Unit Dispatch Research Articles

Design and Development of ER MineTracer: A Mobile Emergency Response Application for Mining Industry

Most of the industries, especially mining companies, are facing nowadays an exciting future with growing demand as well as severe challenges. Several innovations in technology as well as in the organizational process and methods are developed in order to cope with the continuously advancing technologically-driven society and to address pressing issues that industries are facing, including emergency response-related problems. This study aimed to improve information access by developing ER MineTracer mobile emergency response application which combines web and mobile applications designed for reporters and rescuers in responding to employees’ emergency requests. It uses GPS to determine an employee’s current position and communicates the user’s name and present location straight to a web application installed in a command center for quick dispatching of emergency units. Descriptive-developmental research was employed in the study utilizing an object-oriented modeling tool in designing the ER MineTracer mobile application. Thirty (30) participants were purposefully chosen to assess the performance of the system and it was revealed that the developed ER MineTracer mobile application was efficient in terms of accessibility, accuracy, and usability. Hence, it is recommended to utilize ER MineTracer and optimize smartphones to assist individuals in saving lives during emergencies and accidents, especially in mining industries.

Achieving Sustainability and Cost-Effectiveness in Power Generation: Multi-Objective Dispatch of Solar, Wind, and Hydro Units

In the power system, economic power dispatch is a popular and fundamental optimization problem. In its classical form, this problem only considers thermal generators and does not take into account network security constraints. However, other forms of the problem, such as economic emission dispatch (EED), are becoming increasingly important due to the emphasis on minimizing emissions for environmental purposes. The integration of renewable sources, such as solar, wind, and hydro units, is an important aspect of EED, but it can be challenging due to the stochastic nature of these sources. In this study, a multi-objective algorithm is developed to address the problem of economic emission power dispatch with the inclusion of these renewable sources. To account for the intermittent behavior of solar, wind, and hydro power, the algorithm uses Lognormal, Weibull, and Gumbel distributions, respectively. The algorithm also considers voltage limitations, transmission line capacities, prohibited areas of operation for thermal generator plants, and system restrictions. The multi-objective real coded non-dominated sorting genetic algorithm II (R-NSGA-II) is applied to the problem and includes a procedure for handling system restrictions to meet system limitations. Results are extracted using fuzzy decision-making and are analyzed and discussed. The proposed method is compared to other newer techniques from another study to demonstrate its robustness. The results show that the proposed method despite being older is cost-significant while maintaining the same or lower emissions. These results were observed consistently and did not happen by chance, detailed explanation of why and how is discussed.

Economic Evaluation of a Mobile Stroke Unit Service in Germany.

Lower global disability and higher quality of life among ischemic stroke patients was found to be associated with the dispatch of mobile stroke units (MSUs) among patients eligible for recanalizing treatments in the Berlin_Prehospital Or Usual Delivery of stroke care (B_PROUD) study. The current study assessed the cost-utility and cost-effectiveness of additional MSU dispatch using data from this prospective, controlled, intervention study. Outcomes considered in the economic evaluation included quality-adjusted life years (QALYs) derived from the 3-level version of EQ-5D (EQ-5D-3L) and modified Rankin Scale (mRS) scores for functional outcomes 3-months after stroke. Costs were prospectively collected during the study by the MSU provider (Berlin Fire Brigade) and the B_PROUD research team. We focus our results on the societal perspective. As we aimed to determine the economic consequences of the intervention beyond the study's follow-up period, both care costs and QALYs were extrapolated over 5 years. The additional MSU dispatch resulted in an incremental €40,984 per QALY. The best-case scenario and the worst-case scenario yielded additional costs of, respectively, €24,470.76 and €61,690.88 per QALY. In the cost-effectiveness analysis, MSU dispatch resulted in incremental costs of €81,491 per survival without disability. The best-case scenario and the worst-case scenario yielded additional costs of, respectively, €44,455.30 and €116,491.15 per survival without disability. Among patients eligible for recanalizing treatments in ischemic stroke, MSU dispatch was associated with both higher QALYs and higher costs and is cost-effective when considering internationally accepted thresholds ranging from an additional €40,000 to €80,000 per QALY. ANN NEUROL 2023;93:942-951.

A Smart Spatial Routing and Accessibility Analysis System for EMS Using Catchment Areas of Voronoi Spatial Model and Time-Based Dijkstra's Routing Algorithm.

The concept of a catchment area is often used to establish equitable access to essential services such as ambulance emergency medical services. In a time-sensitive environment, taking the wrong decision when there is a need for a short travel time can have serious consequences. In ambulance management, a mistaken dispatch which may result in the late arrival of an ambulance can lead to a life-and-death situation. In addition, finding the optimal route to reach the destination within a minimum amount of time is a significant problem. A spatial routing analysis based on travel times within the emergency services catchment area can quickly find the best routes to emergency points and may overcome this problem. In this study, a smart spatial routing and accessibility analysis system is proposed for EMS using catchment areas of the Voronoi spatial model and time-based Dijkstra's routing algorithm (TDRA) to support the route analysis of emergencies and to facilitate the dispatch of appropriate units that are able to respond within a reasonable time frame. Our simulation shows that the system can successfully predict and determine the nearest candidate ambulance unit within the catchment area and candidate ambulance services in the adjacent catchment area that has a minimum travel time to the demand point taking TDRA construction into account.

Patients’ Satisfaction With the Quality of Emergency Medical Care Service in the Example of Osh City

The article presents a study on patients’ satisfaction with the quality of emergency ambulance medical care service in Osh city. Improving the patients’ satisfaction with the quality of medical care is a key goal of any healthcare organizations. Identifying and resolving the problems (shortcomings) in conducting emergency medical care to people in timely manner is one of the effective mechanisms in quality improvement of the medical care system. An analysis is made of the findings of a survey of population views on the state and the quality of emergency (ambulance) medical care center of Osh city, on the work of it’s the dispatch unit (call center) and on the level of its technical/equipment capacity. The survey shows the prevalence of women (65.8%) who are actively using the service of emergency medical care. Among the respondents, 24% expressed their dissatisfaction with the work of dispatch unit “103”, and 37% of patients have responded that they are unsatisfied with the work of the ambulance, and 40% of the respondents were expressed their dissatisfaction with the level of technical/equipment capacity and medications provided by the ambulance unit. Among the other reasons for patients’ dissatisfaction were the lack of information provided on medical condition of the patients, the overall inadequate medical assistance provided by the emergency ambulance service, and lack of professional attitude or rude behavior toward the patients. To evaluate the quality of the work of ambulance service, the study underlines the necessity of developing and implementing a standardized questionnaire for the patients which allows to identify shortcomings and develop recommendations to the problems of the ambulance service.

Energy saving optimization of thermal power co-generation automation system in power plant

In order to establish a new optimal load distribution between CHP units and wind turbines and realize a new type of energy-saving dispatching, the authors proposed a dispatching system based on smart grid. The author proposed that the heat pump with electric drive air conditioning should share part of the heating load of the hot water radiator, accordingly, the supply of heating water is reduced, increase heating power load. This directly leads to the increase of the total power load in the grid and the decrease of the total heating and hot water load, changing the proportion of thermal power load. Based on the new heating water and power load constraints, a mathematical model of optimal scheduling is established, the energy-saving dispatching of cogeneration units and wind turbines is realized. The simulation results show that using the new energy-saving scheduling method, 342.4 MWh of fuel can be saved per hour, and the energy saving benefit is about 8.83%. If the calorific value of standard coal is 29271 kJ/kg, this means that the fuel consumption savings per hour is about 42.14 ton standard coal. The calculation results show that the higher the value is, the more economically feasible the feed-in price of wind power is. In conclusion based on the current electricity price and heating heat price, in order to ensure that the economic benefits of each participant are not changed, the feed-in price of wind power is discussed, and the economic feasibility of the method is proved.

Full-time scale resilience enhancement strategies for an integrated electricity-gas-transportation coupled system

The frequent occurrence of extreme disaster events with low probability and high risk poses a serious threat to the safe and stable operation of power grids. With the development of energy internet technology, the deep integration of power distribution, natural gas and transportation networks has opened a promising way for resilient distribution networks. This paper proposes a full-time scale resilience enhancement framework for an integrated electricity-gas-transportation coupled system oriented to energy internet. In this framework, a minimax regret robust optimization model considering the uncertainty of extreme disaster attacks is developed to make the line hardening strategy in the pre-disaster stage, which is solved by the column-and-constraint generation algorithm. Furthermore, the synthetic restoration model considering the co-optimization of dynamic dispatch of gas-fired units, network reconfiguration and damaged component repair is established, in which the coupling influence of the gas and transportation networks on the restoration strategy during the disaster and post disaster stages is taken into account. And the sequential cone programming method and generalized Benders decomposition algorithm is implemented to solve the above model. Finally, the proposed model and solution method are validated via a modified 33-bus power distribution network coupled with a 12-node transportation network and a 7-node gas network. The simulation results demonstrate that the proposed minmax regret robust optimization model can achieve a pre-disaster defensive strategy with less conservativeness in contrast to the conventional robust optimization model. Specifically, the cost under the worst-case attacks by the former has reduced by 11.52–22.29% compared to the latter. Moreover, the influence of the interdependent critical infrastructure networks on the synthetic restoration strategy in the disaster and post-disaster stages has been investigated. In particular, the power output by gas-fired units has reduced by 2699 kW when considering the operation constraints of the gas network. Additionally, due to the time-varying characteristics of traffic flow and commuting time in the transportation network, the repair time for the damaged components is shortened by 1.09 h while the preparation time of crews changes from 2.5 to 1.5 h.

Energy cost optimization of globally distributed Internet Data Centers by copula-based multidimensional correlation modeling

The high operating costs of Internet Data Centers (IDC) are a major challenge for their owners worldwide. Therefore, more attention has recently been paid to the energy and cost management of IDCs. This paper investigates the optimal operational strategy for minimizing the electricity costs of a group of globally distributed IDCs in different locations under various day-ahead electricity markets, and each is equipped with a high-performance energy storage system. For this goal, optimal workload dispatching and optimal energy management of the storage units of all IDCs are simultaneously perused by the proposed problem. The system is modeled regarding power balancing constraints, battery costs, and quality of service (QoS). For more practical results, a penalty function is also considered when QoS constraints are not perfectly met, and the impact of the batteries’ depth of discharge on the cost of energy storage is also modeled. Moreover, the cross-correlations between the traffic of IDCs are also considered by the multidimensional copula function. The proposed energy cost optimization is linearized for increasing the accuracy of convergence. The results show that not only the power consumption pattern of the IDCs is significantly improved, but also the cost of power consumption is reduced by 34%. The results also prove the positive effect of battery discharge on workload dispatch and represent a compromise between battery costs and electricity cost savings.

A strategy to enhance the distribution systems recoverability via the simultaneous coordination of planning actions and operational resources

This paper presents a planning and operational strategy to improve the recoverability of distribution systems (DSs) to deal with a set of possible line fault scenarios. The strategy simultaneously optimizes the allocation of dispatchable distributed generation (DG) units while coordinating a dynamic restoration process based on a radial topology reconfiguration, an islanding operation, a demand response program, and the pre-positioning and dispatch of mobile emergency storage units. The uncertainty and variability associated with solar irradiation and demand are captured via a multi-period formulation based on a stochastic mixed-integer linear programming model. The objective function of this model minimizes the investment cost of new dispatchable DG units and the amount of energy shedding within the system. Simulations are performed on adapted 33-node and 53-node test systems to validate the proposed strategy under four different test conditions, numerical results reveal the advantages of simultaneously solving the planning and operational stages to improve the recoverability of the system.

Analysis of Unit Commitment of Coal-fired Units in a Power Base of Cross-area DC Transmission Lines Under Dual Carbon Targets

China has announced achieving a carbon peak before 2030 and neutralization by 2060. Cross-area UHVDC transmission provides a feasible way for the new energy base to transmit power to the load center on a large scale. Usually, the dispatching of coal power units of DC transmission line power base is divided according to the equal proportion of unit capacity, this paper takes all the units as a group and proposes a unit commitment solution to realize lower carbon emission. As the capacity of new energy in the power base increases, this paper also considers the generation margin for new energy to do the optimization simulation. The results show that by operating coal-fired units as a group, it operates in a more economic and environmentally friendly way.

Effect of Mobile Stroke Unit Dispatch in all Patients with Acute Stroke or TIA.

To determine the effect of additional mobile stroke unit (MSU) dispatch on functional outcomes among the full spectrum of stroke patients, regardless of subtype or potential contraindications to reperfusion therapies. We used data from the nonrandomized Berlin-based B_PROUD study (02/2017 to 05/2019), in which MSUs were dispatched based solely on availability, and the linked B-SPATIAL stroke registry. All patients with final stroke or transient ischemic attack (TIA) diagnoses were eligible. The intervention under study was the additional dispatch of an MSU, an emergency physician-staffed ambulance equipped to provide prehospital imaging and thrombolytic treatment, compared to conventional ambulance alone. The primary outcome was the 3-month modified Rankin Scale (mRS) score, and the co-primary outcome was a 3-tiered disability scale. We identified confounders using directed acyclic graphs and obtained adjusted effect estimates using inverse probability of treatment weighting. MSUs were dispatched to 1,125 patients (mean age: 74 years, 46.5% female), while for 1,141 patientsonly conventional ambulances were dispatched (75 years, 49.9% female). After confounding adjustment, MSU dispatch was associated with more favorable 3-month mRS scores (common odds ratio [cOR]=0.82; 95% confidence interval [CI]: 0.71-0.94). No statistically significant association was found with the co-primary outcome (cOR=0.86; 9% CI: 0.72-1.01) or 7-day mortality (OR=0.94; 95% CI: 0.59-1.48). When considering the entire population of stroke/TIA patients, MSU dispatch improved 3-month functional outcomes without evidence of compromised safety. Our results are relevant for decision-makers since stroke subtype and treatment eligibility are unknown at time of dispatch. ANN NEUROL 2023;93:50-63.

The Feasibility Assessment of Power System Dispatch with Carbon Tax Considerations

Traditional economic dispatch methods, which are used to minimize fuel costs, have become inadequate because they do not consider the environmental impact of emissions in the optimization process. By taking into account the horizon year load and carbon taxes, this paper examines the operation and dispatch of power units in a power system. The objective function, including the cost of fuels and the cost of carbon taxes, is solved by the modified particle swarm optimization with time-varying acceleration coefficient (MPSO-TVAC) method under operational constraints. Based on different load scenarios, the influences of various carbon taxes for the dispatch of units are simulated and analyzed. The efficiency and ability of the proposed MPSO-TVAC method are demonstrated using a real 345KV system. Simulation results indicate that the average annual CO2 emissions are 0.36 kg/kwh, 0.41 kg/kwh, and 0.44 kg/kwh in 2012, 2017 and 2022, respectively. As the capacity of gas-fired plants was increased in 2017 and 2022, the average cost in 2017 and 2022 doubled or tripled compared with the average cost in 2012. Reasonable solutions provide a practical and flexible framework for power sectors to perform feasibility assessments of power system dispatch. They can also be used to assist decision-makers in reaching minimal operation cost goals under the policies for desired emissions.

Techno-economic sensitivity analysis for combined design and operation of a small modular reactor hybrid energy system

With increasing grid-penetration of renewable energy resources and a rising need for carbon-free dispatchable power generation, nuclear-hybrid energy systems (NHES), consisting of small modular reactors, are an increasingly attractive option for maintaining grid stability. NHES can accomplish this with a minimal carbon footprint but there are significant uncertainties that are not fully understood. This work describes and demonstrates methods for analyzing the uncertainties of potential NHES designs, including uncertain design parameters and time series as well as variations in dispatch horizon length. The proposed methods are demonstrated on a sample system with 16 design parameters, 3 uncertain time series, and a range of dispatch horizon lengths where the unit capacities and unit dispatch are co-optimized to minimize system LCOE. For the example system, 11 of 16 parameters are uncorrelated with model outputs, allowing for model reduction without decreased accuracy. It is determined that the impact of variation in multiple time series cannot be easily isolated and that the examined sources of uncertainty are of similar importance in terms of overall impact. • Optimize SMR-renewable hybrid energy system design with uncertain parameters. • Quantify design changes with forecasts as stochastic time series. • Investigate optimal dispatch and design with varying horizon length. • Method for sensitivity analysis of combined design and dispatch of SMR hybrid energy systems.

Optimizing Operation Strategy in a Simulated High-Proportion Wind Power Wind–Coal Combined Base Load Power Generation System under Multiple Scenes

In order to accommodate more intermittent renewable energy in coal-dominated power systems, conventional thermal power plants need to improve their operational flexibility to balance the energy system at all times. However, flexible operation of coal-fired power plants could reduce energy efficiency and increase CO2 and pollutant emission, so it is important to consider environmental implications and optimize the dispatch of wind and coal power units in the system. In this paper, based on the output profile of wind power, a wind power peak (T, H) simulation model based on Gaussian distribution was established. Using a high-proportion wind power wind–coal combined base load power generation system as an example, the economical and environmentally friendly unit operation based on different wind power penetration was studied by simulation, and the decision strategy was established. Wind energy curtailment boundary was determined with power generation cost, energy consumption, CO2 and pollutant emissions as decision targets, respectively. Weekly scale results indicate that incorporating energy consumption and pollutant emissions into consideration will lead to different decision-making strategies compared with only targeting minimizing wind curtailment. This paper established a decision-making model of wind–coal system operation strategy based on economy and environmental criteria. This work directly contributes to real system operation and is of great significance for future scheduling/dispatch studies of actual power systems.

Iterative Dynamic Programming—An Efficient Method for the Validation of Power Flow Control Strategies

The operation of electrical networks, microgrids, or heterogeneous battery systems, especially the dispatch of single units within the system, requires sophisticated power flow control strategies. If objectives such as efficiency are demanded for the operation of the energy system, typical control strategies lack the ability to verify the optimality of the operation. Dynamic programming is a widely used method for determining the global optima of trajectory problems. In the context of energy systems and power flow optimization, it is restricted to applications with a low number of states and decisions. The reason for this is the rapid growth of computational effort with increasing dimensionality of the state and decision space. The approach of iterative dynamic programming (iDP) makes dynamic programming applicable to the planning and benchmarking of complex power flow optimization problems. To illustrate this, a heterogeneous battery energy storage system is introduced for which the iDP optimizes the power split at the point of common coupling to minimize the total cumulative loss of energy. The method can be adopted for a broad range of energy systems such as microgrids, utility grids, or electric vehicles. The applicability is limited only by the computation time, which depends on the model complexity and the length of the time series. To verify the functionality of the iterative dynamic programming, its results are directly compared to those of the standard dynamic programming. The total computation time can be reduced by 98% in the tested scenario. As relevant use cases, static and dynamic methods of power sharing are validated and benchmarked. The iDP offers a novel and computationally efficient method for the design and validation of power flow control strategies.

Optimal Dispatch of Multi-Type CHP Units Integrated with Flexibility Renovations for Renewable Energy Accommodation

Driven by the goals of carbon neutral and carbon peak, coal power units need increased flexibility in peak shaving to accommodate intermittent renewables, especially for a region with a large proportion of combined heat and power (CHP) units in China. In this study, the data-mining-based method is proposed for revealing and utilizing the heat–power coupling mechanism of CHP units, which can be used to solve the mentioned issues. Specifically, extraction-condensing (EC) units, high-back-pressure (HBP) units and low-pressure turbine zero power output (LZPO) units are introduced into the proposed dispatch model for maximizing renewable energy accommodation. The operation schemes and the feasible minimum output power of the CHP system under one certain heat load are obtained via the genetic algorithm. Results show that the CHP system is capable of reducing its output power by 18.7% to 41.7% in the heating season, compared with the actual operation data. Furthermore, the influence of multi-type units’ combination on peak-shaving flexibility is discussed. This study can be utilized for the optimal load dispatch scheme of multiple CHP units and guide the power dispatching department in making reasonable generation plans.

Combined static and dynamic dispatch of integrated electricity and heat system: A real-time closed-loop demonstration

Coupling the electricity and heating systems introduce opportunities to handle the intermittent nature of an increasing share of renewable power generation. Coordination of units in the coupled systems requires careful static dispatch towards an optimization objective. As the uncertainties in renewable forecasting are reduced towards operation time, operators can perform dispatch numerous times to balance the determined mismatches. With higher shares of renewable, sudden changes in power generation due to changing weather can cause a power imbalance that disturbs the system frequency. To handle such hazards, dynamic dispatch in the form of frequency control is necessary. Recent literature in integrated electricity and heating systems (IEHS) is studied in this work to combine the static and dynamic dispatch of units. A two-stage stochastic day-ahead scheduling method combined with a model predictive control (MPC) -based real-time optimal operation method that allocates both following and regulating reserves is used as the static dispatch of the IEHS. The allocated reserves constrain the performance of the dynamic dispatch by limiting the control capacity. In this work, an MPC coordinated frequency control of small- and large-scale heat pumps is considered as the dynamic dispatch of the IEHS. The performance of the dynamic dispatch is evaluated through a real-time closed-loop simulation platform, where the system conditions of the static dispatch are used as the steady-state conditions. Results show that despite challenging communication conditions, the frequency control of small- and large-scale heat pumps improves frequency nadir conditions after a power imbalance.

Optimal energy management in a microgrid with known power from grid based on particle swarm optimization embedded Fuzzy multi-objective approach

The optimal energy management among distributed energy resources (DERs) in a microgrid is pivotal for its satisfactory operation. This paper presents the optimal dispatch of combined heat and power (CHP) units and a heat boiler is conducted in zero bus concept based microgrid (ZBMG) and in grid connected microgrid (GMG). In ZBMG, the utility exchanges a prescheduled amount of power to the microgrid. In this work, the optimal dispatch of various CHP units and boiler in all cases under GMG and ZBMG systems with power and heat demand is examined. The generation cost, emission, and energy loss objectives are fuzzified and solved using particle swarm optimization (PSO) algorithm. The results show that minimum objectives are attained in ZBMG compared to GMG system. The analysis is carried out on a 33-bus and 69-bus distribution systems with a 24-hour electrical and heat load profile pattern.

Emergency services support of microgrid system to the utility grid through incentive-based demand response program

The integration of a large share of intermittent renewable generation and varying load demand has increased the ancillary service requirement in the modern power systems. Coordinated and controlled operation of these renewable energy sources (RESs) with conventional sources is required to meet this requirement. The ancillary services arising due to uncertain RESs and loads can be managed better if RESs connected in a microgrid (MG) which has the provision of monitoring, control, demand response (DR), and storage in it. This paper proposes and demonstrates the role of a microgrid in providing the ancillary services support to the grid considering the demand response program (DRP). Netload variations are captured during load scheduling considering the DR contribution and aggregated netload of the prosumers. Participants of the DRP receive incentives based on the power curtailment during scheduling. The system performance has been investigated with and without DR and commitment of the microgrid to support the utility grid (UG) considering different types of consumer loads (i.e. Shiftable, controllable and curtailable). The incentives to the consumers, availability of storage system along with power trading regulations impact their contribution in ancillary service support to the system. The simulation results obtained demonstrate the significance of DR in a microgrid system to improve the system performance during dynamic conditions as it improves the load profile by suitably countering the variations in the generation and the load. In addition, the implementation of DRP in the system operation along with the unit dispatch helps in improving the social welfare by providing incentives to the consumers for participation and also reduces the extreme power generation ramping of conventional generators during periods of power stress.

Optimal fuzzy based economic emission dispatch of combined heat and power units using dynamically controlled Whale Optimization Algorithm

The significance and purpose of this multi-objective Combined Heat and Power Economic Emission Dispatch (MO-CHPEED) problem aims to determine the optimal generator output of the co-generation systems, in which two conflicting objectives of the fuel cost and mass of emissions are to be simultaneously minimized. The nonlinear and nonconvex nature of the objective functions needs a good optimization technique to handle it. This paper proposes a Dynamically Controlled Whale Optimization Algorithm (DCWOA) to solve the multi-objective non-convex MO-CHPEED problem in fuzzy environment. The proposed DCWOA is an improved variant of the traditional WOA method by adding dynamically controlled constriction function. Both the conflicting objectives of fuel cost and mass of emissions are handled using Fuzzy Framework. To highlight the performance of the proposed technique, it is tested on the latest CEC test functions and three different MO-CHPEED case studies. The results obtained by proposed DCWOA after 100 independent trails on latest CEC test functions and compared with latest different published methods show the effectiveness and robustness of the proposed method for getting better average and STD values. Moreover, proposed DCWOA is also tested on different dimensioned MO-CHPEED test functions after 100 independent trails and compared with latest techniques. Again the most compromise results given by proposed DCWOA highlights the supremacy of the proposed method in terms of the getting better fitness and best compromise solution obtained and the convergence traits of the MO-CHPEED problem.