Navid Haghdadi

Clustering-based optimal sizing and siting of photovoltaic power plant in distribution network

This article focuses on sitting and sizing of PV units aiming at minimizing the total power loss in distribution network. Due to fluctuation in output power of photovoltaic and variable nature of the loads in electricity network, for evaluating power loss and the bus voltages, the grid should be simulated for all days of the year and all hours of the day. However, this simulation is time consuming and costly. Consequently the clustering method is employed to find some days as representatives and simulate the grid for these days rather than all days of the year. If the representatives indicate the nature of whole data very well, the error of simulating the grid in this case is negligible comparing with simulating it for all days. In order to assess the performance of the clustering methods and finding the optimal number of clusters, three clustering validity indices are used. The 33 buses test system and irradiation profile of Tehran in a year are considered. Various types of loads are assigned to loads in selected network. The network is simulated for all days and its result is compared with clustering-based method.

A novel temperature estimation method for solar cells

In this paper, an effective approach for estimating the operating temperature of a photovoltaic (PV) module is presented. The developed method is simple and does not need any additional hardware. The proposed approach uses an analytical formula to derive the temperature from the maximum power point (MPP) voltage and current. The effectiveness of the new method is investigated through some conducted simulations in MATLAB/Simulink environment and its validity is verified by experiment on REC-AE220 solar modules.

A clustering-based preprocessing on feeder power in presence of photovoltaic power plant

The equivalent power of feeder, as one of the inputs of chronological simulation of a power network in presence of a large scale photovoltaic power plant, needs some preprocessing in order to reduce simulation time. The Fuzzy C-means, Gustafson Kessel, K-means and K-medoid methods are applied to find a few numbers of representatives for the equivalent power of feeder. The proposed techniques are validated and optimal number of clusters is found out by means of several clustering validity indices. A comparison with a conventional technique is made on the score of invariant separation index.

Multi-attribute decision making for new photovoltaic power plant establishment: Iran case study

This paper deals with decision making for new photovoltaic power plant establishment in Irans electrical network. Iran Electricity network consists of 16 Regional Electricity Companies. In order to find an appropriate place for Photovoltaic power plant, different aspects of the problem have been evaluated and different relative weights are assigned to them. Finally, problem is formulated and solved using Expert Choice software by AHP method.

Real time generation mapping of distributed PV for network planning and operations

With growing penetrations of distributed photovoltaic (PV) systems in Australian electricity networks, it is increasingly important for network planners and operators to better understand, predict and hence manage the impact of these systems throughout their networks. Time series estimates of distributed PV generation mapped to different Australian geographic regions are now being created from a sample of these distributed PV systems that report their generation in near real time. In this paper a range of potential applications of these spatial PV generation traces are discussed, with a focus on their potential contribution towards transmission network planning and operations. These include estimating the impact of PV on peak demand, load forecasting, situation awareness and dynamic line ratings.

Assessing the representativeness of ‘Live’ distributed PV data for upscaled PV generation estimates

The incorporation of distributed PV generation data into power system planning and operation is becoming increasingly important as penetrations of PV systems on Australian distribution networks continue to grow. However, the availability of such data is currently very limited. The APVI Live PV Map (Live Map) provides near real-time distributed PV generation estimates in 57 different regions across Australia based on some 6000 PV systems reporting their generation online. This data has a wide range of potential applications including, for example, network planning or PV performance assessment. In this paper we investigate the characteristics of the PV systems contributing to the Live Map database, in order to assess its accuracy and suitability for providing total distributed PV generation estimates for power system planning and operational purposes. The study compares the sample of PV systems contributing data to the Live Map database with the total set of PV systems in Australia, according to the Clean Energy Regulators (CERs) database. Representativeness is assessed in terms of PV system location, size, age, and inverter manufacturer. The accuracy of the APVI Live Map PV generation estimates for individual regions is assessed by comparison with a separate database of historical interval metered household PV generation from the Ausgrid network. Finally, an example of the application of distributed PV data to electricity network planning is provided to highlight the potential value of these PV generation estimates.

Demand response program evaluation for plugin hybrid electric vehicles purchase encouragement

The rate of using plugin hybrid electric vehicles (PHEV) will be increased in near future in Iran. In the present article, a comparison between existing electricity pricing method (BR) and time of use (TOU) demand response program was made in order to study whether consumers would be motivated purchasing PHEVs or not. The total monthly electricity consumption and the monthly electricity bill utilizing both methods are calculated. Aimed at economic viability evaluation, rate of return (ROR) and net present value (NPV) are calculated in different cases. A motivating loan is entered to cost and benefit analysis and further economic analysis is made.

Impact of Distributed Photovoltaic Systems on Zone Substation Peak Demand

Australia has likely the worlds highest residential photovoltaic (PV) system penetration. In this paper, the impact of distributed PV on peak demand at different distribution network zone substations (ZSs) is assessed by upscaling 15 min PV generation data from 270 distributed PV systems across Sydney, Australia, and comparing it with load data from 138 ZS serving the Sydney region. Gross load (load had there been no PV) was estimated, allowing the impact of current and higher PV penetrations on the value and time of peak at the different ZSs to be assessed. A probabilistic assessment of the impact of PV on ZSs is conducted, based on the availability of PV during the peak demand periods. To better understand the impact of PV on peak demand, K-means clustering is used to group ZSs based on PV generation during peak periods as the clustering features. Mapping of PV availability across percentage of peak times for all ZSs highlights the interannual variability of peak reductions and the potential impact of short-term load shifting. The impact of different penetration levels of distributed PV on the peak demand of the entire distribution network is also assessed by aggregating the ZS loads.

Pricing the urban cooling benefits of solar panel deployment in Sydney, Australia

Cities import energy, which in combination with their typically high solar absorption and low moisture availability generates the urban heat island effect (UHI). The UHI, combined with human-induced warming, makes our densely populated cities particularly vulnerable to climate change. We examine the utility of solar photovoltaic (PV) system deployment on urban rooftops to reduce the UHI, and we price one potential value of this impact. The installation of PV systems over Sydney, Australia reduces summer maximum temperatures by up to 1 °C because the need to import energy is offset by local generation. This offset has a direct environmental benefit, cooling local maximum temperatures, but also a direct economic value in the energy generated. The indirect benefit associated with the temperature changes is between net AUD

Clustering power demand for feasibility study on transition to plugin hybrid electric vehicles

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