Operation Of Hybrid Power System Research Articles

배터리 기반의 하이브리드 전력계통 운용을 위한 선박용 EMS 연구

배터리 기반의 하이브리드 전력계통 운용을 위한 선박용 EMS 연구

Research on power configuration scheme of parallel hybrid oil-electric power system for tilt- rotor UAV

The tilt-rotor UAV is a new type of unmanned aerial vehicle that has both the hovering capability of a rotary-wing UAV and the high-speed cruising flight capability of a fixed- wing UAV. Through the tilting system of the UAV, different working states can be switched: during the take-off and landing phases, the rotor axis is perpendicular to the ground, thus realizing aerial hovering, forward and backward flight and side flight. In the cruise flight phase, the rotor axis is perpendicular to the flight direction, thus achieving the flight attitude of a fixed-wing aircraft. The hybrid power system is a composite power system that combines fuel power with electrical power. By applying the oil-electric hybrid power system on the tilt-rotor UAV, it can combine the advantages of long range and long range of fuel power and low noise and pollution of electric power. In this paper, the tilt-rotor UAV parallel oil-electric hybrid power system power configuration scheme is studied. Firstly, the three operating modes of the oil-electric hybrid power system are introduced, including hybrid drive, drive charging and pure oil drive. The power requirements of the tilt-rotor UAV in vertical takeoff and landing, fixed-wing cruise and other flight phases are calculated, and the correspondence between the UAV flight status and the hybrid power system operation mode is established according to the working characteristics of the tilt-rotor UAV and the hybrid power system operation mode. The power configuration method for each flight phase is finally determined, and the process of the overall power configuration realization of the threshold value is described in detail.

Solution for short-term generation scheduling of cascaded hydrothermal system with turbulent water flow optimization

For economic operation of hybrid power systems, short-term hydrothermal planning is a significant operation which is focused to reduce the fuel costs of thermal power plants while fulfilling the different constraints of electrical and hydraulic networks. This paper addresses a newly developed algorithm, turbulent water flow optimization (TWFO) to solve the hydrothermal scheduling problem. TWFO is based on the whirlpool phenomenon which is formed through turbulent flow of water in seas or oceans. To enrich the solution quality of TWFO and to avoid trapping into local optimum, a chaotic logistic map is employed in the algorithm. The proposed TWFO is used to offer an optimal hourly generation schedule of hydrothermal power system considering the spillage effects of hydro plants, and the valve point loading effects, transmission losses and multi-fuel sources of thermal power plants. Besides, a repair mechanism is applied to fulfil all the equality and inequality constraints and to govern the solutions in the direction of feasible search space. The superiority of the proposed TWFO is examined on three hybrid power systems and the results of TWFO are compared with the performance of recent heuristic approaches including monarch butterfly optimization, Harris hawks optimization, red fox optimizer, remora optimization algorithm, student psychology-based optimization, and other erstwhile approaches reported in the literature. Numerical results demonstrate that the TWFO shows a superior performance in comparison with other approaches.

Creation of a hybrid power plant operating on the basis of a gas turbine engine

This paper considers the issue related to the use of jet gas turbine engines for the generation of thermal and electrical energy, defined as a hybrid energy system powered by biogas. Revealing the main vulnerable points of the use and operation of these systems, it is proposed to use biogas obtained from agricultural, crop and livestock waste as fuel for gas turbine engines. Analyzing the work of gas turbine engines, it reveals not only the technological advantages of using biogas instead of fuel, but also reducing the cost of heat and electric energy obtained by obtaining a productive land biohumus. This will result, firstly, it is especially emphasized, the usefulness of the resulting ground humus as a waste material, when producing biogas as fuel, for the operation of a hybrid energy system operating on the basis of gas turbine engines. Secondly, during the operation of a hybrid power system, it is possible to simultaneously obtain thermal and electrical energy. Thirdly, the low cost of the heat and electric energy received. The following are other useful applications of such a power system. The resulting thermal energy is used for heating the greenhouse, and the electrical energy obtained from the operation of the hybrid power system can be used not only for lighting the premises, but can be used for the needs of the greenhouse. It is shown that the proposed hybrid power system consists of two technological structures. The first design is to obtain fuel in the form of biogas for the operation of gas turbine engines, the second design is the connection of the first design with gas turbine engines. A schematic diagram of the general design of the proposed hybrid power system and the principle of its operation is proposed. The difficulties encountered in the design and operation of such hybrid power systems are noted

Uncertainty-aware non-supplied load minimization oriented demand response program for PV/FC power system with electrolyzer back-up

This manuscript presents robust optimization framework with multi-objective approach for day-ahead operation of hybrid power system consisted of photovoltaic (PV) panel, fuel cell (FC) with electrolyzer (Elc) back-up. The multi-objective optimization model of PV/FC/Elc has been developed by combining the physical and operational constraints with mathematical equivalence of affine forms as well as considering the uncertainties occurring in the load demand and PV power generation. As a novel contribution to the literature, three robust optimization approaches for scheduling the hybrid power systems have been presented through the conservatism approach. Moreover, the objective function has been described to integrate the different objectives as aiming to minimize non-supplied load, while maximize the utilization rate of the essential source. By this way, it has been aimed to accelerate the adaptation of the demand response strategies for the proposed system. Moreover, this hybrid scheme provides solutions to meet the power demands for the residential end-users located in off-grid areas or islands. The mixed integer linear programming (MILP) model is tested in GAMS v.24.1.3 using the solver CPLEX v.12 and the developed strategy is analyzed for different load patterns. The results are discussed and commented with some suggestions to prove the contribution of the paper. • Uncertainty representation in load and power profile is provided. • Multi-objective robust optimization of household DR program for off-grid or island mode applications is presented. • Case study based analysis of optimal management of PV/FC power system with Elc back-up is carried out. • A compact and flexible MILP based modelling of PV/FC/Elc hybrid power system is offered. • Fulfilling the comfort and efficient operation requirements in the same optimization problem is performed.

Equivalent Firm Capacity Assessment of HDR-PV Hybrid Power System: A Distributionally Robust Approach

Aiming at the reliable grid connection of photovoltaic (PV) systems in frigid plateau regions, this work first designs a flexible hot dry rock (HDR) hybrid power system (HPS), making full use of the potential of HDR for energy storage and power generation. Based on the operation of HPS, a comprehensive energy system credible capacity assessment method considering the overall economy of the system and the reliability of the grid is established. In this method, the power allowable fluctuation rate of the grid as the equivalent firm capacity (EFC) constraint is considered. Then, the constraint is converted into a set of linear chance conditions through the distributionally robust method so that the capacity assessment of the HDR-PV HPS can be converted into a mixed-integer linear optimization problem for a solution. The proposed assessment method is verified by real HDR-PV HPS in the Gonghe Basin of Qinghai Province. The results show that the flexible HDR plant increases the credible capacity of the HPS by 113.38%. The profit of the flexible HDR plant was increased by 3.02% at the same time. The parameter analysis shows that the HDR-PV HPS obtains the most profit when the allowable fluctuation rate is 7%, but 10% can fully utilize the geothermal. The assessment method can effectively assess the credible capacity of the system under the premise of ensuring the overall economy of the HPS, thereby guiding power grid dispatching.

Global atlas of solar and wind resources temporal complementarity

The concept of renewable energy sources complementarity has attracted the attention of researchers across the globe over recent years. Studies have been published regularly with focuses on aspects such as new metrics for complementarity assessment, the optimal operation of hybrid power systems based on variable renewables, or mapping resources complementarity in a specific region. This study targets the present literature gap, namely a lack of complementarity study covering explicitly the whole World, based on the same data source and methodology. The research employs Kendall's Tau correlation as the complementarity metric between global solar and wind resources and a pair of indicators such as the solar share and a sizing coefficient usually applied in the domain of hybrid generators. This method allows to conduct a preliminary estimation of a solar and wind energy hybrid generator based on a daily demand of 1 kWh. The data series employed in this study come from NASA’s POWER Project Program, covering the years 2001–2020. This work provides an interesting insight into the global variability of the complementarity between these two variable energy sources. Significant findings of this paper include that Kendall’s Tau ranges between –0.75 and 0.75, in line with previous research for specific regions, thus providing a theoretical maximum for planning. Additionally, the results suggest that in most tropical and subtropical areas, the hybrid solar-wind generator should be dominated by the solar portion to minimize the variability of the total daily energy produced.

Identifying the effect of forecast uncertainties on hybrid power system operation: A case study of Longyangxia hydro–photovoltaic plant in China

Power system operations are unavoidably influenced by forecast uncertainties. The forecast uncertainty's effect on operations was quantified in individual systems, however, was seldom investigated in a hybrid system. This study aims to quantify the effect of forecast uncertainties on the hybrid hydro–photovoltaic system operation. First, the operation model is built considering streamflow and photovoltaic forecast uncertainties with long- and short-time scales. Second, total release uncertainty is determined from the sum of squares for releases under different forecast scenarios. Finally, a variance partitioning method is used to divide the total release uncertainty into the uncertainties induced by individual forecast errors. Longyangxia hybrid hydro–photovoltaic power plant from China was selected as a case study. Results provide following insights: (1) long-term inflow forecast uncertainty accounts for 98.89% of the contribution to the long-term release uncertainty, while photovoltaic uncertainty accounts for 1.11%; (2) long-term inflow forecast uncertainty still dominates the short-term release uncertainty, with the contribution of 62.06%; and (3) the total release uncertainty decreases in long-term hybrid operation compared with the reservoir operation, indicating the complementary relationship between long-term hydropower and photovoltaic power. These implications highlight the importance of improving forecast accuracies for varied energy sources at different time scales.

Renewable/Fuel Cell Hybrid Power System Operation Using Two Search Controllers of the Optimal Power Needed on the DC Bus

In this paper, the optimal and safe operation of a hybrid power system based on a fuel cell system and renewable energy sources is analyzed. The needed DC power resulting from the power flow balance on the DC bus is ensured by the FC system via the air regulator or the fuel regulator controlled by the power-tracking control reference or both regulators using a switched mode of the above-mentioned reference. The optimal operation of a fuel cell system is ensured by a search for the maximum of multicriteria-based optimization functions focused on fuel economy under perturbation, such as variable renewable energy and dynamic load on the DC bus. Two search controllers based on the global extremum seeking scheme are involved in this search via the remaining fueling regulator and the boost DC–DC converter. Thus, the fuel economy strategies based on the control of the air regulator and the fuel regulator, respectively, on the control of both fueling regulators are analyzed in this study. The fuel savings compared to fuel consumed using the static feed-forward control are 6.63%, 4.36% and 13.72%, respectively, under dynamic load but without renewable power. With renewable power, the needed fuel cell power on the DC bus is lower, so the fuel cell system operates more efficiently. These percentages are increased to 7.28%, 4.94% and 14.97%.

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.

Minimizing the Impact of Intermittent Wind Power on Multiperiod Power System Operation with Pumped Hydro Generation

In power system operations, unforeseen energy imbalances commonly occur, resulting in unexpected constraints on the system. This leads to a disturbance in normal operation. In systems with integration of large intermittent wind power resources, additional complications are imposed on the system, especially under heavy winds that require immediate measures to minimize possible impact of abrupt wind power fallout. Effective power system fortifications have to be put in place to address the challenges. Wind varies more on the sub-hourly time scales; therefore, sub-hourly dispatch is bound to address more of these issues than commonly used hourly methods. Hybrid power system operation with wind necessitates the use of fast start-up generation and storage to improve quality of power. In this work, the impact of intermittent wind power curtailment on power system operation is addressed to prevent system instability. A modified wind turbine power curve is used to restrict the onset of the normal cut-off point, thereby allowing sufficient time for effective power switchover with pumped hydro generation. This improves the voltage stability of the power system during curtailment. Singular value decomposition matrix of the power system network is employed to evaluate the performance of the proposed method.

Opportunity for Improving Lead-Acid Battery Management of Photovoltaic-Genset-Battery Hybrid Power Systems Based on Measured Field Data

In this communication, the measured behaviour of a lead-acid battery bank within a stand-alone residential solar photovoltaic (PV)-genset-battery hybrid power system in Canada is presented and discussed. In order to capture rare field-based battery performance data, a newly commissioned lead-acid battery bank was equipped with a battery monitoring device capable of logging voltage, current, temperature and amp-hours every 30 s for the life of the battery. The measured data captures a severe loss of battery capacity due to a combination of short-term deep discharge and extended partial state of charge operation—conditions not unusual during winter season PV-genset-battery hybrid power system operation. Subsequent manual override of the system control set points to encourage gradual battery overcharge are shown to recover the lead-acid battery bank’s performance over the following three months. Limitations of the power conversion system’s battery management approach are discussed and a novel closed loop control system for improving lead-acid based PV-genset-battery hybrid system performance is rationalized and proposed for further research.

Optimal sizing and operation of battery storage for economic operation of hybrid power system using artificial bee colony algorithm

Optimal sizing and operation of battery storage for economic operation of hybrid power system using artificial bee colony algorithm

Energy management hypothesis for hybrid power system of H2/WT/PV/GMT via AI techniques

This paper aims to attain an efficient and optimized energy management operation of Hybrid Power System (HPS) by using Artificial Intelligent (AI) controllers. The HPS comprises Wind Turbines (WTs) and Photovoltaic (PV) panels such as primary Renewable Energy Sources (RESs) in addition to both Fuel Cells (FCs) and Gas Micro–Turbines (GMTs) which are used as Backup Sources (BKUSs).To avoid the undesired negative impacts on the HPS functionality because of the RESs intermittency, the Hydrogen Storage System (HSS) is integrated into the system. Two different energy management strategies based on Neural Networks (NN) and Fuzzy Logic Control (FLC) respectively are applied to the HPS for minimizing the energy production cost and keeping the buffer role of HSS. Using MATLAB™, the proposed two AI introduced solutions are used for reaching adequate energy management operation performance for the overall HPS during 24 h load variation. From the numerical simulations, the superiority of the FLC over the NN control approach is discussed. The proposed HSS can positively act as a buffer solution to avoid drawbacks of RESs during unexpected load peaks and/or discontinuous energy production.

Optimal operation of hybrid power systems including renewable sources in the sugar cane industry

This study presents a control structure, based on model predictive control, applied to energy management optimisation in a sugar cane processing plant including renewable sources. The proposed energy plant is set upon a sugar cane processing industry and has to produce and maintain an amount of electric power throughout the year, defined by contract. This plant is, also, bound to produce flows of steam in different pressures, to comply to the demands of the production process of ethanol and sugar, from the sugar cane. The renewable sources in the system include photovoltaic, wind power generation and the use of biomass, from the remains of the sugar cane. The proposed control algorithm has the task of performing the management of which energy system to use (combined heat and power generation systems, boilers or others), maximise the use of renewable energy sources, maximise the gains of the boilers (that vary according to the biomass mixture used), manage the use of energy storages and supply the defined amount of energy. Simulation results show the satisfactory operation of the proposed control structure.

Economic and Environmental Modeling of a Photovoltaic-Wind-Grid Hybrid Power System in Hot Arid Australia

Increased concern about energy crisis and environmental issues has revitalized interest in the application of renewable energy technologies. For ensuring steady and continuous electricity generations, a hybrid power system (HPS) including more than one renewable energy elements is introduced. In this paper, environmental and economic analyses are used to discuss the sustainability of a HPS. An investigation is made on small-scale operations of 100kWh per day HPS as a grid-assisted power generation consisting of solar (photovoltaic) and wind energy. A comparison is drawn among the different configurations of a grid-connected HPS operation focusing on environmental and economic impacts. Emissions and the renewable energy generation fraction (RF) of total energy consumption are calculated as the main environmental indicator. Costs including net present cost (NPC) and cost of energy (COE) are calculated for economic evaluation. To simulate long-term continuous implementation of the HPS, the hourly mean global solar radiation and wind speed data of 2007, from Alice Spring (