Intisar A. Sajjad

A probabilistic approach to study the load variations in aggregated residential load patterns

The demand side in a power system has key importance in the evolving context of the energy systems. Exploitation of possible flexibilities of the customers behavior is considered as an important option to promote demand response programmes and to achieve greater energy savings. For this purpose, the first action required is to augment availability of information about consumption patterns. The electricity consumption in a residential system is highly dependent on various types of uncertainties due to the diverse lifestyle of customers. Knowledge about the aggregated behavior of residential customers is very important for the system operator or aggregator to manage load and supply side flexibilities for economic operation of the system. In this paper, the effect of sampling time is evaluated for different residential load aggregations using probabilistic approach. A binomial probability distribution model is used to extract trends in increase or decrease in demand with respect to time evolution of a typical day. For each case study scenario, confidence intervals are calculated to assess the uncertainty and randomness in load variation trends. The findings of this study will lead towards better management of demand and supply side resources in a smart grid and especially for microgrids.

Net metering benefits for residential buildings: A case study in Italy

Contrary to expectations, the development of smart (mini) grids is slow. Due to drastic improvements in innovative technologies, the reasons are not strictly technical but the problem mainly lies in regulatory barriers. The current business models are centric to utilities rather than customers. Net metering is a key enabling factor for smart (mini) grids. This paper addresses the economic benefits of net metering for individual residential customers. Energy demand for the individual apartments and common areas is calculated using the daily energy consumption behavior of occupants for typical days of each month of the year. Photovoltaic generation is estimated via PVGIS for a residential building in Italy. The proposed net metering scheme is applied on the aggregate energy demand of selected building without any modification in the current energy billing and net metering tariffs. Results show the noticeable difference in the savings of individual apartments.

Potential of residential demand flexibility - Italian scenario

Aggregator in a microgrid is responsible for its secure and economic operation. As far as system economics is concerned, there are many factors upon which energy cost is dependent, for example peak demand rates and penalties due to violations in energy purchase contracts. Extra charges due to high energy demand and contract violation penalties can be avoided using demand side flexibility. Demand side flexibility has many benefits in normal as well as emergency conditions like less cost and quick response. Residential loads are the major part to be supplied and have 7 days and 24 hour availability for flexible operation. This paper presents the potential for effective use of demand flexibility from residential customers for peak reduction. Demand flexibilities are calculated with Monte Carlo Simulation using probabilistic data of Italian households. Different scenarios are generated to demonstrate the effectiveness of flexibility in residential sector.

Effect of aggregation level and sampling time on load variation profile — A statistical analysis

Electrical load patterns that represent the consumption level are affected by different types of uncertainties associated with customers behavior and with keeping acceptable comfort level. The resulting aggregated load pattern indicates the system response that may be more or less flexible in different periods of time. Many research activities have been dedicated to explore the flexibility of load demand using load patterns and associated uncertainties but little work is found on investigating the effect of sampling time and aggregation level on the shape of the load patterns. Knowing the characteristics of the electrical load patterns is a key aspect to manage load and supply side flexibilities for most economic system operation. This paper addresses the effects of sampling interval as well as aggregation level on the characteristics of the aggregated load patterns. The study is carried out on the basis of comprehensive statistical computations on collected data using load variation profiles, because these profiles embed the information on the load variation trend. The findings of this study may be used for load forecasting and management, generation allocation and economic operation of smart grid system, especially for microgrids.

A statistical analysis of sampling time and load variations for residential load aggregations

The electrical load in residential systems highly depends on various types of uncertainty due to the lifestyle of the residential customers. Enhancing the knowledge on the aggregated behavior of these customers is particularly important for the distribution system operator, also with the aim of determining the potential flexibility of the residential demand and setting up the economic terms of the electricity provision to the customers. This paper addresses the impact of the sampling time interval with which the customer data are gathered on the characteristics of the aggregated electricity demand. A dedicated statistical analysis has been carried out to highlight the load variations occurring for different numbers of aggregated extra-urban residential customers. The results are represented in the form of normalized percentage load variations, using the number of samples and the maximum demand variation to construct the normalizing factor. The results indicate how the sampling time interval affects the load variations for different levels of customer aggregation.

Demand flexibility time intervals for aggregate residential load patterns

This paper deals with the definition of demand flexibility time intervals. These intervals are extracted from the binomial probability model of load variation patterns with the two possible categories of increase and non-increase in demand. These intervals along with the information on the coefficient of variation of the aggregate demand are used to assess the potential of demand flexibility exhibited by the aggregate residential demand in different periods of the day. The results of the proposed approach are useful for the distribution system operator or an aggregator to effectively set up demand response programmes in suitable time slots of the day.

Impact of time varying load models on PV DG planning

A constant load and generation model is generally considered in planning studies that pertain to Distributed Generation (DG) integrated distribution systems. However, such considerations may result in misleading and inconsistent values for the voltage profile, loss reduction, payback period, deferral values, and other related calculations due to the variation of both renewable energy-based generation and load demand. This paper investigates the impact of time varying voltage dependent load models on the DG planning studies. The study is based on the comparative assessment of different impact indices, penetration level, active and reactive power intake, active and reactive power loss, and Mega Volt Ampere support offered by the installation of photovoltaic based DG for different time varying load models. The outcomes of the current research work reveal that the time varying load modeling approach has significant impact on the distribution systems.A constant load and generation model is generally considered in planning studies that pertain to Distributed Generation (DG) integrated distribution systems. However, such considerations may result in misleading and inconsistent values for the voltage profile, loss reduction, payback period, deferral values, and other related calculations due to the variation of both renewable energy-based generation and load demand. This paper investigates the impact of time varying voltage dependent load models on the DG planning studies. The study is based on the comparative assessment of different impact indices, penetration level, active and reactive power intake, active and reactive power loss, and Mega Volt Ampere support offered by the installation of photovoltaic based DG for different time varying load models. The outcomes of the current research work reveal that the time varying load modeling approach has significant impact on the distribution systems.

Dynamic Economic Dispatch Incorporating Photovoltaic and Wind Generation using Hybrid FPA with SQP

ABSTRACT This paper presents a hybrid approach to explore the effect of wind and photovoltaic energy on conventional power network using dynamic economic dispatch. This model deals with stochastic and unpredictable character of wind and solar power output while considering the gaps between the real and predicted output power. A hybrid flower pollination algorithm with sequential quadratic programming is applied to reduce the overall operating costs of generators, while allocating generation to the committed units. The proposed technique is applied on power system having 13 solar units and a wind plant connected with 3, 5, and 10 generating units, respectively. The results of algorithm simulations performed in MATLAB 2014b confirm the competence of the suggested method.

Economic analysis of net metering regulations for residential consumers in Pakistan

Net metering is used to incentivize the distributed generation owners. It is introduced in Pakistan with the aim to promote the building integrated local generation. Presently, it is hard to find any study on the economic incentive indicators of the net metering policy for residential customers in Pakistan. This paper presents the economic evaluation of net metering benefits to the individual residential consumers in the presence of Building Integrated PV (BIPV) system under current net metering regulations in Pakistan. The energy demand of the individual apartments and the common area services inside the building is calculated by means of daily energy usage of the residents for a typical day. The aggregate demand of the residential building, comprising of 100 residential units and common area services, is calculated. The estimation of power profiles of the PV generation system is carried out with the help of PVGIS. At the end, the economic analysis of the proposed net metering scheme is presented. The net metering policy is found to be feasible up-to 50 kWp PV capacity when it is applied on the common area services only and the billing is carried out individually. When it is implemented on the aggregate energy demand of the entire residential building, the annual savings are observed for installed PV capacity above 80 kWp.

Flexibility assessment indicator for aggregate residential demand

In the modern power system, characterization of customers demand plays a vital role for Demand Side Management. Demand flexibility information, extracted from the aggregate demand behaviour of customers, presents more comprehensive picture for the aggregator or system operator. There is an existence of diverse flexible time slots during a day in different time periods. Due to the diverse energy consumption behaviour of the residential customers, extraction of flexibility and its associated potential time durations is a challenging task. To extract flexibility information from aggregate residential customers, a flexibility indicator is formulated in this paper. Information presented gives an indication about flexible time slots in terms of numerical value that is useful for a system operator or an aggregator for demand side flexibility assessment and this will lead to design and initiate DSM programs.