Dispatch Of Supplies Research Articles

Storage and dispatch of supplies in public markets: Dimensions to improve based on empirical evidence from food safety and as a sustainability strategy for the supply chain

The text addresses the importance of food safety worldwide, highlighting the crucial role of organizations such as the UN, WHO and FAO in promoting safe practices in the food chain. It focuses on the public markets of Guayaquil, where an alarming increase in Foodborne Diseases has been observed and various irregularities that affect food security and public health have been identified. The study uses a mixed methodological approach that combines literature review and the application of questionnaires to comprehensively address the issue of food safety in these markets. The literature review provides a broad and contextual theoretical framework, while the questionnaires collect specific data that complement the qualitative findings, thus ensuring a balanced and detailed exploration of the phenomenon. The general objective is to develop a comprehensive approach to improve food safety protocols in public markets, identifying fundamental dimensions, objectives of information gathering tools and design limitations. The need to improve infrastructure, train staff, control pests, manage waste and apply hygiene and safety measures in markets is highlighted, along with compliance with regulations and collaboration between entities. Challenges and measures are raised to improve food safety in the municipal markets of Guayaquil, highlighting the importance of comprehensive actions that address multiple aspects to protect public health and guarantee food security.

Optimal deployment of energy services for economic upliftment of low-income communities: A South African case study

Low-income communities face a causality dilemma: A lack of energy services hampers income growth and insufficient income hampers energy service provision. Interventions delivering cost-effective energy services can address this dilemma, triggering a virtuous cycle of economic upliftment. While several studies have investigated cost-effective energy supply to low-income communities, a gap exists regarding holistic optimization of energy service deployment at different levels of economic development. Hence, a novel energy system model of a South African village is presented to optimize deployment and hourly dispatch of energy supply and energy services to recover time lost to poverty-related activities (e.g., gathering wood and water). Results showed that an optimized technology rollout can save each person over 1500 productive hours per year at an average cost below 0.2 $/hour. The model also identified the optimal order of technology deployment for driving economic development. Interestingly, an electrical grid connection was of minor importance because local mini-grids could economically supply the modest power demands of lighting, refrigeration, water pumping, and cleaning, while energy-intensive cooking and water heating can be economically performed using fuels and solar heaters. Detailed studies of individual low-income communities are recommended to outline optimal technology deployment strategies and reveal the low costs involved.

A multimodal analytics framework for product sales prediction with the reputation of anchors in live streaming e-commerce

Insufficient sales prediction easily leads to the untimely dispatch of supply and causes inventory problems, resulting in a loss of profits for merchants. Previous sales prediction research was mainly based on traditional e-commerce platforms that cannot be directly applied to live streaming e-commerce, which adds many important elements. The main contribution of our research is the design of a multimodal analytics framework for product sales prediction in live streaming e-commerce. In the proposed framework, we explore the influence of anchor reputation on product sales and innovatively consider both historical and real-time reputation signals. In addition, to better extract valuable information for real-time signals, we propose an A-tiFSR model to extract features from product text and images and design a fine-grained analysis method to mine danmaku data. We conduct our experiments based on a real-world dataset collected from Douyin live streaming. The experimental results demonstrate the effectiveness of the constructed multimodal reputation signals of anchors on product sales prediction. The management implication of our research is that merchants and anchors should pay more attention to their multidimensional reputation. The proposed sales prediction framework can help merchants predict sales more accurately and optimize inventory policy and marketing strategies. This study thus supports the more effective development of live streaming e-commerce markets.

Blockchain-Based Gas Auctioning Coupled with a Novel Economic Dispatch Formulation for Gas-Deficient Thermal Plants

Inadequate gas supply is partly responsible for the energy shortfall experienced in some energy-poor nations. Favorable market conditions would boost investment in the gas supply sector; hence, we propose a blockchain-based fair, transparent, and secure gas trading scheme that facilitates peer-to-peer trading of gas. The scheme is developed using an Ethereum-based smart contract that receives offers from gas suppliers and bid(s) from the thermal plant operator. Giving priority to the cheapest offers, the smart contract determines the winning suppliers. This paper also proposes an economic dispatch model for gas-deficient plants. Conventional economic dispatch seeks to satisfy electric load demand whilst minimizing the total gas cost of generating units. Implicit in its formulation is the assumption that gas supply to generating units is sufficient to satisfy available demand. In energy poor nations, this is hardly the case as there is often inadequate gas supply and conventional economic dispatch is of little practical value. The proposed economic dispatch model’s objective function maximizes the quantity of available gas and determines the optimal power output of each generating unit. The mathematical formulation is verified using data from the Egbin thermal station which is the largest thermal station in Nigeria and is solved using the General Algebraic Modeling System (GAMS). Obtained results indicate the viability of the novel approach as it results in a net power gain of 35 MW. On the other hand, the smart contract proved effective in accurately selecting winning suppliers and making payment.

Stochastic local flexibility market design, bidding, and dispatch for distribution grid operations

In order to unlock the flexibility potential of energy consumers and prosumers, the development of market mechanisms for flexibility planning and procurement is necessary. The authors propose a stochastic local flexibility market to solve grid issues such as voltage deviations and grid congestion in a distribution grid. Their proposed solution includes activation of flexibility assets at the consumers’ premises, using a stochastic local flexibility market design. They consider a pooled local flexibility market design under demand uncertainty and stochastic bidding process. Optimization models are used to determine flexibility demand and supply bids by the distribution system operator and the aggregator respectively. A stochastic AC-optimal power model to determine flexibility demand and a two-stage stochastic model to supply flexibility are implemented to simulate a stochastic local flexibility market. This allows to determine stochastic flexibility supply bid curves, and optimum flexibility supply dispatch. The analysis shows that the cost of grid operations is reduced when the system uses the local flexibility market. The proposed methodology is applicable for local flexibility market designs aiming to use potential end-user flexibility for grid operations.

System dynamics mechanism of cross-regional collaborative dispatch of emergency supplies based on multi-agent game

The cross-regional coordinated dispatch of emergency supplies is a complex issue involving multiple topics, which covers multiple relationships and is affected by multiple variables. In the face of severe emergencies, relief supplies inside a specific area are far from meeting the explosive demand for emergency supplies. Besides, the supply of emergency materials and the disaster areas often have a spatial mismatch. Considering the attributes of externalities and public goods of emergency rescue, there are many obstacles for Local administration of emergency (LAE) and emergency logistics enterprises (ELE) spontaneously carrying out emergency supplies across regions. To solve this complexity problem, this research abstracts higher-level administration of emergency (HAE), LAE and ELE as the main stakeholders, with which a tripartite evolutionary game (ETG) model and a system dynamic (SD) model are constructed to analyze the dynamic mechanism of the complex system and to carry out the numerical simulation of the three-party game process. All the analyses and tests in this study have proved that the strong supervision of HAE has a decisive impact on the realization of cross-regional coordinated dispatch of emergency supplies, and the financial rewards and punishments imposed by HAE on other entities can accelerate or delay the achievement of the equilibrium strategy. However, when HAE chooses not to regulate, the cooperation willingness of LAE affects a lot that all the stakeholders will eventually reach equilibrium at (1,1,1) only if LAE chooses to actively carry out cross-regional coordinated dispatch of emergency supplies.

Analysis on the demand response potential in hotels with varying probabilistic influencing time-series for the Canary Islands

Abstract Tourism represents a significant portion of the total economic activity of many islands throughout the world. This high level of tourist activity has a substantial impact on the energy and water demand. Previous research into smart energy systems on islands has demonstrated that there is significant potential for hotels to partake in energy demand shifting. However, the total potential of such shifting is influenced by variables such as air temperature and the level of occupancy of the hotels. The objective of this work is to quantify the sensitivity of these parameters and their impact on the overall effectiveness of demand shifting within hotels. The assessment contained within this paper utilises Mixed Integer Linear Programming to determine the dispatch of supply and demand on a case study hotel in the Canary Islands. The results show that highest reduction of fossil fuels is reached in a fully electrified hotel energy system. The potential is assumed as independent from weather and guests’ behaviour. If only PV is used, demand shifting in only one hotel leads to a relative change of the degree of self-sufficiency of 1.6–1.8% but the results visualise a saturation effect for an already high share of renewable energies.

Spatial representation of temporal complementarity between three variable energy sources using correlation coefficients and compromise programming

Renewable energy sources have shown remarkable growth in recent times in terms of their contribution to sustainable societies. However, integrating them into the national power grids is usually hindered because of their weather-dependent nature and variability. The combination of different sources to profit from their beneficial complementarity has often been proposed as a partial solution to overcome these issues. Thus, efficient planning for optimizing the exploitation of these energy resources requires different types of decision support tools. A mathematical index for assessing energetic complementarity between multiple energy sources constitutes an important tool for this purpose, allowing a comparison of complementarity between existing facilities at different planning stages and also allowing a dynamic assessment of complementarity between variable energy sources throughout the operation, assisting in the dispatch of power supplies. This article presents a method for quantifying and spatially representing the total temporal energetic complementarity between three different variable renewable sources, through an index created from correlation coefficients and compromise programming. The method is employed to study the complementarity of wind speed, solar radiation and surface runoff on a monthly scale using continental Colombia as a case study during the year of 2015.•This paper describes a method for quantifying and spatially representing energetic complementarity between three renewable energy sources.•The method quantifies energetic complementarity by combining known metrics: correlations and compromise programming.•The proposed index for energetic complementarity assessment is sensitive to the time scale adopted.

An Internet of Things based material delivery model for disaster management in libraries

PurposeBased on the context of the Internet of Things (IoT), the territorial public emergency supplies will be networked, platform-based management, unified emergency dispatch. The problem of supplies dispatching in the “last kilometer” of emergency is solved, and the supplies needed in the disaster area are promptly delivered to the hands of the victims so that they can quickly be rescued after the disaster and to save valuable time for rapid rescue, which can greatly decrease casualties and property losses. This paper aims to discuss these issues.Design/methodology/approachBy analyzing the shortage of existing emergency supplies dispatching research and taking all factors such as disaster area demand, social reserve, road conditions, mode of transport, loading limit, disaster area satisfaction rate and road capacity into consideration under the background of IoT, a variety of the territorial emergency supplies dispatching model with more rescue points, more affected areas are constructed. The objective function of the model is to aim in finding the shortest rescue time, giving the solution algorithm, and finally simulating the simulation case.FindingsBased on the context of the IoT, the territorial public emergency supplies will be networked, platform-based management, unified emergency dispatch. Considering factors such as road conditions, modes of transport and road capacity, the authors construct a number of emergency rescue plans, multiple disaster scenarios and various emergency supplies dispatching models. The authors simulate the situation through simulation cases with the shortest time being the ultimate goal. The problem of supplies dispatching in the “last kilometer” of emergency is solved, and the supplies needed in the disaster area are promptly delivered to the hands of the victims so that they can quickly be rescued after the disaster and to save valuable time for rapid rescue, which can greatly decrease casualties and property losses.Originality/valueThis paper provides little research on the dispatch of emergency supplies. The problems of direct dispatch from the rescue point to the affected area and dispatch of supplies without relying on the arrival of emergency supplies at the rear are addressed. Therefore, this study does not focus on the arrival of emergency supplies at the rear but on direct dispatching issues during territorial public emergency supplies from the rescue point to the disaster point.

The role and costs of large-scale heat pumps in decarbonising existing district heating networks – A case study for the city of Herten in Germany

This paper discusses different decarbonisation scenarios for an existing district heating (DH) network supplied by coal-fired combined heat and power plants in Germany. Integrating higher shares of renewable heat is indispensable in reaching the climate goal and CO2 emission reduction targets. The study analyses the technical and economic aspects of integrating various technologies such as solar thermal, biomass boilers, waste incineration plant and heat pumps into the existing DH network, with the main focus on large-scale heat pumps. The approach consists of two main steps. First, we forecast future heat demand and the potential to extend the DH system by simulating the evolution and energy consumption of the city's building stock. Second, we use a supply dispatch model with hourly resolution to calculate alternative scenarios and sensitivities for the supply mix with a focus on heat pumps.Our results show that, under the current regulatory and economic framework, large-scale heat pumps are not cost competitive with the existing coal-fired CHP units. However, redesigning the regulatory framework and optimising heat pump design and operation could achieve cost parity. The CO2 price induced by the EU emissions trading scheme will most likely not be a sufficient incentive in short and medium term.

A Shift From Logistic Software to Service Model: A Case Study of New Service-Driven-Software for Management of Emergency Supplies During Disasters and Emergency Conditions by WHO.

World Health Organization (WHO) states access to medicine as a priority area for universal health coverage, wherein a well-functioning medicine supply chain is indispensable. Optimization of supply chains to cut losses related to overstocking, expiration, and inefficiencies protect the investments and strengthen health systems to better deliver the health services. This article shares the experience of developing a service-driven-software for pharmaceutical supplies during emergency conditions and disasters, and the advantages gained. In 2005, Logistic Support System (LSS), the updated version of SUMA (Supply Management), was introduced by WHO during the earthquake in Pakistan which had offered valuable but limited services to many countries. Moving from ad hoc to a more organized approach, the medical donations and stockpiles of essential medicinal supplies were inventoried on LSS database for managing the dispatch of medical supplies to the disaster-hit area in a shortest possible time. Post disaster rescue and rehabilitation work further instigated the need for development of a new software, Pharmaceutical Information Management System (PIMS), that was effective in the emergency as well as routine inventory operations. It was used for efficient and improved access of medicines and faster decision making. The new systems proved vital to anticipate over/under stocking through proactive alerts and prompting. The updated information on epidemiological and drug utilization needs were crucial for the effective quantification and ordering throughout the supply chain. Implementation of PIMS demanded appreciable customization including conversion of system from stand-alone to online system with consolidation of information on stocks from all locations. Provision of multi-user option allowed facilitation according to the user authorization, and was equipped with improved-speed, efficiency, and security. PIMS was successfully replicated by the pioneer team of pharmacist from Pakistan in other countries.

Electricity market deregulation in Singapore – Initial assessment of wholesale prices

Singapore began a huge step to deregulate its electricity market since 2003, with the creation of the National Electricity Market of Singapore (NEMS) allowing for bid-ask offers to be made for the dispatch of electricity supply on the wholesale side. Subsequently, the retail market liberalised in tranches, with 80% of electricity consumers currently already given an option to select their electricity retailers since late 2014. This paper aims to quantitatively analyse how competitiveness in both the wholesale and retail market led to price decreases from 2014 to 2017, using daily data for electricity and oil prices. We find that supply competition and the more recent retail liberalisation efforts has possibly led to a combinatorial decrease in wholesale electricity prices by up to 9.11%, accounting for the influence of oil prices and volatility components. This work seeks also to bring some insights on what to expect from full retail contestability after the latter half of 2018.

Optimal Transactive Market Operations With Distribution System Operators

Distribution system operator (DSO) has traditionally been responsible for the reliable operation of power distribution systems. The advent of distributed energy resources (DERs) and microgrids in distribution networks has required a new platform for DSOs. The new DSO, which is for the most part an independent agent, is responsible for aggregating a widely dispersed DERs (which include small thermal generation units, energy storage, and demand response) and flexible loads in electricity markets. DSO coordinates and balances the transactive dispatch of supply and demand at the distribution level and links wholesale and retail electricity markets. In this paper, a framework for the day-ahead transactive market is proposed which includes end-to-end power system participants starting from the bulk power ISO and ending at DSO, which includes the management of retail customers with small loads. In this paper, DERs are considered in a local distribution area (LDA). The day-ahead transactive scheduling of LDA is modeled as an MILP and solved using the CPLEX solver. This paper offers numerical results considering a DSO that is responsible for the optimal and secure operation of LDA with microgrids. The simulation results show that the proposed DSO framework in a transactive market can efficiently reduce the supply cost of LDA and increase the GenCos’ payoff considering the optimal power exchange with the ISO.

Study on Regional Water Resources Allocation Efficiency Based on Networking and Joint Scheduling of Reservoir Groups

The effect of reservoir group networking and joint scheduling on the efficiency of regional water resources allocation is studied in the paper and demonstrated by case analysis of two engineering projects in the counties of Zhejiang Province. The efficiency of water resources allocation involves both engineering and economic aspects, and its improvement is the result of the interaction between institutions and technologies. The efficiency of networking and joint scheduling of reservoir groups is obvious, as proved by the physical network created by joint scheduling, the internal incentive mechanism generated by water right transactions, as well as the networking and joint scheduling of agricultural irrigation, urban water supply and ecological water use. This efficiency mainly comes from the accumulation of reservoir resources and the rational utilization of flood resources brought by networking and joint scheduling. It would be an important model for the future development of regional water resources optimization to network and jointly operate reservoir groups. In essence, the networking and joint scheduling of a reservoir group involve the optimal allocation and operation of multi-source water resources for multi-users. The scheduling diagram can be regarded as the combination of diversion and water supply dispatch of each member reservoir, forming the network structure, realizing the joint operation of regional water resources, and finally improving the efficiency of water resources allocation at different stages in different regions. The main body of the reservoir networking and joint scheduling, the government departments, carry out planned dispatching of reservoirs only with obtaining certain amount of information. It is therefore necessary to establish an incentive compatibility mechanism to overcome such defects as information lag and asymmetry, in networking and operating reservoir groups.

Technical assessment of centralized and localized voltage control strategies in low voltage networks

Abstract Both the electric power demand and the penetration of small-scale embedded generators (SSEGs) is rapidly increasing in LV distribution grids. These trends are expected to have significant effects on system performance, efficiency and reliability necessitating the adjustments to the current framework for power supply dispatch and delivery. This paper proposes hybrid voltage control schemes for LV distribution networks combining: (i) centralized control via the on-load tap-changer (OLTC) of secondary distribution transformers and (ii) localized control via both the real and reactive power management from single-phase PV inverters. Specific control algorithms are proposed for both the centralized and localized methods. All the possible operation sequences of the aforementioned methods are examined. The performance of the proposed approaches is investigated on four different test feeders considering the voltage magnitudes, the voltage unbalances, the total losses and the PV power utilization.

Modeling Optimal Economic Dispatch and System Effects in Natural Gas Networks

In this paper we present a modeling framework for analyzing natural gas markets, taking into account the specific technological issues of gas transportation. We model the optimal dispatch of supply and demand in natural gas networks, with different objective functions, i.e., maximization of flow, and different economic surpluses. The models take into account the physical structure of the transportation networks, and examine the implications it has for economic analysis. More specifically, pressure constraints create system effects, and thus, changes in one part of the system may require significant changes elsewhere. The proposed network flow model for natural gas takes into account pressure drops and system effects when representing network flows. Pressure drops and pipeline flows are modeled by the Weymouth equation. A linearization of the Weymouth equation makes economic analyses computationally feasible even for large networks. However, in this paper, the importance of combining economics with a model for pressure drops and system effects is illustrated by small numerical examples.

Optimal Bidding Strategy in Spinning Reserve Market

In this paper, the problem of building the optimal bidding strategies for competitive suppliers in the California-type spinning reserve market is addressed. In this market, each supplier is required to submit a capacity bid and an energy bid simultaneously, and selection of spinning reserve suppliers is solely based on the capacity bids and the required spinning reserve amount broadcast by the independent system operator (ISO). In this procedure, the uniform market clearing price rule is employed. W inners of capacity bids may be asked to provide energy in ISO's real time dispatch according to system operation requirements, and the dispatch of energy supply is based on energy bids with application of the uniform market clearing price rule. It is assumed that each supplier bids a linear capacity supply function and a linear energy supply function into the spinning reserve market, and each supplier chooses the coeffi cients in these two supply functions to maximize benefits, subject to expectations about how rival suppliers will bid. A stochastic optimization model is first developed to describe this problem, and a genetic algorithm based method is then employed to solve it. A numerical example is utilized to illustrate the essential features of the method.