Search

Summary: Employing renewable resources, which act as an alternative energy source for desalination plants, has become one of the promising solutions for overcoming the water crisis. The various experimental, pilot, and research desalination projects powered by renewable resources have validated its practical feasibility in the past decade. An optimal planning scheme must be adopted to enhance these new resources' competitiveness in terms of cleanness, reliability, and affordability. Accordingly, this paper proposes a potable water production system based on water desalination. The desalination unit is supplied by a synergistic wind‐PV system integrated with an electrical energy storage system and a water tank. Also, a diesel generator is considered for power production during periods of critical power production and power/water storage. The resultant air pollution is modeled and controlled to ensure the system's cleanliness. The size of the desalination unit, water tank, associated pumps, and power supply components are optimized simultaneously to ensure a minimum‐cost plan. The proposed model exhibits linearity while preserving a predefined level of water supply reliability and a yearly emission cap. The model is implemented on a test case, and a comprehensive sensitivity analysis is performed to evaluate its effectiveness to obtain optimal results. [ABSTRACT FROM AUTHOR]

To enhance the economic viability of integrated energy systems, it is important to balance risk and reward while ensuring operational flexibility and compliance with regulatory constraints. Developing an integrated risk measurement method for energy trading in energy markets that complies with regulatory constraints adds another layer of complexity, especially when dealing with large-scale heterogeneous energy systems, such as those dominated by green hydrogen. Ensuring adherence to market regulations, grid codes, and flexible requirements requires a thorough understanding of legal frameworks and policy considerations, as well as integrating regulatory constraints into the bidding/offering strategies. To address these challenges and enable the profitable development of integrated electricity-hydrogen energy systems (IEHSs), this paper develops a risk-constrained bidding/offering self-scheduling strategy for IEHSs that allows for simultaneous trading in day-ahead energy and reserve electricity markets. The developed self-scheduling strategy regulates hydrogen and power flow in a centralized manner, taking into account the operational limits of the power sector, hydrogen fueling stations (HFSs), electric vehicle parking lots, fuel cell vehicle parking lots, and renewable energy sources. As a salient feature, the important human-related factors in the mobility sector are included in the proposed strategy to motivate private owners to collaborate with IEHSs and to accommodate the charging demand of vehicles with electricity market signals. To obtain the robust day-ahead schedule, economic risks associated with renewable power generation, calls for reserve deployment, and electricity market prices are taken into consideration. Towards this end, a stochastic adaptive robust optimization approach is proposed to control the risk of profit variability, which is solved by a nested column-and-constraint generation algorithm. The effectiveness and feasibility of the proposed strategy are verified using the modified IEEE 14-bus test system, as a standard scale of local IEHSs. The numerical results highlight the synergies impact between HFSs and the power sector, resulting in an increase in the profit of the IEHS from $101.654k to $275.078k. Furthermore, the IEHS can improve its profit margin and competitiveness by employing the tri-level stochastic adaptive robust optimization approach. This approach ensures that the IEHS is resistant to sudden changes in real-time interactions, even with an 8.14% increase in the imbalance cost. • A risk-constrained market model is proposed for integrated electricity-hydrogen systems. • An adaptive robust approach is proposed to control the risk of profit variability. • The level of access to the mobility sector is reflected in the market-oriented strategy. [ABSTRACT FROM AUTHOR]

In this paper, the multi carrier energy (MCE) systems are reviewed from different point of views including mathematical models, integrated components and technologies, uncertainty management, planning objectives, environmental pollution, resilience, and robustness. The basic of MCE systems is formed by combination of cooling, heating and power (CCHP). The natural gas and electricity are the main inputs to MCE systems and the cooling, heating, and electricity are the common outputs. The regular energy converters in the MCE systems are combined heat and power (CHP), gas boiler, absorption-electrical chillers, power to gas (P2G) and fuel-cell. The generic energy storages are electrical, heating, cooling, hydrogen, carbon dioxide (CO 2) and hydro systems. • Reviewing the design methods and topologies of multi carrier energy systems. • Studying the mathematical models of multi carrier energy systems and energy hubs. • Aspects of energy hubs: pollution, cost, resilience, robustness, flexibility. • Studying the input-output energies in multi carrier energy systems. • Reviewing the energy converters and storage units in multi carrier energy systems. [ABSTRACT FROM AUTHOR]

The delayed operation of distance relays zone-2 element for the faults at the end of the line is excessive. It reduces the fault clearing speed and therefore, is one of the main factors that can endanger power system stability. This paper proposes an impedance-based scheme for discrimination between the last 20% of the line length faults and the adjacent line faults, which are covered by the relay zone-2. The suggested non-pilot scheme uses a modified fault location formula for the accelerated zone-2 operation of distance relays. The negative- and zero-sequence components of local signals are utilized to calculate the accurate fault location after the remote circuit breaker (CB) operation. The proposed algorithm is independent of fault resistance, power flow direction, pre-fault condition, and it can clearly distinguish internal faults from the adjacent line faults. Simulation results show that the proposed method can identify the remote CB operation and thus can accelerate the tripping of zone-2 within a very short time for different fault locations, fault types, fault resistances, and load angles. Also, accurate fault location has been achieved under all simulation conditions. [ABSTRACT FROM AUTHOR]

In this work, a new elevator system created by a linear switched reluctance motor is presented. Unlike conventional linear motors, the proposed linear motor has more than one translator. Each phase in a translator generates a pulsing force; hence, the total generated force has noticeable ripple making it difficult to soft motion. In order to solve this problem, similar phases in different translators have been located in positions with specified distances together. As a result, similar force pulses would be shifted so that they can compensate together. An appropriate control strategy has been designed for the system, which can control the current, force, speed, and position simultaneously. A conventional proportional–integral controller and an adaptive fuzzy controller have been used to control the speed. In order to have a precise study, a prototype elevator system along with its control unit has been made and the obtained results have been compared with the simulation results. These results confirm that the proposed structure can significantly produce force and speed ripples. [ABSTRACT FROM AUTHOR]

The peer-to-peer (P2P) energy management in the buildings is modeled and studied by this paper. In the proposed P2P home energy management, the buildings share their energy resources with each other to supply their demands. Three individual buildings are considered, two buildings are equipped with solar panels and the other building is equipped with hydrogen storage unit. The buildings are connected to each other by power lines for P2P operation. The uncertainty of loads and solar energy are incorporated and the model minimizes the cost of solar unit, power lines, fuel-cell, electrolyzer, and storage tank. The optimization problem finds optimal power of solar system, power lines, fuel-cell, electrolyzer; optimal capacity of hydrogen storage tank; and optimal operation pattern (charging-discharging regime) of hydrogen storage system. The results demonstrate that P2P operation helps the buildings to benefit from their energy resources. • Peer-to-peer home energy management is presented to minimize the costs. • Buildings are equipped with solar units and hydrogen storage system. • Buildings share their energy resources with each other as peer-to-peer operation. • Uncertainty of load and solar energy is handled by stochastic programming. • Optimal sizing and operation are found for hydrogen storage and solar systems. [ABSTRACT FROM AUTHOR]

A new adaptive control strategy for a double‐sided linear switched reluctance motor is proposed in this work. Switched reluctance motors inherently have non‐linear dynamics that complicates their analysis and control. The Takagi–Sugeno fuzzy logic system has been used in this work to achieve an appropriate adaptive control system for the proposed linear motor. The fuzzy system has been heightened by non‐linear rule consequences and a time‐varying parameter. Updated laws have been designed to refresh the amount of the parameter consequently the suggested control system shows a stable performance in control of switched reluctance motors. The proposed control strategy is independent of the uncertainties of the motor dynamics and has an acceptable adaptability. This control method along with a conventional fuzzy logic based system have been studied on the proposed linear switched reluctance motor and their performances were compared in different performance conditions. An appropriate evaluation method has been used to compare the obtained results. The efficiency of the proposed method in different velocity commands has been examined and confirmed using appropriate simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper brings together the benefits of hydrogen and battery storage devices in the electrical network integrated with solar energy. The introduced hybrid storage system is utilized to achieve two purposes including uncertainty leveling and energy arbitrage. The volatility of solar energy and electrical-thermal loads is developed by Normal distribution. The hydrogen storage system is designed to smooth such uncertainty and storing the electrical energy in hydrogen form. Therefore, the hydrogen storage levels the uncertainties associated with solar power and loads. The battery is utilized to shift energy from pricey hours to the inexpensive time intervals and minimizing energy cost in network. The optimization programming finds optimal setting and charging-discharging pattern for both storage technologies. The seasonal profile is considered for electrical-thermal loads and solar energy. It is verified that the given hybrid storage scheme saves the cost by 117000 $/year and the solar system decreases the cost by 28%. • Network is integrated with solar panels and hybrid hydrogen-battery storage. • Solar power and loads are modeled by probability distribution function. • Battery storage shifts energy over day hours to minimize energy cost. • Hydrogen storage levels the uncertainties of solar power and loads. • Optimal setting for hydrogen and battery storages are determined. [ABSTRACT FROM AUTHOR]

The home energy management is an efficient tool to manage energy in the buildings that organizes different technologies and mathematical techniques to minimize energy cost. Home energy management often utilizes renewable energy resources to supply load demand in the building. Current home energy management systems utilize one or several of the available hardware-software capacity resources to deal with energy consumption in the buildings. However, a comprehensive model including various hardware and software capacity resources may increase the flexibility of the model. In this regard, this paper studies an efficient paradigm for home energy management in the building connected to electric grid. The proposed model forms an energy hub including the hardware resources (i.e., vehicle-to-home, wind turbine, and diesel generator) and software tools (i.e., demand response program). All the capacity resources and grid power are optimally adjusted to minimize the daily operational cost of the building as well as improvement of resiliency and self-healing. Wind energy and load uncertainty are modeled through stochastic programming. The seasonal pattern is considered for loads, prices, and wind energy. Simulation results demonstrate that operating all capacity resources minimizes the daily operational cost. When the wind energy, demand response program, vehicle-to-home, and diesel generator are not utilized, the cost is increased by 900, 230, 84, and 322%, respectively. It is also confirmed that the building not only can operate when one of the components is not connected, but also it is able to supply the demand under off-grid operation. • Home energy management is modeled on building connected to grid. • Building is supported by hardware and software capacity resources. • Demand response program, diesel generator, and vehicle-to-home are operated. • Wind and load uncertainty are incorporated by stochastic programming. • Resiliency and self-healing are studied following failures and events. [ABSTRACT FROM AUTHOR]

Thanks to the unique features, deployment of battery energy storage systems in distribution systems is ever-increased. Therefore, new models are needed to capture the real-life characteristics. Beside active power, the battery energy storage system can exchange reactive power with the grid due to the inverter-based connection. Although some previous works have considered this issue, a detailed linear model suitable for the realistic large scale distribution systems is not addressed adequately. In this context, this paper proposes a mixed integer linear programming model for optimal battery energy storage system operation in distribution networks. The proposed model considers various parts of the battery energy storage system including battery pack, inverter, and transformer in addition to linear modeling of the reactive power and apparent power flow limit. Moreover, a linear power flow model is used to calculate voltage magnitudes and power losses with high accuracy. The proposed model is applied to the IEEE 33-bus test case and the results prove the accuracy and efficiency of the proposed model. The results demonstrate that considering reactive capability of the batteries offers new benefits including voltage profile improvement, decreasing reactive power flow in the network, reducing network losses, and releasing network and substation capacity. • Model BESS considering the parts including battery pack, inverter, and transformer. • Model BESS reactive power contribution based on the 4-quadratnt capability curve. • Mixed Integer Linear Programming model for optimal BESS operation. • Considering voltage magnitudes and network losses with precise linear equations. • Achieving diverse benefits besides conventional load leveling by proper modeling. [ABSTRACT FROM AUTHOR]

This paper optimizes the operation of electric vehicles in small charging stations deployed in electrical distribution networks. The grid is equipped with small-scale charging stations rather than one large-scale charging station. In addition, photovoltaic solar panels are installed on the grid to gain renewable energy benefits. The electric vehicles operate on vehicle-to-grid mode. The charging and discharging behavior of all the electric vehicles on all buses is optimized by the given method. The presented strategy optimizes the electric vehicles operation to damp out the renewable energy intermittency and energy cost reduction at the same time. And, it minimizes the charging-discharging cycles of the vehicles batteries in order to avoid battery degradation. The proposed problem is modeled as nonlinear stochastic programming including uncertainty of solar energy and solved by GAMS software. The results demonstrate that the suggested method can properly charge and discharge the vehicle-to-grid system. The vehicles are often charged on off-peak low-cost time periods and they are discharged at on-peak high-cost time-intervals. The Intermittency of solar cells is dealt with the achieved charging-discharging pattern for vehicle-to-grid system and cost of consumed energy is minimized by energy shifting. The results validate that the presented strategy can efficaciously achieve all the intended purposes at the same time. • The distribution grid is installed with multiple small-scale charging stations. • The electric vehicles operate on vehicle to grid mode. • The grid is supported by photovoltaic solar panels with uncertain energy profile. • The charging-discharging operation of vehicle to grid is optimized. • The vehicle to grid deals with uncertainty, peak load, and energy cost. [ABSTRACT FROM AUTHOR]

Battery Energy Storage Systems can provide various applications in the distribution networks including load leveling, expansion deferral, voltage profile improvement, frequency regulation, fast reserve, and renewable energy time shift. Despite offering various applications, the BESSs are characterized with high investment costs. An optimal investment plan can justify the cots by exploiting multiple simultaneous applications. To this end, this paper proposes a novel planning model for the BESSs in distribution network wherein both load leveling and voltage profile improvement applications are extracted. The load leveling application refers to storing cheap energy at off-peak periods to deliver at peak period with high energy costs. In this way, the load profile tends to be flat and resulting lower energy cost. The voltage profile improvement is achieved by the optimal reactive power control of the inverter located between the BESS and the grid. The idea is that the inverter can allocate rated power capacity to the reactive power exchange at periods with negligible or zero active power conversion. Simulation results demonstrate that the voltage profile can improve in some degrees without increasing planning and/or operation costs. Higher degrees of improvement can be achieved at the expanse of cost increase. Also, the simulations show that the conducted load leveling results to loss reduction, peak shaving, and network expansion deferral subsequently. • Battery energy storage systems are planned under unbalanced loading condition. • Optimal charging-discharging pattern is optimized for three-phase system. • Problem minimizes energy cost, and balance unsymmetrical loading. • Optimal place, capacity, power, and charging-discharging regime of batteries. [ABSTRACT FROM AUTHOR]

• Energy storage system is planned to minimize losses in active distribution grid. • Network is installed with distributed energy resources. • The planning determines optimal sizing and siting of energy storage systems. • Optimal operation pattern for both active-reactive powers is determined. • AC power flow including reactive power is carried out. This paper deals with energy storage system (ESS) in active distribution networks. The purpose is to install ESSs on the grid to minimize network losses. The problem is expressed as an optimization programming to minimize annualized cost of losses and annualized investment cost of ESSs at the same time. The constraints of the programming are given as security constraints of the network and ESS operational constraints. The network is also equipped with distributed energy resource (DER) and its uncertainty is modeled and dealt by means of stochastic programming. Different DERs including diesel, wind, and solar resources are modeled and studied. The proposed nonlinear mixed integer stochastic programming is solved by particle swarm optimization (PSO). AC power flow is adopted to consider both active and reactive powers in the model. The ESSs are modeled including both active and reactive powers. The introduced planning finds optimal location, capacity, and power for ESSs. Furthermore, the charging-discharging regime for active power of ESSs and injection-absorption pattern for reactive power of ESSs are determined. The introduced methodology is successfully simulated on a typical distribution network. The simulation results confirm that the planned strategy properly installs ESSs on the grid and minimizes network losses. The results demonstrate that the ESSs decrease network losses about 22%. Finally, considering reactive power for ESSs results in about 24% cost reduction. [ABSTRACT FROM AUTHOR]

The fault resistance and infeeded currents from tapped transmission lines are the two main challenges to establish correct fault location estimation in multi-terminal transmission lines. Also, fault location estimation in double-circuit lines is more complicated than single-circuit lines due to the effect of mutual coupling and inter-circuit faults. This paper proposes a negative-sequence network-based method to estimate the fault location of double-circuit multi-terminal transmission lines. In the presented method, signals are measured in the relay location and then, communication links are not required as it uses only one end measurements. Also, in conventional distance relays, six elements are needed to calculate the fault location in all types of faults. Furthermore, in this method, by using only one element for each transmission line, accurate fault location can be estimated. Also, high fault resistance, mutual coupling, and infeeded currents from tapped transmission lines do not have impact on the performance of the presented scheme. To investigate the effects of the line shunt capacitances on the proposed method, a PI model of the transmission lines is used in all the investigations. Simulation results carried out using MATLAB software indicate that the proposed scheme is able to produce excellent performance for the fault location estimation. [ABSTRACT FROM AUTHOR]

This paper designs an off-grid charging station for electric and hydrogen vehicles. Both the electric and hydrogen vehicles are charged at the same time. They appear as two electrical and hydrogen load demand on the charging station and the charging station is powered by solar panels. The output power of solar system is separated into two parts. On part of solar power is used to supply the electrical load demand (to charge the electric vehicles) and rest runs water electrolyzer and it will be converted to the hydrogen. The hydrogen is stored and it supplies the hydrogen load demand (to charge the hydrogen-burning vehicles). The uncertainty of parameters (solar energy, consumed power by electrical vehicles, and consumed power by hydrogen vehicles) is included and modeled. The fuel cell is added to the charging station to deal with such uncertainty. The fuel cell runs on hydrogen and produces electrical energy to supply electrical loading under uncertainties. The diesel generator is also added to the charging station as a supplementary generation. The problem is modeled as stochastic optimization programming and minimizes the investment and operational costs of solar and diesel systems. The introduced planning finds optimal rated powers of solar system and diesel generator, operation pattern for diesel generator and fuel cell, and the stored hydrogen. The results confirm that the cost of changing station is covered by investment cost of solar system (95%), operational cost of diesel generator (4.5%), and investment cost of diesel generator (0.5%). The fuel cell and diesel generator supply the load demand when the solar energy is zero. About 97% of solar energy will be converted to hydrogen and stored. The optimal operation of diesel generator reduces the cost approximately 15%. • Off-grid charging station is designed for electric and hydrogen vehicles. • Charging station is powered by solar panels and supplies electric vehicles. • Solar energy runs water electrolyzer to produce hydrogen and hydrogen is stored. • Stored hydrogen is used to supply the hydrogen vehicles and fuel cell. • Fuel cell and diesel generator deal with uncertainties of solar energy and loads. [ABSTRACT FROM AUTHOR]

A framework is planned to supply electrical and thermal loads by joint application of a hydrogen storage system (HSS) and a fuel cell. The system, including electrical and thermal loads, is connected to the upstream network. The bidirectional operation is defined for the system, and the system can buy energy from the grid or sell energy to the grid. A water electrolyzer is applied to produce hydrogen from water and store electricity in the form of hydrogen. The stored hydrogen supplies the thermal loads, as well as the fuel cell. The electrical loads are directly connected to the grid and are supplied by the grid. The electricity is received from the fuel cell at hours 17 to 22. When the price of electricity is high, the electrical loads can receive their power from the fuel cell rather than the grid. Additionally, any excess electricity may be sold to the grid. The uncertainty in the thermal and electrical loads is modeled and formulated as stochastic programming. The hydrogen is fed to the fuel cell and the thermal loads. The proposed model minimizes the daily operational cost of the system. The results demonstrate that the daily operational cost of the system is $22.274 USD/day. The bidirectional operation reduces the daily operational cost by about 79%. The unceratinty increases the cost by about 15%. [ABSTRACT FROM AUTHOR]

Abstract This paper presents an efficient framework for converting renewable energy to gas and reducing Carbon dioxide (CO 2) footprint at the same time. The problem is presented in two levels. The first level is a minimization programming that minimizes operational cost and CO 2 of generators. The CO 2 is forwarded to the second level. In the second level, Carbon Capture and Storage (CCS) is designed to capture CO 2. The CO 2 is combined with Hydrogen and makes Methane (CH 4). The required Hydrogen is obtained from water electrolyzer that is supplied by the solar system. The capacity and size of water electrolyzer, solar system, and CCS is designed by the planning in the second level while this programming maximizes profit from selling Methane. As a result, the first level presents minimization programming (i.e., minimizing cost and CO 2) and the second level presents maximization programming (i.e., maximizing profit). The programming is developed taking into account solar uncertainty. The stochastic programming is implemented to cope with uncertainties. The problem is formulated as binary mixed integer linear programming and solved by GAMS software. The proposed power to gas (P2G) procedure efficiently designs proper solar system and deals with intermittency of solar energy, reduces CO 2 footprint, maximizes profit, and minimizes operational cost of generators at the same time. Highlights • Operational cost and CO 2 is minimized for nonrenewable generators. • Considering Carbon tax operates low-cost and low-polluting units. • Optimal size of solar system is designed equal to 190 MW. • Annualized profit of power to gas system is 1.617 Million $ per year. • Carbon capture system captures 1621.5 (kg/day) of CO 2. [ABSTRACT FROM AUTHOR]

This paper presents a multilevel energy management system between homes and the electrical grid. The proposed model includes three levels: the first level is made of the utility grid, and it can send or receive energy from the second level. The second level is formed as a common level that is equipped with a wind turbine, battery energy storage, and a diesel generator. The second level can exchange energy with both the first and third levels. The third level is formed with a set of buildings with different loading patterns, and some of them are also equipped with solar panels. The third level can send or receive energy from the second level. The second level is a common level between two other levels. The proposed planning minimizes the cost of consumed energy by houses in the third level through optimal utilization and management of all levels. The problem optimizes the power between levels 1 and 2, the power between levels 2 and 3, the charging-discharging pattern of the battery in level 2, and the operation pattern of the diesel generator in level 2. The plan optimally utilizes both wind and solar resources (in levels 2 and 3) to minimize the energy cost and deals with their intermittency nature by means of stochastic programming. The plan is also designed to operate under contingency conditions when the utility grid (first level) is out of access. In such a situation, the problem utilizes the available technologies in levels 2 and 3 (i.e., wind, solar, battery, and diesel) to supply the houses in the third level. The diesel generator plays a major role under contingency and emergency conditions to maintain the resiliency of the system. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a unified model for home energy management. The proposed model optimizes the cogeneration of wind, solar, and battery storage units. The introduced tool considers electric and hydrogen vehicles and provides optimal charging pattern for them. The water electrolyze is also modeled to produced breathable oxygen and hydrogen from water. As well, the load modeling options such as adjustable and interruptible loads are included in the planning in order to increase the flexibility and adeptness of the proposed energy management system. The uncertainties of wind and solar powers are included resulting in a stochastic programming. The proposed stochastic optimization problem is mathematically expressed as a mixed integer linear programming and solved by GAMS software. The problem minimizes cost of energy consumption in the building subject to the operational constraints of wind unit, solar panel, battery system, loads, electric-hydrogen vehicles, and electricity grid. The proposed test building is studied under two states including connected to the electrical grid and disconnected from the gird (i.e., islanding mode or NetZero energy home). The impacts of the proposed planning on the environmental pollution are also considered and simulated. The results verify that the proposed strategy can successfully utilize wind-solar-battery units to supply the load, charging the electric-hydrogen vehicles, and reduction of the pollution. As well, it is demonstrated that the operation of the home under islanding mode is completely different from the connected state. Highlights • Hybrid wind-solar-battery is modeled and optimized. • Electric and hydrogen vehicles are included and optimized. • Adjustable and interruptible loads are considered and managed. • Uncertainty of wind-solar is included and stochastic problem is carried out. • The environmental pollution are studied and simulated. [ABSTRACT FROM AUTHOR]

An increasing penetration of renewable power resources (particularly wind farms) is observed in power systems during the last years. There is a frequency control concern with these kinds of power resources because they do not provide the so-called inertial response. Since the doubly fed induction generator (DFIG) equipped with Variable Speed Wind Turbine (VSWT) is the mostly used type of generator in wind farms, this paper proposes a new control approach allowing the DFIG to participate more efficiently in the power system frequency control. The approach consists of three steps: (1) Estimating the active power mismatch Δ P 0 between the active electrical power and the mechanical power which appears at the first moment after the perturbance at the DFIG, (2) based on Δ P 0 determine the electrical power reference P ref of the active power controller, and (3) appropriate removal of Δ P 0 if the power frequency deviation is above a prescribed value and the automatic generation control (AGC) is activated. The obtained simulation results on a simple 2-bus system and on IEEE 14-bus test system show that the proposed approach has several advantages over existing approaches. [ABSTRACT FROM AUTHOR]

• Proposal has distance protection scheme for the lines connected to the PV plants. • The proposed scheme is independent of PV plant parameters and fault resistance. • In this method the exact fault location is also calculated. The output power of the inverter-interfaced photovoltaic (PV) plant has the continuous variations due to the properties of PV modules and environmental conditions. These variations fundamentally affect the performance of the conventional distance protection during nonmetallic faults. This paper proposes a positive sequence network-based distance protection scheme for the transmission lines connected to the PV plants. Different from the adaptive mho and quadrilateral characteristics, the proposed scheme is independent of PV plant parameters and fault resistance. In this method, the Thevenin equivalent parameters of the grid seen from the PV plant are calculated. Thevenin equivalent parameters are calculated using prefault current and voltage data at the local terminal, without additional costs related to the requirements of the communication channel. The obtained parameters are used in the fault resistance compensation. Furthermore, by eliminating the fault resistance effect on the relay impedance, the exact fault location is also calculated. Since the fault line impedance formula is derived only from the positive sequence network, the proposed method is applicable to different grid codes. The efficiency of the proposed scheme is evaluated on the Western System Coordinating Council (WSCC) 9-bus and IEEE 30-bus test systems. The obtained simulation results verify the validity of the proposed scheme under various fault and PV plant conditions. [ABSTRACT FROM AUTHOR]

This paper presents a novel study on the multi-objective energy audit and management of a proposed plus-ZEB covered by a green roof in Tehran's climate. The planning impact of changing a proposed plus-ZEB to an intensive plus-ZEB is also evaluated. The planning is performed for one year based on Tehran's accurate urban climate data. The plus-ZEB consists of renewable and non-renewable resources like CHP, boiler, furnace, photovoltaic, solar water heater, wind turbine, air to the water heat pump, electric heat pump, and chiller boiler units in addition to energy storage to supply diverse electrical, thermal, and cooling demands of the presented building. The planning's functions are included in the total cost and emission of the plus-ZEB. The objective function prioritization is also participated to show the planner's decision on the function. Also, diverse solvers are implemented to evaluate and compare and validate results. The problem is simulated in energy plus to assess the amount of demands, construction materials, and energy audit issues; then, the results transfer to the GAMS software for energy management of the proposed plus-ZEB by utilizing a green roof. The problem in GAMS is modeled as a real mixed-integer programming (RMIP) and solved using the augmented epsilon constraint method (AEC). The final results show the significant effect of the proposed planning on reducing the cost and emission of the plus-ZEB, in which the total cost and pollution are decreased by about 7.4 % and 10.6 %, respectively. [ABSTRACT FROM AUTHOR]

The presence of flexible ac transmission system (FACTS) controllers in transmission lines causes mal-operation of distance relays. The series-shunt FACTS devices have larger influence on the performance of the relays compare to the other FACTS controllers. Furthermore, high-resistance fault is another factor that relay become under-reach and cannot correctly identify the fault. In this paper, a method is provided based on synchrophasors to eliminate the effects of unified power-flow controller (UPFC) and fault resistance on the distance relay. In the presented method, the data of voltage and current signals of buses will be sent to system protection center (SPC). In SPC, an algorithm is provided based on active power calculation in buses which is able to eliminate the effects of both mentioned factors. The main advantage of the proposed method, in addition to the simplicity of the algorithm, is the ability to operate in all types of faults and in high-resistance faults. Furthermore, a technique is presented in this paper to calculate UPFC data. A comparison has been performed between this technique and another method where UPFC data is directly transmitted to SPC by communication channel. In modeling of UPFC, detail model is used based on 48-pulses voltage source converters. [ABSTRACT FROM AUTHOR]

Distance relays are often used in the protection of the transmission lines connected to the wind farms. The distance relay using the transmission line impedance measurement identifies the type and location of the fault. However any other factors that cause the failure of the measured impedance, makes the relay detect the fault in incorrect location or do not detect the fault at all. One of these factors is the fault resistance which directly increases the measured impedance by the relay. One of the methods to eliminate relay under-reach effect is using of the trip boundaries. Trip boundaries are changing with wind variation and following with output power of the wind farms. Therefore, trip boundaries should continuously change proportional by the wind speed. In this paper, a method is provided based on the combination of distance and differential protection. In this method, using active power calculation in both ends of the transmission line, fault resistance is calculated and its effects are directly deducted from the calculated impedance by the relay. Therefore, variable trip boundaries are not needed anymore. Also in this method, unlike the technique that the trip boundaries are used, the exact location of fault and its distance from the relay also is calculated. Detailed model of a doubly-fed induction generator (DFIG) driven by a wind turbine is used in the modelling. Results of studies show that the presented method eliminates properly the mal-operation of relays under all different fault resistance conditions. [ABSTRACT FROM AUTHOR]

Due to the increasing hydrogen demands, a strong sense of commitment has recently been found to take advantage of the economic opportunities offered by power-to-hydrogen (P2H) units considering the high penetration of renewable energy sources (RESs). Deriving a market participation model for extracting green hydrogen with special attention to the grid code requirements is a fundamental challenge that has not yet been addressed. Motivated by this challenge, this paper presents a stochastic security-constrained optimal power flow (SSC-OPF) model to optimally allocate P2H units in renewable-dominated regional power grids. The main aim of the proposed planning model is to maximize the profit of power grid operators by extracting as much green hydrogen as possible and delivering it to the downstream industries. The presented model covers essential operational constraints, reserve adequacy issues, conservation voltage reduction, and uncertain behavior of demands and RESs to ensure the realistic operation of power grids. Moreover, the net present value of the proposed model is calculated to determine the profitability rate of using P2H units according to business models. The applicability of the proposed model is examined on the extended IEEE 30-bus and IEEE 118-bus test systems. The simulation results show that the use of P2H units in combination with RESs not only makes power grids more profitable but also improves the technical parameters. [Display omitted] • A stochastic security-constrained problem is used to allocate P2H units in power grids. • The impact of practical operating conditions is examined in P2H units planning problem. • NPV method is used to determine the profitability rate of using P2H units in power grids. [ABSTRACT FROM AUTHOR]

This paper presents a secondary voltage control that applies discrete controllers to regulate the voltage in the Hydro-Québec power network. Firstly, an artificial intelligence methodology is presented for partitioning the Hydro-Québec network into smaller and separated areas. The proposed methodology uses a self-organizing map (SOM) and is based on an original concept in which competitive and learning vector quantization (LVQ) neural networks are used to partition the power system. Secondly, pilot buses are chosen to represent the most controllable buses in each area. Finally, discrete controllers are designed to overcome and avoid propagation of disturbances on the network. The proposed methodology and the results obtained with the Hydro-Québec network are presented in this paper and show the effectiveness and performance of the controllers. [ABSTRACT FROM AUTHOR]

This study proposes a secondary voltage control based on a systematic approach that decomposes a transmission system network into several areas. Network decomposition and pilot buses selection are fundamental in area voltage control. The proposed decomposition approach is hierarchical with two levels of decomposition. The first level is based on the clustering analysis; at this level, the appropriate number of areas is determined. Only several buses (named as control buses) are assigned to each area at this level. The aim of the second level is to assign the remaining buses (named as load buses) to a given area among the already obtained areas in the first level. Buses classification at this level is based on proximity analysis. The control uses reactive power compensation at critical buses, as well as at pilot buses to eliminate voltage violation resulting from disturbances at these buses. For pilot buses selection, a pilot index is proposed. The critical buses are determined based on the sensitivity factors. The IEEE 39‐bus and IEEE 118‐bus are used to illustrate the performance of the proposed approach. [ABSTRACT FROM AUTHOR]

As an achievement of innovations resulting from partitioning mechanisms, these mechanisms can contribute to the more flexible operation of power systems in local communities. The ever-increasing frequency and severity of unexpected real-time failures have created challenges for partitioned-based power system operators, affecting each partition's resiliency. With this in mind, this paper presents an adaptive local operation strategy (ALOS) for resilient scheduling of the renewable-dominated partitioned-based power systems under normal and islanding modes in a decentralized manner. The main objective of the developed ALOS lies in reaching an affordable preparedness level in each partition to deal with unscheduled islanding mode, which can occur subsequent to real-time failures at common lines between adjacent partitions on transmission level. To this end, a set of resilience-target constraints is presented to prepare sufficient spinning reserve capacity in each partition to ensure continuity of supply during islanding mode. The proposed strategy is formulated as a two-stage stochastic mixed-integer linear program (MILP), and the nested formation algorithm is employed to execute it in a hierarchical fashion based on the privacy-preserving protocols. Besides, the tri-state compressed air energy storage (CAES) system is also included in the proposed strategy to mitigate the negative consequences caused by real-time failures and uncertain sources. Numerical results conducted on the IEEE 30-bus test system reveal that the proposed ALOS can enhance the resilience of each partition in responding to unscheduled islanding mode by efficiently utilizing all available capacities on the generation side. Furthermore, the DIgSILENT PowerFactory is used to identify the worst possible series of events and to evaluate the effectiveness of the proposed resilience-promoting proactive strategy in dealing with these events. • A local operation strategy is presented for resilient operation of partitioned power grids. • A decentralized approach is used to coordinate power trading among various partitions. • The nested formation algorithm is employed to execute a two-stage stochastic program locally. [ABSTRACT FROM AUTHOR]

This paper presents coordinated secondary voltage control based on partitioned power network and decentralized controllers designed for each region. The elements of control are installed on pilot buses (critical point for voltage control in each region). The aim is coordination among elements of control in each region or between different regions to regulate voltage of buses and increase the security of the power network. The elements of control are considered as nodes of a graph and reactive power will be transferred through edges of this graph. This gives capability of transfer of reactive power between regions in case of voltage violations in a special region that cannot be regulated by controllers installed on that region. The control uses decentralized controllers to eliminate voltage violations resulting from load variations and disturbance in the power network. The methodology is applied to the IEEE 118-bus network. The results show and verify the performance of coordinated control scheme to regulate the voltage and to avoid propagation of contingency between regions. [ABSTRACT FROM PUBLISHER]

This study presents a secondary voltage control based on an optimisation algorithm to locate the control buses and regulate the voltage. Control buses are the buses where compensators will be installed on these buses to regulate voltage and avoid voltage violations. Firstly, partitioning algorithm using fuzzy C‐means has been implemented on the power network. Partitioning techniques split the power system into regions to avoid the propagation of disturbances between regions by using local controllers. Then, a number of buses are labelled as control buses displaying the critical point for voltage control in each region. The control algorithm is a decentralised controller which tries to eliminate voltage violations in power system resulting from load variations and disturbances. The decentralised controllers are implemented using flexible AC transmission system (FACTS) devices such as static synchronous compensator (STATCOM). The methodology is applied to the IEEE 118‐bus network. The results show the performance and ability of the partitioning algorithm and bus control selection to regulate the voltage and avoid propagation of disturbances between regions. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to demonstrate the impacts of mobile battery and diesel DG in integrated electrical-heating networks for promoting the resilience, self-adequacy, load restoration, power quality as well as reducing the load shedding and operational cost. The case study is IEEE 33-bus electrical system with both the electrical and heating demands. Several buses of the grid are integrated with combined heat and power (CHP). The battery is moved between the buses hourly and the diesel DG is moved seasonally. The transfer time between origin and destination buses is considered in the given model. The electric network feeds three regions (i.e., three different loading patterns) including residential, industrial and agricultural areas where the major activity of the industrial loads is at night due to low energy price and the major activity of the agricultural loads is in the spring and summer. The outage of electricity and natural gas (NG) are two faults that are imposed on the network in order to evaluate the resilience and load restoration. The demand response program (DRP) is included in the model. Both the active and reactive powers are considered for battery, diesel DG and CHP. Several cases are simulated, studied and compared like fixed, mobile and mixed fixed-mobile locations for energy resources. The simulation results show that the proposed model reduces the total annual cost by 16.5% while the other costs such as purchased energy, NG and losses are reduced by 16.5%, 22.9% and 21.5%, respectively. The self-adequacy of network is increased by 2.5 h and the electrical-heating load restorations are increased by 36% and 38%, respectively. • Application of mobile battery for load restoration in electrical-heating system. • Optimal movement of disel DG and battery to minimize operational cost. • Modelling the shiftable/curtailable/critical loads and load shedding strategy. • Incorporating the uncertainty behavior of all loads and renewable resources. [ABSTRACT FROM AUTHOR]

• The proposed non-pilot scheme is based on the accurate fault location estimation. • This method can be applied to both single- and three-pole CB operation modes. • The proposed method is independent of the line impedance variations and remote source impedances. In multi-zone distance relays, zone-2 has an intentional time delay which is considered for the coordination among the other distance relays. This delay is unnecessary for faults that occur at the end of the protected line and causes the fault to be cleared after hundreds of milliseconds. On the other hand, high-speed fault clearance is an important issue of ensuring the stability of the power system. To address the above problem, an auxiliary fault location (AFL) element based on the proper Kirchhoff voltage law (KVL) loop in the negative- and zero-sequence circuits are designed for distance relays. The input signals to the AFL are the measured signals by local distance relay. The proposed AFL can reduce the zone-2 intentional time delay from 18-28 cycles to 3 cycles. In addition to this, AFL can improve limitations associated with similar methods such as the dependence of these methods to the fault resistance, remote source impedances, and line parameters variation. The AFL can accurately calculate the fault location, before issuing a trip command. Furthermore, to increase the accuracy, the shunt capacitances of the line are compensated by the algorithm. Numerous PSCAD simulation studies verify the effectiveness and applicability of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper investigates a secondary voltage control based on a graph partitioning method. The method divides the power system into regions to eventually prevent the propagation of disturbances and to minimize the interaction between these regions. The optimized number of regions is found based on the bus voltage sensitivity to disturbances being applied to loads in each region. Then, a number of representative buses are labelled as pilot buses displaying the critical point for voltage control in each region. The control uses decentralized controllers to eliminate voltage violations resulting from load variations and disturbances in the system. The decentralized controllers are implemented by fuzzy logic which is trained via offline simulations; they inject required reactive power into the regions to correct voltage violations. The methodology is applied to the IEEE 118-bus network. The results show the performance and ability of graph partitioning and fuzzy secondary voltage control to regulate the voltage and to avoid propagation of disturbances between regions. [ABSTRACT FROM PUBLISHER]

Abstract: This paper considers the problem of creating a coordination algorithm for a team of mobile robots. The goal for coordinating a group of mobile robots is to create an efficient architecture and control algorithm that enables them to work both individually and in meaningful robot formations. This is achieved by employing coordination and trajectory following techniques, and the knowledge derived by the localization of the robots from their environments. The model use a combination of the Lyapunov technique and graph theory embedded in the virtual structure. In this way, the knowledge derived by the localization of the robots in the group allows for efficient coordination and trajectory following, which can then create useful robot formations. The results obtained from experiments, using three mobile robots in differing formations, show the performance of the controller and the coordination algorithm. They also demonstrate the ability of the algorithm to recover from position sensor measurement errors and temporary delays or failures in the communication, which may cause the robots to momentarily abandon their place in the group formation. [Copyright &y& Elsevier]

Abstract: This paper presents a control strategy for the coordination of multiple mobile robots. A combination of the virtual structure and path following approaches is used to derive the formation architecture. A formation controller is proposed for the kinematic model of two-degree-of-freedom unicycle-type mobile robots. The approach is then extended to consider the formation controller by taking into account the physical dimensions and dynamics of the robots. The controller is designed in such a way that the path derivative is left as a free input to synchronize the robot’s motion. Simulation results with three robots are included to show the performance of our control system. Finally, the theoretical results are experimentally validated on a multi-robot platform. [Copyright &y& Elsevier]

This paper considers battery swapping and energy resilience in the building integrated with electric vehicle (EV), reserve battery, and solar energy. The building is able to continue the operation under both the off-grid and grid-tied states. The EV and reserve battery are coordinated for battery swapping strategy, energy cost reduction, and energy resilience improvement. The battery swapping strategy enables the EV to leave the building at each hour of the day when needed by the owner. Such flexible battery swapping model makes the EV available for owner at all time periods of the day even when the EV has just arrived to the building with empty battery. This strategy increases the acceptance rate of EVs and deals with the concerns regarding lengthy charging times. The coordinated EV and reserve battery also enables the system to supply the load demand following events like outage of solar or grid energy. Such model significantly improves the energy resilience in the given home energy management system. The solar power uncertainty is modeled by scenarios of performance and the problem is solved under set of uncertainty scenarios. The super capacitor is applied to remove the solar uncertainties under off-grid operation. The results including various cases verify that the enhanced battery swapping strategy is able to improve the resilience and reduce the energy cost. • Vehicle-to-home operation is modeled based on battery swapping mechanism. • Coordinated operation is realized between electric vehicle and reserve battery. • Battery swapping enables the electric vehicle to leave the building at each hour. • Coordinated model reduces the energy cost and improves the energy resilience. • The energy system is resilient under consecutive events at all hours of the day. [ABSTRACT FROM AUTHOR]

• A pilot scheme to enhance the fault location for TCSC compensated line is proposed. • In this method only the current data at remote-end should be sent to the local-end. • The proposed algorithm is independent of fault resistance, and TCSC parameters. This paper introduces a communication-aided scheme to enhance the fault detection, and fault location calculation for a thyristor-controlled series capacitor (TCSC) compensated transmission lines. In the proposed method only the current data at the remote-end should be synchronously sent to the local-end. Since the remote-end voltage data do not use in local-end, compared with the conventional pilot impedance-based protection schemes, the proposed method significantly reduces the requirement of data transmission bandwidth. The proposed algorithm is independent of fault resistance, power flow direction, and pre-fault condition. In the proposed method the TCSC parameters are not utilized in the derived fault location formula and as a result, the performance of the proposed method is not impacted due to variations in TCSC parameters. Several major factors are taken to investigate the accuracy of the proposed method, including measurement errors and power swing conditions. The simulation results prove the high accuracy and acceleration of the proposed scheme during all fault cases. [ABSTRACT FROM AUTHOR]

In this paper, a new short-term daily scheduling model is proposed and formulated. In the proposed model, thermal power plant will be optimally scheduled in a system with water desalination units. For the thermal units, various cost terms including start-up, shut-down, and also fuel cost are considered and modeled. Also, thermal dynamics of the plants including power generation ramp-up and ramp-down, minimum up and down time limits, and start-up and shut-down ramps are considered. In addition, energy storage batteries as well as water storage tanks of the desalination units are modeled. The proposed model is a mixed integer linear programming (MILP) for simultaneous scheduling of thermal power plants and desalination units while considering transmission constraints. Power and water balance at the network buses in addition to the power flow constraints of the lines are considered. Various membrane and thermal desalination methods are modeled. The proposed model is implemented on a test case and the simulation results show a significant reduction in the system operating costs as well as improved performance of both the thermal power plants and the desalination unit. The proposed scheduling method can be used for the various future studies of joint power-water production and coordination. • Model, design, and optimize a joint water and energy supply system for a remote island • Considering reverse-osmosis, multi-stage flash, and multi-effect distillation • Supplying electrical and thermal energy by a hybrid solar-wind renewable system • Balance renewable energy production with the peak load demand using battery energy storage [ABSTRACT FROM AUTHOR]

Water and energy are one of the most primitive and prominent needs of each society. Supplying these requirements to island residents is especially more complicated and costly due to limited access to the urban utilities. On the other hand, investment cost of the renewable energy resources is progressively decreasing. In this context, this paper model, design, and optimize a joint water and energy supply system for a remote island without access to the utility networks. Freshwater will be produced by means of the desalination units. Various desalination processes including reverse-osmosis, multi-stage flash, and multi-effect distillation have been considered and compared to select optimum method in terms of technical and cost factors. The required electrical and thermal energy demanded by the consumers and also desalination process is supplied by a hybrid solar-wind renewable system. A battery energy storage system is used to balance time period of the renewable energy production with the peak load demand. In addition, diesel generator units are considered to enhance reliability level of the supply system. Results of the simulations demonstrate that the proposed approach will optimally determine capacity and characteristics of the system components and also desalination method. • Model, design, and optimize a joint water and energy supply system for a remote island. • Considering reverse-osmosis, multi-stage flash, and multi-effect distillation. • Supplying electrical and thermal energy by a hybrid solar-wind renewable system. • Balance renewable energy production with the peak load demand using battery energy storage. [ABSTRACT FROM AUTHOR]

• This method is only based on the current data in relay location. • The proposed method is completely analytical. • A negative-sequence based approach used to fault location estimation. This paper introduces an accurate fault location algorithm for double-circuit transmission lines compensated by Static Var Compensator (SVC). The proposed algorithm is based on the negative-sequence circuit of the transmission system and it depends only on the current data available from one end of the line. Since only magnitudes of current signals are required, there is no need for data synchronization. The proposed technique uses the COMTRADE fault files available from digital distance relays and it can effectively locate the all types of unbalanced faults, regardless the high fault resistance, effect of mutual coupling and SVC current injection information. As one formula can be used for all types of fault, classification of fault types and phase selection are not required. The shunt capacitances of the line are considered by utilizing the distributed parameters model of the transmission lines. The proposed algorithm is rigorously investigated for various fault scenarios in SVC compensated transmission system. The simulation cases in the MATLAB environment verifies that the proposed scheme has excellent performance. Test results are compared with a conventional fault location technique to illustrate the accuracy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Today, renewable resources have become one of the main pillars of electricity generation because of the constant reduction in their costs. In this regard, wind energy possesses the highest share in installed capacity and total energy output. Adopting a well-structured planning model is one of the most effective ways to further reduce costs and been the focus of research in the past decades. The previously models use a generic model for the wind turbine and its related parameters while only the optimal number is determined. In this context, this paper presents a novel approach for optimally planning of wind-diesel-battery systems which optimizes the wind turbine technology as a decision variable from the different types already commercially available. For this purpose, an optimization problem is introduced with the possibility of choosing a single type of turbine technology. The proposed model is then modified to optimize and simultaneously select multiple different wind turbine technologies. Results of the case study demonstrate a significant reduction in the planning cost, namely above 5 percent depend on the wind speed. Furthermore, the total yearly energy generated by diesel generator is decreased by 700 kWh, meaning higher renewable penetration and less emissions. • New approach for modeling and optimization of turbine technology selection. • Possibility to select and optimize multiple different turbine technologies. • Linear planning model without convergence problems and easily solvable. • Flexible and interactive model in terms of planning preferences. • Considerable reduction in the planning cost and pollutant emissions. [ABSTRACT FROM AUTHOR]

• A novel model for hybrid wind-PV-diesel-battery system design. • Modeling wind turbine technology selection. • Integration and optimization of wind turbine technology selection. • Lower planning cost by optimal turbine selection. • Linear model easily solvable and without convergence problems. Electric power demand in the remote areas can be effectively supplied by the renewable resources. In this context, hybrid wind-photovoltaic systems have attracted more attention due to the system cost reduction and higher level of the supply reliability. In the past decade, various models have been proposed for optimal sizing of the system components with various objectives. In the previous studies, a typical wind turbine for capturing wind power is considered. In this case, changing turbine parameter will change results of the problem to a large extent. In other word, selecting optimal turbine technology is not considered as an influential decision variable. In this paper, a novel formulation is proposed to incorporate turbine technology selection in the optimal hybrid wind/photovoltaic renewable energy system design. The proposed model will select the optimal turbine model among a set of the choices. Also, optimum size of the other equipment according to the problem conditions will be determined. Results of testing the model in the various scenarios demonstrate efficiency and also functionality of the proposed model in real cases. [ABSTRACT FROM AUTHOR]

An optimal energy management is addressed in the residential building. The residential building is equipped with renewable energies including wind turbines and solar panels. The uncertainty of renewable energies is modeled by stochastic programming. The demand response program is simultaneously adopted to handle such uncertainty and reducing the energy cost. In this respect, four different loads are modeled in the building including interruptible, constant energy, constant power, and uninterruptible loads. The aforementioned loads are properly adjusted and dispatched for minimizing the energy cost as well as to deal with renewable energy intermittency. The bidirectional operation is modeled for the building and it can send energy to the grid or receive it from the upstream network. The results verify that the introduced model can efficiently harvest all possible energy of the wind-solar system, handle the uncertainty, minimize the cost, and operate as off-grid. All of these purposes are achieved by optimal dispatching and adjusting of the loads through the proposed demand response program. • Building is supported by coordination of various energy capacity resources. • Energy capacity resources are wind, solar, and demand response program. • Bidirectional and off-grid operations are admitted for building. • Demand response program includes different loading models and operations. • Uncertainty is incorporated by stochastic programming and demand response program. [ABSTRACT FROM AUTHOR]

• Hybrid solar-hydro-hydrogen-fuelcell is developed in net zero energy building. • Solar power, hydro power, and load demand modeled by Gaussian distribution. • Hydrogen storage and fuelcell smooth out energy volatility and uncertainty. • Solar-hydro systems compensate each other during summer and winter. • Optimal power and operation pattern is found for hydrogen, fuelcell, solar units. The net-zero energy buildings are often supplied by renewable resources and energy storage systems. These energy resources have different seasonal and daily patterns of power production. Their output power is also uncertain. This paper aims to study these issues including daily-seasonal operation patterns, uncertainty, and cogeneration of various renewable resources and storage systems. These issues are investigated at net-zero energy building supported by renewable resources (i.e., solar energy, hydro energy, and fuelcell) and energy storage systems (i.e., hydrogen storage system). The uncertain parameters of the model are solar-hydro-load powers. The model minimizes the investment cost on solar system. The plan finds optimal sizing and operation for solar, hydro, hydrogen, and fuel-cell. The cooperation of hydrogen storage and fuelcell is optimized to level the uncertainty. The surplus of energy is fed into water electrolyzer to produce hydrogen and the fuelcell consumes the hydrogen to produce electricity. The seasonal operation is dealt by cogeneration of hydro-solar systems. The proposed plan installs 73 kW solar panel. The hydrogen storage system is charged at hours 7–17. When hydro power is increased to 39 kW, the building does not need the solar energy. The proposed model decreases the Carbon Dioxide by about 39546 kg. The model also reduces the total cost by about 50.3%. [ABSTRACT FROM AUTHOR]

• The overcurrent relay settings are coordinated for minimum operating time. • The developed technique for relay operation is simulated in MATLAB software. • The simulation are confirmed and verified by experimental laboratory tests. • The settings of overcurrent relay are applied as backup of each other. • The model protects the system when one of the settings fails to operate. Industrial overcurrent relays such as MiCOM P123 (overcurrent and earth fault protection relay) often offer three individual options for separate settings. These settings can be separately tuned and such ability can be utilized to apply the relay as backup of itself. In this system, not only the other relays operate as backup of the current relay, but also settings of the relay operate as backup for themselves. In order to verifying such ability, this paper tunes the settings of MiCOM P123 overcurrent relay as backup of each other to make the non-standard characteristic for overcurrent relay. In the developed model, the first setting of the relay is set on normal inverse (NI) curve, the second setting on very inverse (VI) curve, and the third setting on the instantaneous definite minimum tome (DMT) type. The operating area of the relay is divided into two areas. In the first area, the VI curve operates as backup of NI and in the second area, the NI curve operates as backup of VI. The third setting also operates as backup of both the first and second settings. The system is implemented in the protection laboratory as well as it is simulated using MATLAB software. The simulation outputs are verified and confirmed by the experimental tests. The results confirm that the proposed model has two advantages. The first achievement is to reduce the tripping time by about 5%. And he second advantage is to increase the protection level when one of the settings fails to operate. [ABSTRACT FROM AUTHOR]

Renewable energies and electrical loads usually show short-term variations in their energy profiles and they need to be precisely modeled in terms of time-scale and uncertainty. Correlation of time-scale, uncertainty, and simulation time must be studied to make an optimal tradeoff between these parameters. This paper aims to deal with this issue and it studies the correlation of time-scale and uncertainty in the renewable energy simulation. The different time scales including 15, 30, and 60 min are modeled and simulated. Uncertainty of electrical loads and wind energy are also incorporated. The introduced model is simulated and investigated on a typical building for energy management. Energy management tool is simulated under multiple time-scale patterns and wind-load uncertainty. The model is expressed as mixed integer stochastic programming and results confirm that considering shorter time-scale results in more precise outputs. It is demonstrated that 30, 15, and 5-min time-scale reduce the cost about 5, 3, and 0.8%, respectively. But they increase the simulation time about 100, 200, and 300%, respectively. As a result, 15-min time-scale is considered as the best case because it keeps both simulation time and model accuracy on the acceptable level. It is also shown that uncertainty in model increases the cost about 22% and reduces load by 10% and decreases the cost about 38%. • Correlation of time-scale modelling and uncertainty is simulation. • Multiple time-scales are modeled including 15, 30, and 60 min time-intervals. • Uncertainties of the loads and wind energy are incorporated. • Energy management is carried out to optimize energy consumption in building. • Seasonal profile is included for loads, wind energy, and electricity prices. [ABSTRACT FROM AUTHOR]

This paper utilizes the thermal and wind energies in power to gas (P2G) process. The purpose of the proposed P2G system is to reduce the operating costs and environmental pollutions. The wind energy is used to produce Hydrogen (H2) via water electrolyzer. The Carbon dioxide (CO2) of thermal energies is also captured by Carbon Capture and Storage (CCS). The achieved H2 and CO2 are combined to make Methane (CH4) through Methanation reaction. The unit commitment denotes the optimal operation schedule of thermal generating units at each hour. The proposed model also determines the optimal size of wind energy. In the case of any event or outage, the wind energy recovery is studied by application of hybrid battery-capacitor storage system. The achieved CH4 from wind energy is sold to make profit. The wind speed volatility is included in the model and handled by stochastic programming. The proposed P2G achieves several purposes including optimal wind turbine sizing, uncertainty management, CO2 decrease and operating cost reduction. It is demonstrated that the Carbon tax can reduce the CO2 pollutions up to 8%. The high-cost and high-polluting generating systems like oil fired steam turbines are only used at on-peak hours like 17–21. These units produce about 6% of total energy but releases 11% of total CO2. The optimal capacity of wind generating system is obtained equal to 107 MW and the profit of process is estimated about 2.383 million $ in year. [ABSTRACT FROM AUTHOR]

This paper studies the effects of wind power on electricity market parameters. The penetration level of wind energy, location of wind turbines, and integration of multiple wind turbines are the main topics addressed in this paper. Flow-gate marginal pricing is the main electricity market concept which is analyzed and studied. Stochastic programming including wind power uncertainty is presented to minimize the annual operational cost of generators. The Flow-gate marginal pricing of transmission lines is also calculated. The Flow-gate marginal pricing is scrutinized under various wind power sizing, siting, and settings. The location, number, and capacity of wind turbines are changed to find out their impacts on the network Flow-gate marginal pricing. The proposed analyses and simulations are carried out using general algebraic modeling system software. [ABSTRACT FROM AUTHOR]

This paper deals with the real‐time optimal operation of active distribution networks (ADNs) hosting hybrid hydrogen‐electricity refuelling stations by benefiting from renewable energy sources (RESs), conversion facilities, and energy storage systems. The hybrid refuelling stations, which are controlled by ADN operator, supply electricity and hydrogen for electric vehicles (EVs) and hydrogen vehicles (HVs), respectively. In addition, the deployment of water equipment technologies in the ADNs, is considered by utilizing water well pumps in the hybrid stations to serve water demand. The principal aim is to minimize the expected operation cost, including the cost of purchasing power from the upstream grid and maintenance and operation costs of each hybrid refuelling station. Various technical and physical constraints are considered to ensure the reliable operation and realistic scheduling of ADNs in the presence of hybrid refuelling stations. This study employs a hybrid information gap decision theory (IGDT)‐stochastic approach to address the uncertain behaviour of wholesale market price, electricity demand of EVs in refuelling stations, RESs output power and nodal demand of ADN to reach a risk‐averse strategy. The developed approach is coded under GAMS software and the effectiveness of the approach is validated by testing on the modified IEEE 33‐bus test system. [ABSTRACT FROM AUTHOR]