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Bi-Level Volt-VAR Optimization to Coordinate Smart Inverters with Voltage Control Devices
摘要： Conservation voltage reduction (CVR) uses Volt-VAR optimization (VVO) methods to reduce customer power demand by controlling feeder's voltage control devices. The objective of this paper is to present a VVO approach that controls system's legacy voltage control devices and coordinates their operation with smart inverter control. An optimal power flow (OPF) formulation is proposed by developing linear and nonlinear power flow approximations for a three-phase unbalanced electric power distribution system. A bi-level VVO approach is proposed where, Level-1 optimizes the control of legacy devices and smart inverters using a linear approximate three-phase power flow. In Level-2, the control parameters for smart inverters are adjusted to obtain an optimal and feasible solution by solving the approximate nonlinear OPF model. Level-1 is modeled as a Mixed Integer Linear Program (MILP) while Level-2 as a Nonlinear Program (NLP) with linear objective and quadratic constraints. The proposed approach is validated using 13-bus and 123-bus three-phase IEEE test feeders and a 329-bus three-phase PNNL taxonomy feeder. The results demonstrate the applicability of the framework in achieving the CVR objective. It is demonstrated that the proposed coordinated control approach help reduce feeder's power demand by reducing the bus voltages; the proposed approach maintains an average feeder voltage of 0.96 pu. A higher energy saving is reported during the minimum load conditions. The results and approximation steps are thoroughly validated using OpenDSS.
关键词： three-phase optimal power flow,Volt-VAR optimization,distributed generators,smart inverters
更新于2025-09-23 15:23:52
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[IEEE 2018 International Ural Conference on Green Energy (UralCon) - Chelyabinsk (2018.10.4-2018.10.6)] 2018 International Ural Conference on Green Energy (UralCon) - Comparative Analysis of Approaches to Consider Rationale of use of Solar Panel Plants for Power Supply of Off-Grid Consumers
摘要： The values of solar radiation for different monitoring periods from reference books were compared with calculated values from recent data of meteorological stations. The choice of meteorological stations depended on the differences of their latitude location, their position in the zone of the off-grid power supply, available data in different reference books on solar potential of the stations under study and presence of power plants located in different latitude zones using power resources for energy generation. The Sakha Republic (Yakutia) corresponded to these conditions. The comparative analysis of the initial values of solar potential showed that deviations amounted to 5–10%. The authors compared the results of recalculation of solar radiation values on the inclined surface using two approaches and showed the advantages of these approaches. They also investigated how the application of different approaches affected the optimal power of solar panel plants and calculated the payback periods of their construction. The payback period of the existing solar panel plants on the territory of the Sakha Republic (Yakutia) was compared with the calculated one. The application of different methodological approaches at different stages of rationale of solar panel plant construction was efficient for the power supply of off-grid consumers. It was proved that a simplified approach was reasonable for investigations of economic viability of power potential use on the territory under study. Detailed calculations are necessary for the determination of technical and economic parameters of a solar panel plant in a concrete settlement and for the estimation of economic effectiveness of its construction taking into account recent meteorological data.
关键词： recalculation on an inclined surface,optimal power,deviation of values,Solar radiation,payback period
更新于2025-09-23 15:22:29
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[IEEE 2018 IEEE Energy Conversion Congress and Exposition (ECCE) - Portland, OR, USA (2018.9.23-2018.9.27)] 2018 IEEE Energy Conversion Congress and Exposition (ECCE) - Optimal Solar PV Sizing for Inverters Based on Specific Local Climate
摘要： Generally, the output power of the Photovoltaic (PV) panels is less than the nominal rating of the panel. On the other hand, the inverters of the PV systems are normally sized smaller than the nominal rating of the photovoltaic system. A typical PV to inverter power rating ratio is 1.2, which can be influenced by the weather condition. The main drawback is that during peak irradiance and optimal temperature situation, the peak power is generated at the PV, but the inverter is not sized for absorbing the whole power. This article develops a systematic method to calculate the optimal ratio between PV panel and inverter to absorb the maximum possible power with an optimal cost. This method uses the annual irradiance and temperature of the geographical region and extracts the power curves for a photovoltaic system in specific regions. Based on the distribution of the various weather conditions, the total possible power generation of the system is calculated. Then the possible extracted and lost power for different sizes of inverters are calculated to develop an efficiency function for the extracted power of the typical power system. This function is optimized considering the price of inverters and system. Both of conventional 1000 V PV system as well as recently developed 1500 V system for 480 VAC grid connection are studied and the effect of transformer in both case is investigated. The paper shows how 1500 V system is superior to its 1000 V counterpart.
关键词： optimal power rating,Grid connected solar generation,PV panel
更新于2025-09-23 15:22:29
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A Novel Method for Optimizing Power Efficiency of a Solar Photovoltaic Device
摘要： Most recently, photovoltaic energy has made an incredible technological advancement for the forthcoming decades towards mitigating the ever-increasing energy demand worldwide through generating electric power. Present paper proposes a novel solar photovoltaic (SPV) device model that achieves optimal power efficiency from simulation and graphical performance analysis of SPV device characteristics. First of all, power as well as current performances is compared for varying irradiance and temperatures circumstances. Then, output current characteristics of the SPV device for the proposed as well as existing model with variable temperatures is plotted. Later, power versus voltage performances of a SPV device for the proposed model with varying irradiance and temperature criterions is compared. Finally, power–voltage characteristics are plotted graphically for the existing as well as proposed SPV device model that achieves significant amount of output power for the proposed model than the existing model and optimal power efficiency is obtained for the novel SPV device model.
关键词： Power–voltage,Irradiance,Solar photovoltaic (SPV),Optimal power efficiency (OPE),Photovoltaic (PV)
更新于2025-09-23 15:19:57
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Optimal power flow of power systems with controllable wind‐photovoltaic energy systems via differential evolutionary particle swarm optimization
摘要： The produced energy from varied sources in modern power systems is to be optimally planned for planning and operating of power system under the determined limit conditions. Recently, the rising overall people population of the world, the increasing of people requirements, improvements of technology, and ecosystem and global climate changes have caused with the increasing of electric energy demand. One of the most important solution methods to meet this energy demand is considered as utilization of renewable energy sources (RESs) in power systems. The structure of power systems has become with the usage of RESs more complex. The optimal power flow (OPF) from planning and operation problems has converted to difficult problem with RESs integrated into modern power systems. This paper presents the OPF problem of power systems with a high penetration of controllable renewable sources. These kinds of sources are able to inject a determined power since they have a back-up unit (storage). Uncertain solar irradiance and wind speed are simulated via log-normal and Rayleigh probability distributions, respectively. The proposed OPF problem with controllable renewable sources is solved by the differential evolutionary particle swarm optimization (DEEPSO) algorithm. Simulations conducted on various test systems illustrate the effectiveness and efficiency of DEEPSO as compared with other algorithms including moth swarm algorithm, backtracking search algorithm, and differential search algorithm. In addition, the Wilcoxon signed-rank test is applied to show the supremacy, effectiveness, and robustness of DEEPSO algorithm.
关键词： power system planning,optimal power flow,solar energy,wind energy,optimization
更新于2025-09-12 10:27:22
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[IEEE 2019 IEEE Industry Applications Society Annual Meeting - Baltimore, MD, USA (2019.9.29-2019.10.3)] 2019 IEEE Industry Applications Society Annual Meeting - Multi-time scale coordinated scheduling for the combined system of wind power, photovoltaic, thermal generator, hydro pumped storage and batteries
摘要： Grid connection of random renewable energy such as wind power and photovoltaic results in difficulties of keeping power balance for power system operation. In order to solve this problem, this paper proposed a multi-time scale coordinated scheduling model for the combined system of Wind power-Photovoltaic-Thermal generator-Hydro pumped storage-Battery (WPTHB) by taking advantages of their complementary operation characteristics. The scheduling model is composed of three time scales: the day-ahead scheduling, the 1-hour ahead scheduling and 15-minute ahead scheduling. 1) in the day-ahead scheduling, based on the day-ahead forecast data of Wind-Photovoltaic power and Load demand (WPL), the optimal power outputs of thermal power units in 24 hours are solved from a mix integer linear programing (MILP) model to achieve the minimal operation cost of thermal units. 2) In the 1-hour ahead scheduling, based on power outputs of thermal units solved in the day-ahead scheduling and the 1-hour-ahead forecasted WPL, the hydro pumped storage power output is optimized to achieve its minimal operation cost. 3) In the 15-minute ahead scheduling, based on the day-ahead optimal power outputs of thermal units and the 1-hour ahead optimal outputs of pumped storages, the battery optimal power generation is obtained from a AC optimal power flow model solved by MATPOWER. Simulations of New England system validate that the proposed multi-time scale coordinated scheduling model could fully explore the different power regulation speeds and capacity of hydro pumped storages, thermal power generators and batteries to effectively alleviate WPL variations and achieve economic operation for multi-source generation systems.
关键词： day-ahead scheduling,mix integer linear programing,AC-optimal power flow,15-minute ahead scheduling,1-hour ahead scheduling,coordinated scheduling model,Multi-time scale
更新于2025-09-12 10:27:22
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Power Management in Active Distribution Systems Penetrated by Photovoltaic Inverters: A Data–Driven Robust Approach
摘要： Under the smart grid paradigm, distribution systems with large penetrations of photovoltaic–based power generation are called to optimize their operational resources to achieve a more ef?cient and reliable performance. In this context, this paper proposes a multiperiod mixed integer second order cone formulation to optimize distribution feeders operation. The model takes into account the feeder physical behavior; discrete control equipment (tap changers and capacitors banks) with a maximum allowable daily switching operation number; photovoltaic inverters operation; and the uncertain nature of solar energy and loads. A two–stage robust optimization framework is used to include the uncertainty into the model, where discrete and continuous control actions are assumed to be part of the ?rst and second stage of this model, respectively. The conservativeness level of the robust model is controlled by an polyhedral uncertainty set whose vertexes are adaptively adjusted in a data–driven fashion in order to better capture complex spatiotemporal dependencies among uncertain parameters. Extensive computational experiments are performed utilizing modi?ed versions of various IEEE test feeders. The performance of the proposed data–driven model is contrasted against traditional deterministic and robust budget–constrained models, using a rolling horizon out–of–sample evaluation methodology. When compared to the deterministic model, the data–driven approach yields a reduction in power losses of approximately 15% and a reduction up to 98% in hourly voltage violations. Results also suggests that the proposed approach exhibits better performance in terms of both average and conditional–value–at–risk metrics in comparison to budget–constrained models.
关键词： Distribution Systems,Data-Driven Optimization,Optimal Power Flow,Robust Optimization,Volt/VAR Control
更新于2025-09-12 10:27:22
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[IEEE 2019 IEEE Milan PowerTech - Milan, Italy (2019.6.23-2019.6.27)] 2019 IEEE Milan PowerTech - optimising Load Flexibility for the Day Ahead in Distribution Networks with Photovoltaics
摘要： In this paper a methodology is proposed to calculate the load demand ?exibility that could be activated within the next 24-hours for solving the technical impacts of contingencies that may come up in an unbalanced low voltage distribution networks with high penetration of intermittent DG sources. The methodology is formulated within a Demand Response program environment via load shifting as ?exibility enabler mechanism. To achieve that, a non-linear optimisation problem is formulated based on an unbalanced optimal power ?ow, which allows the determination of the load ?exibility that each Demand Response customer could provide at the request of the Distribution System Operator. The demand as well as weather conditions are forecasted for the day ahead. The optimisation problem is solved in a sequence fashion, within a daily framework, splitting the whole problem in optimisation blocks. In each block, the ?exible load demand is obtained and the load demand forecasting its updated for the upcoming blocks based on the changes in the scheduled load demand. The methodology is applied to a real distribution network with the load data received from the smart metering infrastructure. The results obtained show the strength of the methodology in solving the technical problems of the network under high unbalanced operation.
关键词： Photovoltaics,Demand Response,Load Flexibility,Distribution Networks,Optimal Power Flow
更新于2025-09-12 10:27:22
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Design of Optimal Power Point Tracking Controller Using Forecasted Photovoltaic Power and Demand
摘要： With the advent of grid-connected Photovoltaic systems for energy generation, new technologies must be created that maintain a continuous and stable balance between supply and demand of generated electricity. Consequently, accurate prediction of solar energy generation and consumption is required. Solar energy generation and electric power demand are both stochastic and non-stationary in nature and often incongruous. The imbalance between demand and supply can be costly and leads to long-term ineffectiveness of power generation and distribution. The aim of this work is to propose methods for maintaining demand-supply balance in PV power generation and distribution systems. To achieve this, we build and combine three different tools: 1) a predictive model for forecasting solar energy generation, 2) a predictive model for demand prediction, and 3) a real-time control algorithm that uses the outputs of prediction models and adjusts the output voltage of PV system to maintain demand- supply balance. Our prediction models are based on time-series forecasting tools and Arti?cial Neural Networks. The control algorithm is called Optimal Power Point Tracking (OPPT) and is based on the Perturb and Observe algorithm. We evaluate the performance of the combined prediction-controller system using real-world data.
关键词： Neural Network,Modeling,Optimal power,Optimization,Fuzzy Logic,Forecasting
更新于2025-09-12 10:27:22
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[IEEE 2019 IEEE Milan PowerTech - Milan, Italy (2019.6.23-2019.6.27)] 2019 IEEE Milan PowerTech - Optimal Scheduling of Generators and BESS using Forecasting in Power System with Extremely Large Photovoltaic Generation
摘要： Large scale integration of renewable energy sources (RES) can cause supply demand uncertainty. In Japanese power systems the photovoltaic (PV) generation is growing rapidly. PV forecasting with energy storage systems can be used in Unit Commitment (UC) to reduce these imbalances. In this study Battery Energy Storage systems (BESS) and day-ahead PV forecasting with prediction intervals have been used to examine the imbalances. The day-ahead UC of thermal generators and day-ahead optimal BESS charging and discharging is calculated with different BESS inverter capacities and BESS energy capacities. Then the power shortfall and surplus of PV power in the target day are calculated. The simulation is run for 3 months from April to June 2010 for Kanto area power system of Japan.
关键词： Photovoltaic (PV) forecasting,Unit Commitment (UC),Optimal Power dispatch,Battery Energy Storage Systems (BESS),Prediction Intervals,Mixed Integer Linear Programming (MILP)
更新于2025-09-11 14:15:04