Solar Power Units Research Articles

Collaborative Control of Reactive Power and Voltage in a Coupled System Considering the Available Reactive Power Margin

This article proposes a hierarchical collaborative reactive power and voltage control method aimed at meeting the internal voltage requirements of a coupled system composed of centralized new energy stations such as wind and solar power and traditional thermal power units, with particular attention paid to the reactive power regulation ability of power units in new energy stations. This method is implemented in two layers: At the transmission layer, the overall reactive power compensation capacity of thermal power units and stations on the transmission lines within the system is determined according to the engineering requirements of different node voltages in the coupled system, the regulation voltages of the high-voltage grid-connected points and the point of common coupling (PCC) of the stations are found, and the actual regulation voltages of the PCCs of the stations are given as commands. At the station layer, based on determining reactive power distribution between power units and continuous reactive power compensation devices within each station, voltage optimization is carried out using the voltage command issued by the transmission layer as a reference. At the same time, consistency coordination between the transmission layer and the station layer is achieved based on the Analytical Target Cascading (ATC) method at different layers. Finally, simulation analysis was conducted on a regional coupled system in Dalian. The results showed that the method proposed in this paper can effectively control the voltage safety requirements of each region and PCC in the coupled system and, to some extent, improve the economic efficiency of system operation.

Prospects of solar power generation in dry regions: the case of Arar in KSA

The prim aim of this paper is to propose and analyze technical and economic dimensions concerning the integration of solar power (PV) unit(s), in the existing typical conventional power generation system, in the absence of a feed-in tariff scheme. The basic scenario examined in this work assessed possible electricity unit cost taking into account the penetration of PV modules of about 5 to 10 kW PV systems as roof-tops for residential use, without storage capability in prevailing local conditions in the northern region of KSA, i.e. city of Arar. Based on the input data and assumptions made, the simulations indicated that the scenario to meet the electrical demand of Arar would require installing at least 20-30 central modules, with a capacity of about 10 MW each. But it is not possible to meet the total electrical demand by employing distributed PV modules. In addition, the cost The estimated cost of produced electricity is about 0.1-0.12 US$/kWh and considered very high compared with the current prices of about US$ 0.013 per kWh. Without government incentives, i.e. feed-in-tariff or any other financial scheme aiming to encourage the utilization of renewable energy resources, such systems will not be feasible or find its way in KSA. However, the sensitivity analysis on current fuel prices, used for power generation, showed that increasing the local fuel prices would make such plants more economically attractive compared with conventional systems.

An application of nature inspried algorithm based dual-stage frequency control strategy for multi micro-grid system

In this article, a dual-stage frequency control strategy is proposed to maintain the reliable operation of an islanded interconnected micro-grid system. The controller helps micro-grid in frequency stabilization and maintains the load demand balance during abnormal operating conditions. The multi-microgrid system comprises a biodiesel generation unit wind turbine, redox flow battery (RFB) in area-1 and BDG, organic Rankine cycle-based solar thermal power unit, and a capacitive energy storage system (CES) unit in area-2. The CES maintains the transient frequency deviation and RFB fulfills the long-term power demand during abnormal conditions. In this proposed work, a novel and efficient optimization technique entitled modified African Buffalo Optimization (MABO) has been implemented for optimal tuning of PIDF, PID-PDF, and PDF controllers. Further, the performance of MABO is compared with recently deployed optimization techniques i.e. Corrected Moth Search Optimization (CMSO) and African Buffalo Optimization (ABO). Eigen-values stability analysis and bode plot analysis are considered to validate the efficacy of the proposed controller design. In addition, a sensitivity analysis has been executed to manifest the potential of the proposed strategy for a wide variation in micro-grid specifications, magnitude, and fluctuation of step/random power load disturbance. The various performance analyses validate the dominance of the proposed approach in damping frequency oscillations during severe disturbances and uncertain conditions.

Multi-criteria optimization of a renewable combined heat and power system using response surface methodology

Sun is one of the reliable sources of energy that is available in most locations in the world. Among various solar power units, the parabolic trough collector (PTC) is one of the most functional systems that can provide considerable thermal energy. However, this unit is not able to directly provide electrical energy. Thus, this study presents a non-dimension model of a renewable power system that incorporates a photovoltaic cell and a PTC unit. This hybrid system can simultaneously provide both heating load and electricity. The scheme is examined from the perspectives of exertion, energy, emission, entropy, and economics (5E). In this order, the influence of diverse operating factors on the outcomes of the unit, including saved cost, electrical and thermal exergies, CO2 emission, electrical and thermal energies, and entropy generation, are examined. On top of that, the performance of this innovative unit is optimized using both single-objective and multi-objective methods. The findings indicate that increasing fluid inlet temperature and solar radiation intensity lead to an increase in the temperature of every component of the unit. A stronger heat transfer from the receiver tube to the working fluid causes the temperature of the fluid and solid zones to decrease when the mass flow rate is increased. The analysis shows that the optimum value of solar radiation for the electrical exergy and saved cost is around 900 W/m2 and further reduction or increment in the value of this parameter has an unfavorable impact on both electrical exergy and saved cost. While, raising solar radiation improves all other output parameters of the unit, continuously. Also, it is found that the concentration ratio is the only parameter that elevation in its value leads to ascending the value of all output parameters of the presented system. Based on the findings, at the optimum operating condition, the value of saved cost, CO2 emission, and entropy generation are 70 USD/month, 803.956 kg/month, and 23.93 W/m.K, respectively.

Analysis of a novel concentrated solar power and magnetohydrodynamic liquid metal units integrated system with hydrogen production

The engineers are very interested in concentrated solar power (CSP) due to its renewable energy source nature. However, for this technology to grow, it is crucial to integrate efficient, cost-effective subsystems. On the other hand, since liquid metal magnetohydrodynamic (LMMHD) power generation systems can operate at high temperatures of 600 °C–3000 °C, they are ideal for use as a subsystem of a CSP-based plant to improve efficiency. The use of waste heat recovery units is another method of increasing efficiency and preventing exergy losses. Taking these points into consideration, the proposed trigeneration system includes an LMMHD, a CSP, and humidification-dehumidification and proton exchange membrane units to produce power, freshwater, as well as hydrogen, respectively. Performance evaluation of the presented system includes thermodynamic and thermoeconomic considerations. The results show that the presented system produces 11.87 kW of power, 6.1 m3/h of hydrogen, and 860.2 L/h of freshwater with an energy utilization factor of 45.81%, a total exergy efficiency of 4.63%, and a unit cost of 19.57 $/kWh. The receiver is the most destructive component of the system, with 256.9 kW of exergy destruction. Further, the parametric study indicates that it is possible to maximize the energy efficiency of the system by changing the concentration ratio of the receiver.

Optimal scheduling for unit commitment with electric vehicles and uncertainty of renewable energy sources

The unit commitment (UC) problem is a typical mixed integer nonlinear programming problem related to power systems. As electric vehicles (EVs) and renewable energy sources (RESs; e.g., wind and solar power) have become integrated into the power system, the UC problem has become increasingly complex. With the continuous growth of the proportion of renewable energy based on wind and solar energy in the power supply structure on the supply side in the future, the random characteristics of the supply and demand sides of the power system will become more obvious, which will inevitably bring about the safety, stability and economic operation of the power system. The study of UC not only has great academic value, but also has important practical significance. The optimal scheduling of UC, including thermal, wind, solar, and EV power units was investigated. The objective function of optimal scheduling was to minimize the operating cost of the unit and optimize the charging and discharging costs of EVs. In view of power generation characteristics of RESs, an interval number was introduced to describe the uncertainties in the outputs of wind and solar power generation. The enhanced-interval linear programming is introduced to deal with the UC problem including EVs and uncertainty of RES. For better accuracy, wind power was considered for each of the four seasons (spring, summer, autumn, and winter) and solar power was divided into sunny, cloudy, and rainy conditions. To reflect the influence of EV charging and discharging on UC, three different charging and discharging pricing schemes were considered. Various scenarios were simulated using the CPLEX solver. The results showed that costs can be affected by season and climate. The interval number solution sets of the total cost and of the charging and unit costs were obtained by using interval number theory to describe the uncertainty of output in RESs; this provides a new approach for solving the UC optimization problem by integrating RESs. The charging and discharging of EVs can also affect costs. By encouraging the orderly charging and discharging of EVs, power load fluctuations could be reduced and peak-load shifting could be achieved. Different pricing schemes had different impacts on cost. The pricing scheme can not only effectively reduce the charging cost borne by EV owners, but could also make EVs profitable. This discovery provides a theoretical basis for guidance on the charging and discharging of EVs through charge and discharge price schemes. The simulation results reflect the relationship between economic cost and seasons/climate and confirm the suitability of using an interval number to describe uncertainty in energy generation.

Thermo-economic investigation of solar-biomass hybrid cogeneration systems based on small-scale transcritical organic Rankine cycles

• An innovative small-scale solar/biomass hybrid system is investigated. • A novel transcritical organic Rankine cycle is studied at full and partial loads. • The comparison with single-source systems shows the advantages of the hybrid solution. • Biomass and solar source integration assures cost decrease and clean production. • Biomass saving (–32.8%) and better solar exploitation (+8.8%) are reached. The present study aims at investigating the energy, exergy, and economic performance of an innovative multi-source renewable hybrid energy system for small-scale combined heat and power (CHP) applications. The system is based on a transcritical organic Rankine cycle (ORC) able to exploit solar and biomass sources, through a concentrated solar power unit and a biomass boiler. A thermo-economic model has been developed and a parametric analysis has been implemented to define the proper configuration of the hybrid system balancing energy and economic purposes. The investigation, performed for a residential complex in Southern Italy, highlights that the suitable hybridisation of biomass and solar energy increases the useful production and system flexibility compared to the single-source configurations. The proposed small-scale system guarantees a 48.9% decrease in the biomass consumption compared to the corresponding biomass-only apparatus, increases the exploitation (+8.8% of electric production) of low solar radiations that are not adequate to feed a full-solar ORC, also overcoming the stochastic and intermittent characteristics of the solar source. The comparison with the conventional scenario, where the electric grid and natural gas boilers satisfy the energy demands, separately, demonstrates that the suggested solar/biomass hybrid ORC system guarantees a 24.2% primary energy saving, a 53.5% decrease in the unit electric and thermal production costs, and a 57.7% drop in greenhouse gas emissions, with a payback period equal to 7.5 years.

Strategic Placement of Solar Power Plant and Interline Power Flow Controllers for Prevention of Blackouts

In these post COVID times, the world is going through a massive restructuring which India can use to its benefit by attracting foreign industrial investment. The major requirement is a reliable and ecofriendly electrical power source. Of late, renewable energy sources have increasingly become popular as alternative source of electricity. They can provide immense aid in improving the reliability of the power system, when placed properly. The alternative integrated energy sources along with FACTS devices can provide a promising future for reliable power systems. In this paper, an effective location for the solar power unit and Interline Power Flow Controller using Line Severity Index is proposed in order to avoid contingencies. An Indian 62 bus system and IEEE 57 bus system are considered for the study. The Firefly algorithm is used to tune the IPFC in the Integrated Energy Systems scenario, for a dual objective function. The effect of placement of the solar unit and the optimized IPFC is analyzed and studied in detail in this paper.

Design and Implementation of a Wireless Sensor Network for Smart Greenhouse Controller

Sensors play an essential role in gathering environmental information for greenhouse farming. Wireless sensor network creates and manages links between sensor blocks in the system. As a result, not only various environmental parameters can be collected, but the sensor location can also be flexibly deployed. Sensor blocks require low energy consumption and inexpensive implementation costs with typical operating conditions. The research has built a wireless sensor network based on open Radio Frequency (RF) technology. Each sensor block has a low deployment cost and operates independently via a solar-powered unit. A novel communication protocol is designed for the proposed sensor network. In addition, a greenhouse controller exploiting designed wireless sensor networks is also constructed to evaluate the practicality of the system. Sensor networks developed are intended to be applied to the existing agricultural greenhouses in the surveyed area. The greenhouse is medium-sized, and the system implemented in practice is for vegetable farming. As a result, the controller can connect to the Internet to serve IoT links and applications. Experimental results prove the practicality of sensor blocks and the stability and efficiency of the wireless sensor network. It helps to reduce deployment costs and improve applicability. In addition, the sensor blocks are designed and built with low energy consumption, which can be operated with a small solar power source.

DEVELOPMENT OF AN AUTONOMOUS HYBRID ELECTRICAL COMPLEX WITH A TEMPERATURE CHANGE SYSTEM

Recently, due to the progress in the development of wind generators and solar panels, autonomous hybrid energy systems based on renewable energy sources, which include solar panels, wind generators and power units, have been used for reliable power supply to remote settlements. The vulnerability of a hybrid power plant is its dependence on external climatic conditions and power units require fuel. To solve this problem, it is proposed to supplement hybrid systems with the use of power systems based on the day-night temperature difference. Today, there are no developed circuit solutions for the structure of a hybrid electrical complex based on renewable energy sources with a system of daily temperature difference in its composition according to a scheme with a common AC bus. (Research purpose) The research purpose is developing electric circuits of an autonomous hybrid power plant based on renewable energy sources with a temperature change system taking into account the load and determining the turn-on time of the gasoline generator. (Materials and methods) Considered an electrical complex of hybrid type with four sources of electrical energy, which includes a system of daily temperature difference. (Results and discussion) We have developed schemes for an autonomous hybrid electrical complex based on renewable energy sources with a temperature change system and an alternating current bus for power supply to remote agricultural facilities. The problems of the complex when using several inverters operating on one AC bus in the circuit and ways to solve them were shown. We calculated the loads for each power system and deduced the condition for switching on the gasoline power unit in adverse weather conditions. (Conclusions) It was determined that the developed electrical circuits with a load control unit and a common master generator of a hybrid energy system based on renewable energy sources with a temperature difference power system allow creating an optimal mode of its operation and managing the entire hybrid system more efficiently.

Developing a Pilot Biogas-Solar PV System for Farming Communities in Botswana: Case of Palapye

Palapye is one of the fastest growing urban centers in Botswana. The projection of this urbanization shows a subsequent high rate of waste generation in the future with a composition of over 50 % of organic compounds from discarded foods. Several studies show that there is currently no effective waste management system in this town. For this reason, this paper sought to succinctly propose the design of a pilot 9 kW Biogas-Solar Photovoltaic (PV) Hybrid Mini-grid (BSPVHM) as a tool for an effective waste management plan and an alternative energy and agricultural solution for local farming communities. The designed pilot BSPVHM is composed of four sections which are the power generation section (with a 5-kW biogas and a 4 kWp solar PV power units), the power back-up section (with a 5 kVA diesel genset and a 6-kWh lithium-ion battery), the energy management system (EMS) section (with a 4.6 kW inverter and remote and on-site monitoring instruments) and the power supply section (with a low voltage cable). The town of Palapye was selected as the site of the pilot project because of its high waste generation capacity estimated at an average of 0.20 kg/capita/day from various categories of domestic sources. Additionally, the noticeable presence of farming communities and the yearly solar photovoltaic power potential ranging between 1753 - 1899 kWh were other reasons for this selection. Based on these available ressources, it was assumed that BSPVHM will supply at domestic scale, solar power from panels for 12 hours from 6 AM to 6 PM, power from the biogas generator for 6 hours from 6 PM to 12 AM and power from the back up section from 12 AM to 6 AM. The supply of electricity will be done autonomously by the BSPVHM system under a limited physical monitoring.

Smart Energy Management in Virtual Power Plant Paradigm With a New Improved Multilevel Optimization Based Approach

A virtual power plant (VPP) is a cloud based distributed power plant that aggregates the capacities of diverse distributed energy resources (DERs) for the purpose of enhancing power generation as well as trading or selling power on the electricity market. The main issue faced while working on VPPs is energy management. Smart energy management of a VPP is a complex problem due to the coordinated operation of diverse energy resources and their associated uncertainties. This research paper proposes a real-time (RT) smart energy management model for a VPP using a multi-objective, multi-level optimization-based approach. The VPP consists of a solar, wind and thermal power unit, along with an energy storage unit and some flexible demands. The term multi-level refers to three different energy levels depicted as three homes comprising of different amounts of loads. RT operation of a VPP is enabled by exploiting the bidirectional communication infrastructure. Multi-objective RT smart energy management is implemented on a community-based dwelling system using three alternative algorithms i.e., hybrid optimal stopping rule (H-OSR), hybrid particle swarm optimization (H-PSO) and advanced multi-objective grey wolf optimization (AMO-GWO). The proposed technique focuses on achieving the objectives of optimal load scheduling, real-time pricing, efficient energy consumption, emission reduction, cost minimization and maximization of customer comfort altogether. A comparative analysis is performed among the three algorithms in which the calculated real-time prices are compared with each other. It is observed that on average H-PSO performs 7.86 % better than H-OSR whereas AMO-GWO performs 10.49% better than H-OSR and 5.7% better than H-P-SO. This paper concludes that AMO-GWO is the briskest, most economical, and efficient optimization algorithm for RT smart energy management of a VPP.

Day-Ahead and Intraday Dispatch of an Integrated Biomass-Concentrated Solar System: A Multi-Objective Risk-Controlling Approach

Solar energy and bioenergy are two leading renewable forms of energy in the move toward a near-zero-emission electric power industry. Concentrated solar power units coupled with thermal storage and biomass power plant offer dispatchable electricity, raising their ever-growing role in future renewable-dominated networks. This paper proposes a day-ahead and intraday dispatch model for maximizing the profit of an Integrated Biomass-Concentrated Solar (IBCS) system considering the synergies arising from their coupled operation. To sensibly capture uncertainty and decision sequence of real-life electricity markets, a two-stage stochastic structure is proposed, while the solar-related uncertainty is involved using Information Gap Decision Theory (IGDT). The model is complemented with a novel multi-objective architecture based on the compound of IGDT and Conditional Value-at-Risk (CVaR), which allows handling risk exposure to both stochastic and IGDT inputs. The Pareto strategies in the multi-objective model are extracted through an expanded form of the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -constraint method, whereas <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a posteriori</i> approach based upon the out-of-sample assessment is applied to derive the optimal dispatch pattern among the generated Pareto strategies. The simulation results demonstrate that: 1) the proposed integrated dispatch model achieves substantial profitability, and 2) the performance of the suggested CVaR-IGDT model is superior to conventional approaches.

Modeling, Analysis and Optimization of Grid-Integrated and Islanded Solar PV Systems for the Ethiopian Residential Sector: Considering an Emerging Utility Tariff Plan for 2021 and Beyond

Currently, difficulties such as the depletion of fossil fuel resources and the associated environmental pollution have driven the rise of other energy systems based on green energy sources. In this research, modeling and a viability study of grid-connected and islanded photovoltaic (PV) power systems for supplying the residential load in Mekelle City, Ethiopia, were carried out considering the country’s emerging utility tariff plan for 2021 and beyond. The technical viability of the proposed supply option was analyzed using PVGIS, PVWatts and HOMER Pro tool, while the economic and environmental optimization aspects were carried out using HOMER Pro. Sensitivity analyses and output comparisons among the three renewable energy simulation tools are presented. The results showed that under the consideration of an incremental electricity tariff plan (up to 2021), the analyzed cost of energy of the grid/PV system is around 12% lower than the utility grid tariff. Moreover, we also found that by taking the continuous global solar PV cost reduction into account, the cost of energy of the modeled islanded operation of solar PV power units totally broke the grid tariff in Ethiopia after 2029 based on the tariff for 2021 and well before with the expected escalation of the grid tariff on an annual basis. The technical performance of the system realized through PVGIS and PVWatts was almost comparable to the HOMER Pro outputs. Thus, this investigation will offer a clear direction to the concerned target groups and policy developers in the evolution of PV power supply options throughout the technically viable locations in the country.

Towards Renewable-Dominated Power Systems Considering Long-Term Uncertainties: Case Study of Las Palmas

In this paper, we analyze the generation, storage and transmission expansion of the isolated power system of Las Palmas (Spain) for 2050. This power system comprises two isolated systems: Lanzarote-Fuerteventura and Gran Canaria. The generating, storage and transmission capacity to be built is determined by solving a two-stage stochastic investment model taking into account different long-term uncertain parameters: investment costs of immature technologies of power production and storage, annual demand growth, number of electric vehicles, rooftop solar penetration and natural gas prices. The possibility of linking together the isolated power systems of Lanzarote-Fuerteventura and Gran Canaria for reaching a higher penetration of renewable units is also considered. The operation of the power system is simulated by considering the day-ahead energy and reserve capacity markets. The variability of the hourly available wind and solar power, and the demand level are modeled by using a set of characteristic days to represent the target year. The performance of the resulting power system is assessed by conducting an out-of-sample analysis using the AC model of the power system. The numerical results show that a future configuration of Las Palmas power system mainly based on solar and wind power units can be achieved with the support of gas units and storage.

Aerial Tramway Sustainable Monitoring with an Outdoor Low-Cost Efficient Wireless Intelligent Sensor

Infrastructures such as aerial tramways carry unique traffic operations and have specific maintenance requirements that demand constant attention. It is common that old structures lack any type of automatization or monitoring systems, relying only on human judgment. Owners are interested in implementing techniques that assist them in making maintenance decisions, but are reluctant to invest in expensive and complex technology. In this study, researchers discussed with the owners different options and proposed a sustainable and cost-efficient solution to monitor the Sandia Peak Tramway operations with just two strategically located acceleration sensors. To maximize the success options researchers worked with the owners and developed a sensor that satisfied their needs. A Low-cost Efficient Wireless Intelligent Sensor 4—Outdoors (LEWIS 4) was developed, tested and validated during the experiment. Two solar-powered units were installed by the tramway staff and recorded data for three days. When retrieved, researchers analyzed the data recorded and concluded that with only two sensors, the acceleration data collected were sufficient to determine the position and location of the tramway cars. It was also found that the sensor on the tower provides data about the cable–tower interaction and the forces caused by the friction on the system, this being a critical maintenance factor. This work summarizes a methodology for infrastructure owners consisting of guidelines to design a sustainable and affordable monitoring approach that is based on the design, development and installation of low-cost sensors.

Risk-involved optimal operating strategy of a hybrid power generation company: A mixed interval-CVaR model

In this paper, a hybrid power generation company consisting of a concentrated solar power unit, wind turbines, a battery system, and a demand response provider is established to take part in electricity markets. The operating strategy of the hybrid power generation company in day-ahead and adjustment (intraday) markets is determined based on their coordinated operation. To tackle the intrinsic uncertainties, for the first time, a mixed stochastic-interval model is proposed which addresses the uncertainty in demand response and solar energy via interval optimization. The examined problem is formulated as a multi-objective optimization problem in which the risk of both stochastic and interval parameters can be involved. On this basis, the proposed operating strategy covers three objective functions, namely, expected radius and midpoint of the hybrid power generation company's profit together with the conditional value-at-risk. Accordingly, the normal boundary intersection and lexicographic optimization techniques are utilized to derive feasible solutions. Lastly, numerical results are presented and the performance of the proposed framework is investigated. The results indicate that the suggested model can be efficiently used to handle the decision-maker's preference over interval and stochastic parameters, and the risk criterion associated with interval parameters becomes larger as the forecasting errors increase.

Visual Processing and Analysis of Landslide Deformation Based on GNSS

For landslide surface monitoring, the Global Navigation Satellite System (GNSS) has been widely used in landslides due to its real-time, all-weather, high-precision, simple operation and a high degree of automation. However, these data are not intuitive and visual data will be more interesting for users without professional knowledge. At the same time, the conventional data representation method is in the form of curves or tables for three-dimensional data of landslide surface deformation collected by GNSS. To make the data more intuitive, clear and valuable, it is easier for people to understand the process of landslide deformation and finally realize the visualization of decision. Here we show that a polar coordinate system rather than a Cartesian coordinate system is adopted to visualize the horizontal data, which not only shows the horizontal deformation of the landslide, but also easily knows the direction of the landslide deformation. The vertical data is in the form of slices rather than curves, which not only shows the deformation of the landslide surface, but also shows the process of the vertical change of the landslide in terms of the time series. Single GNSS monitoring station is composed of a GNSS receiver, GNSS antenna with random, a solar power unit, and a network transmission module. The system can be powered by the solar energy system, which can realize 24-hour unmanned operation, 7 days a week. The system can receive satellite signals in real-time process and analyze deformation data, then it automatically broadcast early warning information. Our results demonstrate that it is a better choice that the thematic map of Geographic Information System (GIS) is a technical system for collecting, storing, managing, calculating, analyzing and displaying geographic data supported by computer hardware and software systems. Here we show that the multi-dimensional properties of deformation monitoring and multiple expressions of the attribute values are displayed synchronously in order to obtain more useful information from the visual graphics.

Profit-Based Unit Commitment for a GENCO Equipped with Compressed Air Energy Storage and Concentrating Solar Power Units

With the advent of restructuring in the power industry, the conventional unit commitment problem in power systems, involving the minimization of operation costs in a traditional vertically integrated system structure, has been transformed to the profit-based unit commitment (PBUC) approach, whereby generation companies (GENCOs) perform scheduling of the available production units with the aim of profit maximization. Generally, a GENCO solves the PBUC problem for participation in the day-ahead market (DAM) through determining the commitment and scheduling of fossil-fuel-based units to maximize their own profit according to a set of forecasted price and load data. This study presents a methodology to achieve optimal offering curves for a price-taker GENCO owning compressed air energy storage (CAES) and concentrating solar power (CSP) units, in addition to conventional thermal power plants. Various technical and physical constraints regarding the generation units are considered in the provided model. The proposed framework is mathematically described as a mixed-integer linear programming (MILP) problem, which is solved by using commercial software packages. Meanwhile, several cases are analyzed to evaluate the impacts of CAES and CSP units on the optimal solution of the PBUC problem. The achieved results demonstrate that incorporating the CAES and CSP units into the self-scheduling problem faced by the GENCO would increase its profitability in the DAM to a great extent.

A novel parabolic solar dish design for a hybrid solar lighting-thermal applications

A concentrating solar power (CSP) unit was designed to work as a hybrid system to supply the required energy for heat water and high intensity light. The system consists of a parabolic solar dish that reflected light in a set of optical fiber light inside a receiver. In turn, this light was transmitted to an indoor photovoltaic (PV) panels to produce electrical energy or used directly as a source of light during the day. This study revealed the following points: (i) the increased number of fiber optics, the improved efficiency of solar panel and power generated; (ii) the efficiency of the hybrid solar system was 23.62%. (iii) when the separation distance between the fiber optics and the PV module was closed, the level of the power generated becomes higher; and finally; (v) this application is more suitable for a limited area in the roof of the building.