Nadali Mahmoudi

• PhD
• Manager at Ernst & Young (EY)

In this study, a privacy-based demand response (DR) trading scheme among end-users and DR aggregators (DRAs) is proposed within the retail market framework and by distribution platform optimiser. This scheme aims to obtain the optimum DR volume to be exchanged while considering both DRAs' and customers' preferences. A bi-level programming model is...

One of the key features of future power networks, referred to as smart grids, is deploying demand-side resources in order to reduce the stress at the supply side. This implies active participation of electricity customers, as a societal network, in the power networks, as a physical network, which increases the interdependencies of these two network...

This study develops a new multi-stage (dynamic) approach for the co-planning of power and gas systems to deal with variable renewable energy resources (VREs). The model is formulated using a stochastic programming framework to accurately capture the unfolding of both short and long-term uncertainties faced by power and gas systems. The effects of h...

Abstract— In this work a new trading framework for demand response (DR) aggregators is proposed using a non-probabilistic model. In this model, DR is acquired from consumers to sell it to the purchasers by aggregators. Two programs, i.e., time-of-use (TOU) and reward-based DR program, are implemented to obtain DR from consumers. Then, the obtained...

Analyzing the probability of power transformer failure is challenging, because to observe a sufficient number of failures requires a fleet size larger than is often operated by one utility. Parametric distributions have been applied to small data sets to model failure. However, an assumption is that the failure follows the chosen distribution. Reli...

This paper proposes a new self-scheduling framework for demand response aggregators, which contributes over the existing models in following aspects. The proposed model considers the uncertainties posed from consumers and electricity market prices. Further, the given model applies the information-gap decision theory (IGDT) in the self-scheduling pr...

This paper extensively models the interactions of emerging players in future power systems to analyze their impacts on electricity markets. To this end, renewable energy resources are modeled in such a way that wind power poses uncertainty on the supply side, and rooftop photovoltaics (PVs) add uncertainty to the demand side. Moreover, both uncontr...

This study deals with new challenges in the long-term planning of power systems in the presence of high variable renewable energy resources (VRE). To this end, a stochastic multi-stage planning model is proposed, through which the investment decisions on the new generation and transmission systems are made in several stages of the planning horizon...

With the rapid growth of Electric Vehicles (EVs) in distribution systems, a new player, called EV parking lot operator (EV PLO), is emerging around the world. Furthermore, the integration of distributed generation in the distribution level, in particular, renewable energy sources (RESs), is leading to the establishment of various markets in distrib...

Integrating wind and solar energy resources poses intermittency to power systems, which faces independent system operators with new technical and economic challenges. This study proposes a novel model to integrate the uncertainties of wind power on the supply side and roof‐top solar photovoltaic (PV) on the demand side. To cope with their uncertain...

This paper assesses long term electricity planning under uncertain load growth, gas price, renewable production and new technologies' investment costs for the state of Queensland, Australia in 2030. A stochastic programming approach is mathematically formulated to decide which technology to be built, while determining its capacity and location. Add...

A 24-bus system is presented including 10 wind farms, 11 demand response aggregators (DRAs), and 4 electric vehicle aggregators (EVAs).

This paper investigates the impacts of rooftop photovoltaic (PV) penetration as well as gas market uncertainties on the generation planning decisions. These issues are paramount in the state of Queensland in Australia that has traditionally been reliant on coal based generation. A Generation Expansion Planning problem is used to evaluate alternativ...

This paper studies the Australian market conditions and subsidies in place to promote the growth of wind power through the use of a stochastic linear programming model. This model optimizes the profit obtained for a static investment based on a variety of wind and price scenarios. It is subject to different constraints which focus on the amount of...

This paper deals with wind power offering strategies in day-ahead markets. A new plan is proposed in which a wind power producer participates in the day-ahead market while employing demand response (DR) to smooth its power variations. In this context, a new DR scheme is presented through which the wind power producer is able to achieve DR by establ...

This paper considers a wind power producer playing strategically in a day-ahead market while willing to set demand response (DR) contracts with a DR aggregator. To this end, a bilevel problem including a single leader and two followers is formulated. The wind power producer is the leader aiming at maximizing its profit through offering into a day-a...

This paper proposes an energy offering strategy for wind power producers. A new trading plan is presented through which a wind power producer can employ demand response (DR) to maximize its profit. To consider DR, a new DR scheme is developed here. The proposed plan includes two steps: The first step takes place on a day-ahead basis. The correspond...

This paper proposes a new framework in which demand response (DR) is incorporated as an energy resource of electricity retailers in addition to the commonly used forward contracts and pool markets. In this way, a stepwise reward-based DR is proposed as a real-time resource of the retailer. In addition, the unpredictable behavior of customers partic...

Load profiling is essential in power systems operation and planning. Accurate load profiles lead to a better load scheduling as well as load and price forecasting. Clustering techniques are used to provide an enhanced knowledge on electrical load patterns. This paper deals with clustering methods to analyze Queensland's load data. The K-means clust...

This paper proposes a new wind offering strategy in which a wind power producer employs demand response (DR) to cope with the power production uncertainty and market violations. To this end, the wind power producer sets demand response (DR) contracts with a DR aggregator. The DR aggregator behavior is modeled through a revenue function. In this way...

This paper proposes a new trading framework which allows demand response (DR) aggregators to procure DR from consumers and sell it to purchasers. The aggregator obtains DR from the proposed price and incentive-based DR programs. On the other side, the DR outcome is sold to purchasers through the proposed agreements, namely fixed DR contracts and DR...

A new demand response (DR) scheme from the retailers’ point of view is presented in this paper. The proposed DR scheme allows a retailer to decide how to buy DR from aggregators and consumers. Various long-term and real-time DR agreements are proposed, where they are considered as energy resources of retailers in addition to the commonly used provi...

This paper deals with short-term decisions made by electricity retailers. It is assumed that a retailer aims to minimize the cost of procuring energy from two sources: one is the commonly-used pool market, and the other is the demand response (DR) program proposed in this paper. A reward-based DR is mathematically formulated where the volume of loa...

This paper addresses the problem of day-ahead generation scheduling for isolated micro-grids with renewable energy generators. Geothermal, solar and diesel generator are considered as the only sources for supplying electricity to the micro-grid. The aim of this paper is to illustrate how demand response measures can be utilized to meet the demand d...

In the electricity market, it is highly desirable for suppliers to know the electricity consumption behavior of their customers, in order to provide them with satisfactory services with the minimum cost. Information on customers' consumption pattern in the deregulated power system is becoming critical for distribution companies. One of the suitable...

This paper introduces an innovative methodology based on clustering techniques to provide the retailer with a strategy to select the most suitable customers for implementing demand response programs (DRPs). The main aim is to minimize the cost of DRPs for supplying the demand during power shortage periods. For this purpose, customers with similar l...

In this paper, an innovative strategy for optimal price offering to customers for maximizing the profit of a retailer is proposed. This strategy is based on load profile clustering techniques and includes three stages. For the purpose of clustering, an improved weighted fuzzy average K-means is proposed. Also, in this paper a new acceptance functio...

In the competitive environment, it is necessary for a retailer to increase his/her profit as much as possible. There are few researches focused on the subjects related to the retailer and the retail market. In addition, those researches have mostly focused on the participation of the retailer in the wholesale market. In order to determine the optim...

In the electricity market, it is highly desirable for suppliers to know the electricity consumption behavior of their customers, in order to provide them with satisfactory services with the minimum cost. Information on customers' consumption pattern in the deregulated power system is becoming critical for distribution companies. One of the suitable...

In restructured power systems, the ISO should maintain the power system in an acceptable level of security. The amount of available transfer capability and spinning reserve are two important indicators of power system security. This paper presents a strategy for the allocation of demand response programs in restructured power system. The proposed a...

There are several pattern-based clustering methods which are used for different applications such as pattern recognition, data mining, etc. In recent years, some of these methods are implemented in power system studies, especially for clustering load curves for designing suitable tariffs, demand response programs selection, etc. Choice of the best...

Clustering is a process that partitions a set of feature vectors into clusters. There are different applications of load curves clustering in regulated and deregulated environment such as system analysis, load and price forecasting, distributed resource selection, better tariff design, etc. In this paper we evaluate performances of two clustering m...

In the electricity market, it is highly desirable for suppliers to know the electrical behavior of their customers, in order to provide them with satisfactory services at the least cost. One of the most important objectives in such case is designing tariff for customers. Electricity providers have been given new degrees of freedom in defining tarif...