Emerging innovation in smart charging for plug‐in electric vehicles (EVs) has the potential to achieve significant economic benefits. In several works, smart charging encourages the use of EVs as a ...flexible resource by modifying their power consumption through a demand response (DR) program. However, it is promptly assumed that EVs are always responsive and accept the smart charging signals with no fault. In practice, due to uncertainties such as random EV mobility, volatile battery charging characteristics or charging component failures, some EVs would be unable to accept the assigned charging signals dispatched from a central server. Therefore, this article proposes a feedback loop to predict EV charging behaviours and thereby adaptively tune the time‐based control signals dispatched to individual EVs. Moreover, a parallel‐operating distributed DR algorithm is proposed which aims optimal EV scheduling under charging uncertainties while reducing the need of private information sharing. The proposed distributed algorithm allows increased EV user privacy, fast convergence properties and optimal operation under communication disruptions and delays. The effectiveness of the proposed methods are also numerically exhibited for varying penetration of EVs within a low‐voltage (LV) distribution test network.
•Developed a mathematical model for semitransparent photovoltaic thermal Trombe wall.•Evaluated temperature of room air, Tr and of Trombe wall at Tx=0 and Tx=L.•Thermal load leveling for variation of ...thickness of the Trombe wall was evaluated.•Further also decrement factor for change in thickness of Trombe wall was evaluated.•Effect of packing factor and absorptivity on thermal heating of the room was computed.•Overall energy and exergy analysis of the PVT Trombe wall system was obtained.
In this paper, a periodic modeling of semitransparent photovoltaic thermal Trombe wall (SPVT-TW) for thermal heating of a single room for winter season in New Delhi has been developed. In the proposed concept, there are direct (through non-packing factor) and indirect (by convection from back of PV module) gain to blackened surface. After absorption of thermal energy by Trombe wall, heat is transfer to room by conduction to raise the room air temperature. Single room has a dimension of 30m2 and further by using various energy balance equations, a matrix of 4×4 has been developed for periodic condition of solar intensity and ambient air temperature. For a given design parameters and climatic conditions for New Delhi, unknown parameters for time independent and time dependent were obtained to evaluate thermal comfort of the room, in terms of thermal load leveling and decrement factor and the hourly room air temperature. Based on computation, it has been observed that optimum thickness of the wall should be 0.3–0.4m for thermal load leveling of 0.01 and decrement factor about zero for thermal heating as per requirement.
This paper proposes a disturbance‐observer‐based control (DOBC) scheme for frequency and voltage regulation in modern power systems with high renewable energy sources (RES) penetration. The proposed ...approach acts as a feed‐forward control that improves the dynamic performance of the conventional proportional‐integral‐derivative (PID) controller. The proposed voltage and frequency control has been validated through hardware‐in‐loop (HIL) implementation on OPAL‐RT, and testing on laboratory‐scale experimental test setup. The robustness of the proposed control scheme has been validated through simulations under worst‐case and stochastic uncertainties to mitigate real‐time variability in RES output and load. Real‐time simulation results depict superior performance of the proposed control strategy in comparison to several well‐established techniques under practical operating conditions, in the presence of communication delay and white noise. To validate the proposed control on laboratory‐scale experimental setup, the digital twin of the physical plant transfer function has been designed. Results reveal that the proposed DOBC control scheme drastically improves the system performance without rendering much computational burden under practical operation scenarios.
This study proposes a comprehensive framework for developing a multi‐energy off‐grid microgrid with the decoupled flow of thermal and electrical energies in a rural setting. A carbon‐neutral ...microgrid with a hybrid generation system constituting a photovoltaic unit and a biofuel generator is proposed. In order to enhance the fuel utilisation efficiency, the biofuel generator is operated in combined cooling, heating, and power mode, and the recovered thermal energy forms the heat distribution network in the microgrid. The flexibility of system operation is improved by suitable multi‐energy (electrical and thermal) storage. Firstly, an optimal sizing framework has been developed for the system as a mixed integer linear programming model. Secondly, a coordinated multi‐energy management system (MEMS) has been developed for combined optimal dispatch of multiple generation and storage resources. The MEMS has been developed as a mixed integer non‐linear programming model, which minimises system operational cost while considering minimum battery degradation to prolong its lifetime. Finally, a detailed economic analysis of the proposed system has been presented, highlighting the levellised cost of energy and net present value. Extensive case studies and simulation results depict the effectiveness and suitability of the proposed MEMS for the rural off‐grid microgrid.
•Boundary eigenvalue approach is used to identify the worst-case scenarios•Look-ahead approach is proposed for Hopf bifurcation stability margin (HBSM) monitoring•Formulation of HBSM enhancement ...problem using boundary active power loss evaluation•Optimal rescheduling of power system controllers under non-statistical uncertainties
Uncertainties in the forecasted load and generation can have a catastrophic impact on power system stability. For a reliable power supply, a sufficient dynamic stability margin is always desired. This paper introduces a novel boundary eigenvalue-based approach for the determination of Hopf Bifurcation Stability Margin (HBSM), which, explicitly, accounts for the impact of uncertainties in specified renewable generation and loads. Since the Hopf bifurcation stability problem is nondeterministic, it requires large computational efforts to determine the HBSM. Most of the available methods are based on statistical data, which are computationally less efficient for such applications. In this paper, a non-statistical uncertainty based control rescheduling strategy is proposed to enhance the stability margin of the system. To balance the trade-off between solution quality and computation time, the proposed approach is composed of two stages: i) determination of boundaries of critical eigenvalues; and ii) optimal setting of the controllers by minimization of a boundary active power loss based objective function under the given range of uncertainties. The proposed approach is demonstrated on standard IEEE test systems with promising results to show the importance and its reliability.
A stability study of interconnected microgrids is presented herein. This interconnection is vital to enhance the performance under dynamic conditions by providing mutual power support. The microgrids ...considered are based on three renewable energy sources, namely wind, solar, and biogas. The wind energy converting system (WECS) considered has a permanent magnet synchronous generator (PMSG) for conversion to electrical energy. A solar photovoltaic system (SPVS) with appropriate inverter has been incorporated. These two renewable energy sources are intermittent in nature. A biogas genset (BG) consisting of a biogas engine coupled with a synchronous generator is the third power source. The interconnection is by an AC line. Two interconnected microgrids, M1 and M2, are considered for mathematical modelling. Additionally, the microgrid M2 is also connected to the main grid for a limited but continuous power supply. Proportional integral (PI) controllers are used to control the frequency and voltage of the microgrids. Simulation studies are conducted on the system under step load disturbances and also for step changes in input power of wind/solar. It has been found that frequency and voltage deviations of the microgrids vanish under steady‐state conditions.
Uncontrolled electric vehicle (EV) charging is known to have an adverse impact on power networks. In particular, the inherent problem of phase load unbalance (PLU), due to uneven loading of phases ...can be substantially increased due to uncoordinated EV charging demands. Increased unbalance would cause sub-optimal operation of the distribution grid with higher thermal losses and increased network congestion. In this paper, a day-ahead EV scheduling strategy to mitigate unbalance is proposed, by controlling single-phase charging demand of EVs with vehicle to grid (V2G) power transfer. In addition, the EVs are also scheduled as per a price-based demand response program. The aim of this work is to use multi-objective lexicographic ordering to achieve economic benefit by controlling EV charging/discharging rates as per dynamic electricity prices, while simultaneously shift EV power consumption among phases to reduce unbalance. Further, uncertainty handling optimization techniques are presented to hedge against any randomness in prices and phase-wise loads. The proposed methods are simulated for a community charging station connected to the unbalanced grid. It is found that the active power consumption among phases can be balanced almost entirely using continuous charging/discharging rates from EVs. Moreover, up to 30% reduction in charging costs can be achieved while maintaining a balanced three-phase system.
•Multi-objective optimization for low impact integration of electric vehicles in unbalanced distribution grids.•Energy arbitrage using time-flexible charging loads shown conducive to balancing the grid.•Uncertainties of electricity tariff and consumer loads are considered for increased algorithmic robustness.•Numerical studies under varying day-ahead energy tariffs and household power consumption scenarios.
Rapid urbanization leads to increasing electricity demand. The intraday high and low electricity consumption patterns further increase challenges for grid operation. This article proposes a real-time ...strategy to minimize peak demand of a building by optimally scheduling the energy consumption of electric vehicles (EVs) with bidirectional power transfer. The strategy also incorporates rooftop photovoltaics (PVs) in reducing the power consumption of the building. In this article, the randomness of PV output is handled using scenario modeling under a rolling time-horizon framework, where feedback regarding EV mobility is also utilized in real time. In addition, the degradation of EV batteries is limited by controlling the charging/discharging cycles required for peak reduction. To provide incentives for contributing to peak reduction, a cooperative game is presented, wherein the EVs are conceptualized to work in a coalition with the building's energy management system. The payoffs in the game are decided based on the power extraction of EVs from the building combined with degradation costs incurred by individual EVs. The results demonstrate up to 40% reduction in demand peaks and 25% reduction in energy costs using the proposed energy management methods.
This paper focusses on the linearization of apparent power flow constraint (APFC) and the polyhedral approximations of second-order cone. The analysis presented in the paper is based on theoretical ...error (α=ε r /S) and not on the absolute error tolerance (ε r ) where S is apparent power limit. α is not a great measure to work with. The IEEE-39 bus system has transmission lines capacity ranging from 480 MVA to 1800 MVA. The difference in the objective value is negligible when the irregular polygon method (IPM) is used in comparison to regular polygon method when compared with ε r = 0.01 MVA for IEEE-30 bus and IEEE-118 bus systems. The linear optimal power flow (OPF) is very useful in solving transmission expansion planning (TEP) problems. This work can be improved via inclusion of reactive power and voltage using linear OPF with 1PM in deterministic TEP problems.
In this paper, a new approach is proposed to select the optimal sitting and sizing of distributed solar photovoltaic generation (SPVG) in a radial electrical distribution systems (EDS) considering ...load/generation uncertainties. Here, distributed generations (DGs) allocation problem is modeled as optimization problem with network loss based objective function under various equality and inequality constrains in an uncertain environment. A boundary power flow is utilized to address the uncertainties in load/generation forecasts. This approach facilitates the consideration of random uncertainties in forecast having no statistical history. Uncertain solar irradiance is modeled by beta distribution function (BDF). The resulted optimization problem is solved by a new Dynamic Harmony Search Algorithm (DHSA). Dynamic band width (DBW) based DHSA is proposed to enhance the search space and dynamically adjust the exploitation near the optimal solution. Proposed approach is demonstrated for two standard IEEE radial distribution systems under different scenarios. KCI Citation Count: 2
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