Load Supply Research Articles

Recent Trends in Power Quality Improvement: Review of the Unified Power Quality Conditioner

The electrical power sector is currently focusing on power quality (PQ) issues and their mitigation. Industrial automation and the use of power electronic converters for the integration of distributed generation create various PQ problems. This necessitates PQ enhancement, which in turn helps to improve the life span of the equipment as well as the reliability of supply for feeding critical loads within the system. This paper presents a comprehensive review of the Unified Power Quality Conditioner (UPQC) and its widespread application in the distribution system. The UPQC belongs to the family of active power filters. It contributes to the alleviation of voltage and current-related PQ issues along with power factor correction and the integration of renewable energy systems in the distribution network. This paper discusses various topologies, compensation methods, control theories, and the technological developments in recent years. More than 160 research papers have summarized the features of UPQC for further applications. Based on the outcomes of the investigation, the future direction of the UPQC is discussed. This paper is expected to play a major role in guiding research scholars in the application of the UPQC.

Equilibrium allocation strategy of multiple ESSs considering the economics and restoration capability in DNs

Distribution networks (DNs) face challenges in maintaining continuous power supply for critical loads under extreme natural disasters, such as typhoons. However, the economic benefits resulted from the investments of multiple energy storage systems (ESSs) is difficult to be evaluated and described in the resilience-oriented pre-typhoon allocations as a result of the huge differences lying in the impacts and probabilities of typhoons and normal states. This paper proposes an allocation strategy of multiple ESSs to seek for the equilibrium between the resilience and the economic benefits of DNs considering the advantages of fixed ESSs (FESSs) and mobile ESSs (MESSs). Firstly, the framework of equilibrium allocation strategy of multiple ESSs is captured, where indexes of resilience and economic benefits of DNs are formulated based on the evaluation of DN failure probabilities under typhoons using Gaussian mixture models (GMMs). The restoration states of outage loads and prioritized power requirement of loads are also considered based on FESSs and MESSs. Then, a bi-level allocation model of multiple ESSs in the whole planning period is proposed, in which the Nash equilibrium method is used to balance the resilience under typhoons and economic benefits under normal states. Finally, simulation tests of typhoon-prone DNs verify the superiority of the proposed bi-level equilibrium allocation model of multiple ESSs compared with other approaches.

Robust coordination of repair and dispatch resources for post-disaster service restoration of the distribution system

Since extreme weather events usually severely damage the power grid and lead to widespread power outages, coordinating repair and dispatch resources, such as repair crews (RCs), mobile power sources (MPSs), renewable energy sources (RESs) and energy storage systems (ESSs), is an efficient method to restore the power supply for outage loads. However, the uncertainties existing in RES output and load demand pose significant challenges to the service restoration of distribution systems in terms of security constraints. To address these uncertainties, this paper proposes a robust restoration approach to maximize the restored load in a distribution system by coordinating RCs, MPSs, RESs, ESSs and network reconfiguration. The coordination problem is formulated as a two-stage robust optimization model to generate optimal dispatching and operation schemes of multiple resources with guaranteed robustness against uncertainties. Involving some unexpected changes in topologies and distributed sources during post-disaster repair, the robust coordination model is re-optimized to guarantee the efficiency of repair and operation scheme. Simulation results show that the repair and dispatch resources can be coordinated effectively to accommodate the RES output and load demand uncertainties while maximizing the amount of restored load for service restoration of the distribution system.

Case Study of Load Matching and Energy Cost for Net-Zero Energy Houses in Korea

Over the past 20 years, net-zero energy house (NZEH) construction costs have steadily decreased because of many reasons, such as technical progress, energy-saving design obligations, and dramatic cost reductions in renewable energy systems, especially solar power systems. Currently, the costs of NZEH are estimated to be about 5% higher than similar-sized houses. These additional costs are mainly for installing PV systems, which can be offset by energy saving costs. This study assessed energy performance and load matching through remote monitoring systems, and energy costs were analyzed for two-family houses. The two houses were all-electric houses and different in both size and location. A 6 kWp grid-connected PV system and 16 kW air source heat pump for space heating and domestic hot water were equally implemented. After data analysis, 100% of the energies were supplied through the PV system for 3 years, thus achieving net-zero energy. According to the Korean residential electricity tariff system, the annual electricity charges were, on average, between USD 105.1 and USD 121.4 after adding demand charges and value-added tax for import electricity charges. The energy cost reduction rate, compared to the same house without a PV system, was about 95%, and the simple payback period of the 6 kW PV system in NZEH was about 6 years. In addition, the annual load cover factor and supply cover factor as load-match indices between electricity generation and the load were in a range of 0.39–0.49 and 0.37–0.42, respectively.

Вплив енерговтрат імплантата з бездротовим живленням на тепловий стан організму

Technical means that create for regenerating lost functions of the human body primarily focused on the target function. However, even when implants achieve performance that corresponds to natural organs and systems, in many cases the developers do not pay enough attention to the energy supply of implants and additional heat load due to energy losses in mechanical, electrical, and electronic units. If you do not consider these factors, it limits the duration and medical safety of the devices. It is especially true for implants with significant power consumption and wireless power supply. Therefore, this work determines the allowable additional heat load of the human body to justify the choice of further circuit solutions for wireless powering of implants with significant energy consumption and long-term operation. The subject of research is the processes of heat exchange between the implant and body structures and their energy and temperature indicators. The research object was chosen as an implant of the type "Artificial Heart" device (AHD) with a maximum power of 20… 25 W and the magnetic induction principle of energy transfer. The research tasks are to analyze the processes of heat exchange between the implant and the biostructures of the body; to calculate quantitative indicators of energy exchange in the location of the main components of the implant; to determine the temperature of biotissues in the area of the receiving inductor. The subject of research is the processes of heat exchange between the implant and body structures and their energy and temperature indicators. The research object was chosen as the implant of the type "Artificial Heart" device (AHD) with a maximum power of 20… 25 W and the magnetic induction principle of energy transfer. The research tasks are to analyze the processes of heat exchange between the implant and the biostructures of the body; to calculate quantitative indicators of energy exchange in the location of the main components of the implant; to determine the temperature of biotissues in the area of the receiving inductor. Research results. The processes of heat exchange between the structural elements of the implant and the biostructures of the body have a complex combination of physiological and physical mechanisms. Estimates are made based on the thermal conductivity process, as the most objective in terms of known quantitative indicators. With an average efficiency of ~ 0.8 for mechanical, electrical, and electronic components of the implant "Artificial Heart," the human body can maintain a stable temperature of internal organs in the presence of an implant with a maximum power consumption of 20 watts. The calculation conducted using the method of electrothermal analogy showed a possible increase in the temperature of biotissues in contact with the surface of the receiving implanted inductor, by 1.32 ° C. This value refers to the critical levels of internal tissue temperature rise. Summary. For practical implementation of the autonomous device the Artificial Heart Device, it is necessary to combine known or to find the original circuit-technical and design decisions of construction of components of wireless power supply with the magnetic induction principle and efficiency of not less than 0,8. To prevent thermal overload of biotissues, it is advisable to introduce a temperature control channel at potentially critical locations of the implanted elements. It is possible to predict the finding of these critical points by calculations by the method of electrothermal analogy.

A Power Dispatch Optimization Method to Enhance the Resilience of Renewable Energy Penetrated Power Networks

With the wide deployment of renewable energies, future power grids become more vulnerable to extreme environments. This paper investigates enhancing the resilience of power systems with high penetrations of renewable energies under emergencies. The resilience enhancement firstly is defined as maintaining as much electric energy to critical loads in a fixed number of post-disaster periods by properly coordinating the available resources. Then, an optimal decision-making method is proposed to maximize the power supply of critical loads and to minimize the instability risks due to the randomness of the output power of renewable energies. The power consumption of loads, charging/discharging power of power storage plants, power generation of generators, and spinning reserve ratios of the renewable energy at each period are taken as decision variables. Constraints include spinning reserve, power flow constraints, and power consumption/generation limits. The interior-point algorithm is used to solve the formulated optimization problem. Numerical simulations verified the effectiveness and superiority of the proposed optimization method in boosting grid resilience after disasters. It is also found that a balance should be sought between decreasing stability risks and increasing the power supply benefit in extreme environments.

Energy Performance Investigation of Bi-Directional Convergence Energy Prosumers for an Energy Sharing Community

Due to the wide-spread use of photovoltaic (PV) systems, interest regarding economic benefit and energy-sharing from surplus electricity has been raised. In this study, decentralized thermal and electric convergence energy prosumers for an energy-sharing community are proposed. For the convergence energy system, a simultaneous heating and cooling heat pump (SHCHP) system integrated with a thermal network is proposed, and the energy performance and operating energy savings of the proposed system were investigated. A smart village located in the Busan Eco Delta Smart City was selected as a case study for the simulation analysis. Experimental data of the heat pump system were used to analyze the SHCHP. The analysis results showed that the proposed system could provide over 53% and 86% of the load cover and supply cover factors, respectively. The proposed system can earn economic benefits, such as energy trading from the surplus electricity of PV systems and thermal energy produced by an SHCHP, more than 30.5 times those of conventional air-source heat pump systems. These benefits mainly originate that a conventional system can trade the surplus electricity from a PV system but the proposed system can trade produced thermal energy from SHCHPs and the surplus electricity from PV systems.

Total power deficiency estimation of isolated power system network using full-state observer method

<span>An isolated electrical network with an independent local distributed generator is very sensitive towards the contingencies between load demand and supply. Although the network system has less complexity in term of structure, its stability condition is crucial due to its stand-alone operating condition. The total power deficit in the network gives the important information related to the dynamical frequency responses which may directly affect the system’s stability level. In this paper, the approach to estimate the total power deficiency for the isolated electrical network was presented by utilized the Luenberger observer method. Although the power deficit is not the state variable in the network mathematical model, the solution of estimation problem was feasible by introducing the new variable using additional dummy system. The simulation was carried out by using MATLAB/Simulink environment and the designed estimator was verified using multifarious load demand changes. The results show that the estimated signal was successfully tracked the expected actual signal with minimum error.</span>

Optimal Energy Management Strategy for a DC Linked Hydro–PV–Wind Renewable Energy System for Hydroelectric Power Generation Optimization

The goal of this article is to create an intelligent energy management system that will control the stand-alone microgrid and power flow of a grid associated that includes Battery Energy Storage System, Fuel Cell, Wind Turbine, Diesel Generator, Photovoltaic, and a Hydro Power Plant. Storage systems are required for high dependability, while control systems are required for the system's optimum and steady functioning. The control, operation, and planning of both energy demand and production are all part of energy management. By controlling unpredictable power and providing an appropriate control algorithm for the entire system, the suggested energy management strategy is designed to handle diverse variations in power demand and supply. Under the TOU Tariff, the problem is presented as a discrete time multi-objective optimization method to minimize grid imported energy costs. It also maximizes earnings from surplus RE sales to the grid at a pre-determined RE feed-in tariff. Simulations were run using SIMULINK/MATLAB to validate and evaluate the suggested energy management approach under various power demand and power supply scenarios. The simulations indicate that the proposed energy management can fulfill demand at all times utilizing unreliable renewables like wind, solar, and hydroelectric power plants, as well as hydrogen fuel cells and batteries, without affecting load supply or power quality.

Investigating techno-economic effects and environmental impacts of energy renovation of residential building clusters on a district heating system

Studying energy renovation of older residential building stocks together with the surrounding district heating (DH) system is essential to fully understand implications from a reduced district heat demand and for involved actors. This study reveals the benefit of integrating the simulation and optimization tools OPERA-MILP, IDA ICE, and MODEST to investigate thoroughly the effect of energy renovation strategies on heat load supply, building and DH system-based life cycle costs (LCCs), primary energy use, and total of direct and indirect CO2 emissions. Energy renovation considered different cluster combinations of slab and tower blocks of a stock of 343 apartment buildings in two Swedish municipalities and strategies for lowest LCC and code compliance. Applied tools were thoroughly validated and verified including heat demand and load duration curves and numerical accuracy. Results with all aggregated clusters and renovation strategy for code compliance showed a reduced combined heat and power production with 35.7 GWh/a (heat) and 6.5 GWh/a (electricity), deceased primary energy use with 36.2 GWh/a and reduction of marginal CO2 emissions with 8.4 kton/a mainly from released biofuels substituting for fossil fuels in power plants, increased CO2 emissions of 0.5 kton/a with electricity production mix, and financial deficit for building owners, energy companies, and industries of respective 44, 33.9, and 2.2 M€/50a.

Autonomous Cooperative Control for Hybrid AC/DC Microgrids Considering Multi-Energy Complementarity

Multi-energy hybrid AC/DC microgrids (MGs), considering ice storage systems (ISSs), can promote the flexible integration and efficient utilization of distributed generators (DGs) and energy storage systems (ESSs), provide a reliable power supply for local loads, and achieve multi-energy complementarity and energy savings at the same time. An autonomous cooperative control of multi-energy MGs is proposed in this paper, which can realize the following targets: 1) In the energy storage period, ice storage systems and energy storage systems can absorb energy in accordance with their rated capacity. 2) In the energy releasing period, ice storage systems are first put into operation, and the rest of the equivalent cooling loads and electrical loads are shared by the energy storage systems according to their rated capacity ratio. Besides, the complete system small signal model is constructed, which can be used to analyze the features and characteristics of the system and guide the optimal design of the control parameters. Finally, the effectiveness of the proposed control is corroborated by several case studies conducted in PSCAD/EMTDC.

Review and characterisation of high-temperature phase change material candidates between 500 C and 700°C

Latent heat thermal energy storage, by using phase change materials (PCMs), is considered as a promising technology that can be integrated into concentrated solar power (CSP) applications to mitigate the load and electricity supply. Multiple PCMs connected in series has attracted considerable research attention as this configuration has the potential to improve the thermal performance compared to single PCM storage. However, this technology has not yet been deployed in commercial CSP plants. One of the major restrictions is the lack of reliable thermophysical property data for high temperature PCMs. This study gives a broad review of the experimentally verified PCMs with melting temperatures from approximately 500 °C–700 °C, applicable to CSP systems. A further twelve PCM candidates, containing low-cost sodium and/or potassium salts, were identified in this study and their thermophysical properties were experimentally evaluated. It was found that nine of the new candidates can be used as PCMs.

A novel home automation distributed server management system using Internet of Things

In this work, the Home Automation System (HAS) with low cost and wireless remote control module is designed. Internet of Things (IoT) is also implemented along with HAS for monitoring and controlling the home appliances via World Wide Web. Raspberry pi and ESP8266 module use 3.3V TTL logic and the module can be configured to connect with the existing home internet Wi-Fi router through AT commands. So, it can be connected automatically to the configured Wi-Fi network without any initialisations. For switching the load, relays are used for high load current switching capability. Raspberry pi GPIOs can deliver only 20mA of current at 3.3V. The Hall Effect sensor is connected to each load supply line to monitor the current drain by the load. Based on the current drain, the status and power consumption reduces 30% of the load.

Sistem Monitoring Penggunaan Beban Pada Proses Pengosongan Baterai 100WP Menggunakan Sensor PZEM-004T

In this study, a prototype tool of plts battery discharge monitoring system was created that aims to facilitate in monitoring plts system, solar panel battery usage monitoring system equipped with arduino microcontroller, current sensor, voltage and power that has been calibrated, so that the data acquisition system integrated in arduino microcontroller based system can be obtained in real time. From the results of the study, according to the microcontroller planner used in this final task is arduino UNO328 and sensor PZEM-004T. This monitoring tool is capable of reading voltage, current, power, cosphi and battery capacity in percent at the time of load supply.

Load prioritization technique to guarantee the continuous electric supply for essential loads in rural microgrids

Microgrid (MG) is one of the practical and best concepts to provide energy access to rural communities, where electric grid extension is not techno-economically feasible. Since the trend of load consumption is not uniform with a low load factor in a rural area, the required rating of the system becomes very high. Similarly, the generation is fixed for these MGs, whereas the load increases continuously over time. Such a system faces supply deficit issues triggering a high number of interruptions that may cause frequent blackouts. Hence, rolling blackout and load clipping techniques are preferred during the peak load period in most of the rural MGs. These issues lead to an unreliable power supply and low satisfaction level of the user. This paper presents the load prioritization technique to guarantee the continuous supply for the essential loads within the rural community. A day-ahead energy allocation technique is mathematically formulated and optimized to maximize the total hours of energy served. This technique maximized the hours of energy served to the load with higher priority followed by the load with lower priorities. From this study, it is found that the proposed strategy helps to improve the hours of energy served in the overall system, by improving the state of charge (SoC) level of the battery system. The result shows that the user satisfaction level has been improved by 5% through 100% of continuity for the essential loads.

Application of variational mode decomposition and chaotic grey wolf optimizer with support vector regression for forecasting electric loads

Accurate electric load forecasting is critical in guaranteeing the efficiency of the load dispatch and supply by a power system, which prevents the wasting of electricity and facilitates energy sustainability. Applications of hybrid intelligent computing methods and swarm-based algorithms with the support vector regression (SVR) model are very promising for solving the problem of premature convergence. This paper presents a novel SVR-based electric load forecasting model by hybridizing variational mode decomposition (VMD), the chaotic mapping mechanism, and the grey wolf optimizer (GWO) in the VMD-SVR-CGWO model to improve the solution searching experiences and to determine the appropriate combination of SVR’s parameters that improve forecasting accuracy. Numerical examples that involve two widely known electric load data sets reveal that the proposed VMD-SVR-CGWO model outperforms other models with respect to forecasting accuracy.

Optimal design of an off-grid hybrid renewable energy system considering generation and load uncertainty: the case of Zanjan city, Iran

In this paper, designing a hybrid stand-alone photovoltaic/wind energy system with battery storage (PV/WT/Batt) is presented to minimize the total cost of the hybrid system and considering reliability constraints for Zanjan city in Iran country considering generation and load uncertainties. The total cost includes the cost of the system components and load losses cost and also deficit power probability-hourly interruption probability index, which is defined as the reliability constraint. The optimal size of the system components is found using an improved crow search algorithm based on mutation and crossover operators of the genetic algorithm to prevent premature convergence. The optimal designing of the hybrid system is implemented considering the uncertainty of photovoltaic and wind resources as well as the load demand of the system based on the probability distribution functions of uncertain parameters using Monte Carlo simulation. The simulations are implemented in two deterministic and probabilistic scenarios. In the deterministic scenario, the optimal design of various combinations of the hybrid system is investigated in view of the system cost and deficit power probability probability-hourly interruption probability index based on the improved crow search algorithm with and without the cost of load loss. The results of the deterministic scenario showed that the system cost is increased considering the cost of load loss, but the system load is supplied with higher reliability. Also, the deterministic results cleared the superiority of the improved crow search algorithm compared with conventional crow search algorithm and particle swarm optimization methods. Moreover, the results of the system designing showed that considering the uncertainty, the system cost increases, and the reliability is significantly improved. The results cleared that the system cost in deterministic and probabilistic designing is obtained 1.0108 M$ and 1.210 M$, respectively for load supply equal to 153.87 MWh. So, due to the inherent nature of the uncertainty in the renewable resources power generation as well as continuous load changes, a probabilistic approach of the hybrid system designing is necessary to know the accurate cost and reliability.Article highlightsEffective performance of the proposed method in system designing with lowest cost and higher reliability.Achieving to a more reliable hybrid energy system with considering cost of load losses in designing.Increasing the system the cost and improving the reliability considering uncertainties of generation and load.

A Multi-objective Optimization Framework for Dynamic Planning of Energy Hub Considering Integrated Demand Response Program

The integrated operation of multi-carrier energy systems has attracted special attention due to its increased efficiency, improved flexibility and reduced pollution. It should be noted that accurate and optimal design of these systems will have a high impact on their optimal operation. Hence, this paper presents a multi-objective optimization framework for long-term planning of energy hub, in which equipment degradation and integrated demand response (IDR) programs are considered. The planning problem has been solved for 20 years and all short-term operation constraints have been taken into account. The problem is modeled using the fuzzy max-min method as a three-objective optimization problem, in which the objective functions include total cost, emission and hub losses. The simulation results demonstrate that the IDR program has reduced the total cost by about 9% by reducing equipment capacity and operating costs. In addition, the results illustrate that the reduction of 29% and 31% of losses and emission, led to a 49% increase in total costs. Overall, the results demonstrate that the proposed model, considering the equipment degradation and the annual load growth, leads to the optimal design of the hub structure and guarantees the supply of load until the end of the planning period.

Influence of Within-Die Transistor Characteristics Variation on FINFET Circuit Delay

The increase of within-die random variation accompanying continuing advancement of the semiconductor technology necessitates variation-aware approaches in circuit design and analysis. Statistical circuit modeling becomes an important means of realizing such approaches. In this article, analytical models for the within-die random variation of the inverter, NAND and NOR circuits are developed. To analyze random variation, the effective current concept is employed wherein circuit delay is approximated by the product of the load capacitance and supply voltage over two times the effective current. The standard deviation and mean of the circuit delay are expressed as functions of the standard deviation and mean of the effective and linear transistor currents. The developed model delivers easy means of evaluating delay variation of basic circuits. The model is verified by comparison to Monte-Carlo circuit simulations for 7-nm state-of-the-art FINFET technology. Relative error for NAND2 fall/NOR2 rise mean delay is less than 9% and for standard deviation is less than 6%. Relative error for inverter rise/fall mean delay is within 8%, however, error is larger for inverter delay standard deviation. The model is convenient for analyzing the dependence of the circuit delay standard deviation on the transistor width and the supply voltage and is useful for improving technology development efficiency in achieving target circuit performance.

Multi‐agent decentralized microgrids planning considering long‐term demand response model

Demand-side management resources, such as demand response programs (DRPs) are useful options for the reduction of energy cost according to the viewpoint of department of energy. Utilizing these resources in long-term studies like generation and transmission expansion planning (GTEP) needs long-term modeling. In this article, the GTEP was developed considering long-term model of DRPs using a cooperative game theory approach to minimize the total cost of microgrids (MGs). A two-level decision-making method was used to develop this model. On the top level, investment decisions were cooperatively made by MGs and a stochastic chance-constrained mixed integer linear programming formulation was modeled for investment decisions with operational uncertainties on the bottom level. The self-sufficiency index was also considered that guarantees supply of sensitive loads in islanding mode. Effectiveness of the proposed model was shown by numerical studies in three cases where in Case 1, load of each smart MG (SMG) will be supplied using its own resources and trading with the retail market. In Case 2, SMGs can also trade with each other in non-cooperative (profitable) approach and in Case 3, SMGs can trade with each other in cooperative approach. The total cost of SMGs was decreased in Case 2 compared to the previous case by 2.62%, which was due to the use of other SMGs' resources to provide load. Also, the total cost of SMGs was decreased in Case 3 compared to the two previous cases (2.92% and 0.3% decrease compared to the Cases 1 and 2, respectively), which was due to cooperative approach taken by SMGs in this case. In this approach, SMGs provide each other's load without additional cost and try to minimize the total cost of all the SMGs.