-2 electric buses outperformed other electric bus alternatives based on the chosen criteria. In addition, the stability of the results obtained under different scenarios using this method was established via sensitivity analysis.

Study of Selection of Bus Mode and Rail Train Surabaya – Malang

The need for transportation facilities and infrastructure that is quite large in the city of Surabaya to the city of Malang is the impact of population growth and increased activity in the city. To support economic, social, trade and education activities between the two cities, public transportation facilities are needed that can meet the needs of the community in terms of comfort and safety. Fulfillment of comfort factors in the use of public transportation such as cheap travel costs, speed of travel time, and accuracy of operational schedules, is expected to increase the interest of travelers to use public vehicles more often than private vehicles. The analysis method used, among others, Descriptive Analysis aims to identify the characteristics of users of the Surabaya-Malang and bus modes, then the Logistic Regression Analysis and Binomial Logit Difference Analysis aim to Obtain a model of selection of bus and train modes in the Surabaya-Malang route, then proceed Sensitivity Analysis which aims to determine the sensitivity of the model of the response of the traveler in determining the choice if there is a change in each attribute of the trip. The results of logistic regression analysis and binomial logit difference, it can be concluded that, attribute / variable X2 (travel time) is the attribute / variable that most influences the mode selection. The sensitivity analysis results can be concluded as follows: Sensitivity to travel costs, the possibility of respondents prefer to use the train mode is greater than the bus. Sensitivity to time, the possibility of respondents prefer to use the train mode is greater than the bus. Sensitivity to the departure schedule (headway), the possibility of respondents choosing to use the train mode will be greater than the bus, if the difference in the headway is between 90-165 minutes. However, if the difference in headway is above 165 minutes, then the respondent will switch to choosing the bus mode.

A Stochastic Multi-Objective Approach to Pilot Bus Selection for Secondary Voltage Regulation

This letter presents a multi-objective probabilistic model for the optimal selection of pilot buses in secondary voltage regulation (SVR) of transmission grids. The pilot-bus selection (PS) problem is formulated in the form of a stochastic multi-objective optimization problem (SMOP). The resultant SMOP is solved toward the non-dominated sorting genetic algorithm (NSGA-II) together with a fuzzy set theory. The applicability of the proposed PS model is examined on a classical test system as well as a practical transmission grid.

Road Test-Based Electric Bus Selection: A Case Study of the Nanjing Bus Company

Globally, the use of electric vehicles, and in particular the use of electric buses, has been increasing. The city of Nanjing leads China in the adoption of electric buses, supported by city policies and infrastructure. To lower costs and provide a better service, vehicle selection is crucial, however, existing selection methods are limited. Accordingly, Nanjing Bus Company developed a test method based on road tests to select a bus. This paper presents a detailed description of the test method and a case study of its application. The method included an organization structure, selection of eight test vehicles (four 10 m length, four 8 m length) from four brands (a total of 32 test vehicles), selection of indicators and selection of routes. Data was collected from repeated drives by 65 drivers over an 8-week period. Indicators included power consumption, charging duration, failure duration and driving distance. It is concluded that the road test method designed and conducted by the Nanjing Bus Company provides a good framework for the selection of pure electric buses. Furthermore, subsequent experience with selected buses supports the validity and value of the model.

Zoning‐based candidate bus selection for dynamic VAR planning in power system towards voltage resilience

Dynamic VAR planning for voltage stability enhancement is a challenging topic for power systems with a growing penetration level of wind power. As a critical step of VAR planning, candidate bus selection (CBS) can reduce the scale of the problem and improve the optimality of the planning decisions. This study proposes a new zoning-based CBS method towards multiple voltage resilience indices. First, a set of resilience-oriented metrics are proposed to comprehensively evaluate voltage performance in pre-contingency and post-contingency stages, considering the extent of the voltage deviation and voltage recovery time, as well as the post-contingency steady-state voltage profile. Then, a zoning-based approach is developed based on fuzzy C-means clustering and Morris screening to categorise buses into different zones with capacity sensitivity analysis. Finally, a comprehensive multi-objective CBS scheme is proposed for voltage resilience enhancement. Simulation results show that, compared with conventional approaches, the method can achieve more voltage stability improvement with the fewer or the same number of candidate buses.

Evaluation Method to Select Pure Electric Buses Based on Road Operation Tests

In China, the development of pure electric buses is an essential means to address energy and environmental concerns. Proper evaluation and selection of pure electric buses is a crucial step prior to introducing the buses into actual operation. This paper presents a multi-objective method for the selection of pure electric buses based on road driving tests. An index system for evaluating the operating performance through the fuzzy analytic hierarchy process is established, and to ensure the method is more systematic than those in previous studies, indicators are classified into three categories: qualitative, semi-qualitative and quantitative indicators, of which the nineteen indexes have been comprehensively considered and designed. To verify the advantage of the evaluation method proposed in the article, two typical buses were selected as the assessed objectives regarding reliability, economic, security, environmental adaptability, etc. The assessing process indicates that the method is easily implemented and of high practical value. Additionally, the results show satisfactory agreement with the actual scenario. Thus, it can be assumed that the method detailed herein provides a basis for the design, selection, and evaluation of pure electric buses.

Operational‐based techno‐economic PMU installation approach using grey wolf optimisation algorithm (GWOA)

Phasor measurement units (PMUs) are currently the most useful devices to obtain fast, precise, and synchronised measurement data. Owing to the high cost of installation, the minimum number of PMUs required for the full observability of a network must be determined. However, power companies do not consider such optimal PMU installation (OPI), because their main concerns are preventing cascaded tripping and secure grid separation, for which critical buses (CBs) should be prioritised for direct observability. In practice, utility grids (UGs) may lose their full observability status during islanding, which the OPI problem should account for. On the other hand, actual bus-to-bus variations in the PMU installation cost are not properly addressed in the PMU installation problem. Considering these practical aspects, an operational-based multiphase PMU installation approach is proposed here using the grey wolf optimisation algorithm for CB prioritisation. A PMU cost minimisation-based OPI problem that considers the full observability of each UG during islanding is formulated. To determine quality outputs, logical and unique mathematical equations are developed. A novel multiple bus selection approach is proposed for a phase-wise bus assortment. The results of the proposed algorithm are compared with those of other existing methods.

Multi-Objective Optimal STATCOM Allocation for Voltage Sag Mitigation

Voltage sags mitigation has become a significant concern for utilities due to the pressure from both customers and regulators recently. This paper proposes a novel multi-objective optimization formulation for STATCOM allocation problem to mitigate voltage sags. The allocation of STATCOM is formulated as a multi-objective optimization problem (MOP) with two conflicting objectives including the voltage sag performance and annual investment costs of STATCOM. To analytically evaluate the voltage sag performance in the optimization process, a mathematical voltage sag profile calculation model of power system with multiple STATCOMs is proposed and solved by nonlinear programming method. System Average RMS Variation Frequency index-X index is chosen to quantify the voltage sag performance for optimization. Sensitivity-based candidate bus selection is also performed as an essential step to reduce problem size. An improved multi-objective evolutionary algorithm (MOEA) called SPEA2+SDE (Strength Pareto Evolutionary Algorithm with shifting density estimation) is utilized to solve the proposed MOP model, so a set of Pareto optimal STATCOM allocations for voltage sag mitigation can be derived demonstrating the trade-off between two objectives and better supporting the decision-making. IEEE 30-bus system and IEEE 118-bus system are tested to demonstrate the effectiveness and feasibility of proposed method.

Uncertainty modeling for bus selection and allocation in a private transportation system

ABSTRACTThis paper describes the development of a probabilistic formulation that provides global optimum selection and allocation of a fleet of buses in a private transportation system of an organization where a third party is hired to provide transportation for its employees and their dependents. In this private transportation system, a fleet of buses is to be selected and allocated to serve employees and their independents on different prescheduled trips along different routes from the organization’s headquarters and residential compound where round-trip times of scheduled trips are subject to uncertainty due to random delays. We propose a probabilistic approach based on 0-1 integer programming for the selection and allocation to determine the optimal number and size of buses assigned to a set of prescheduled trips in a particular time interval. Examples and a case study are presented to illustrate the applicability and suitability of the proposed approach.

An investigation on apportion of mathematical loss in transmission loss/cost allocation approach

<p>Cost allocation of highly non-linear transmission loss is complex and essential in competitive electricity market. In most of the existing transmission loss/cost allocation approaches, real power loss depends on selection of slack bus and hence the cost of transmission losses which are allocated to the generators and the loads also varies. In this paper, a complete analysis on the impact of slack bus selection on transmission loss allocation with and without mathematical loss is made. One of the existing approaches, proportional generation and proportional load (PGPL) method is taken to illustrate the impact. Mathematical loss is the loss without generation and load in the network and can be obtained from power flow solution by taking generation and load as zero. The cost incurred for this mathematical loss is allocated to the transmission lines while the cost of transmission loss due to bilateral contracts is allocated among the sources and the consumers. These loss/cost allocations with and without considering mathematical loss is shown using an IEEE 30 bus, 57 bus, 75 bus and 118 bus systems. The simulation results are obtained using MATLAB R2014a.<em></em></p>