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The future of power systems known as smart grids is expected to involve an increasing level of intelligence and incorporation of new information and communication technologies in every aspect of the power grid. Demand response resources and gridable vehicle are two interesting programs which can be utilized in the smart grid environment. Demand response resources can be used as a demand side virtual power plant (resource) to enhance the security and reliability of utility and have the potential to offer substantial benefits in the form of improved economic efficiency in wholesale electricity markets. An economic model of incentive responsive loads is modelled based on price elasticity of... 

In this paper, the operation of a future distribution network is discussed under the assumption of a multi-carrier microgrid (MCMG) concept. The new model considers a modern energy management technique in electricity and natural gas networks based on a novel demand side management (DSM) which the energy tariff for responsive loads are correlated to the energy input of the network and changes instantly. The economic operation of MCMG is formulated as an optimization problem. In conventional studies, energy consumption is optimized from the perspective of each infrastructure user without considering the interactions. Here, the interaction of energy system infrastructures is considered in the... 

Advancements in smart grid technologies have made it possible to apply various options and strategies for the optimization of demand response (DR) in electricity markets. DR aggregation would accumulate potential DR schedules and constraints offered by small- and medium-sized customers for the participation in wholesale electricity markets. Despite various advantages offered by the hourly DR in electricity markets, practical market tools that can optimize the economic options available to DR aggregators and market participants are not readily attainable. In this context, this paper presents an optimization framework for the DR aggregation in wholesale electricity markets. The proposed study... 

Demand response programs can be regarded as a risk management approach for retailers in electricity market. In case of high wholesale electricity price, implementation of demand response will reduce the economic risk exposure of the retailer. Realization of demand response requires investment in various sectors, and therefore, there is a need for economic valuation in order to determine the economic profit gained. This paper attempts to evaluate the economic value of demand response programs by the use of real option valuation method. In this regard, at first demand response programs are converted to option contracts. Then, the profit of retailer resulting from the demand response is... 

This paper presents a hierarchical demand response (DR) bidding framework in the day-ahead energy markets which integrates customer DR preferences and characteristics in the ISO's market clearing process. In the proposed framework, load aggregators submit aggregated DR offers to the ISO which would centrally optimize final decisions on aggregators' DR contributions in wholesale markets. The hourly load reduction strategies include load shifting and curtailment and the use of onsite generation and energy storage systems. The ISO applies mixed-integer linear programming (MILP) to the solution of the proposed DR model in the day-ahead market clearing problem. The proposed model is implemented... 

Advancements in smart grid technologies have made it possible to apply various options and strategies for the optimization of demand response (DR) in electricity markets. DR aggregation would accumulate potential DR schedules and constraints offered by small- and medium-sized customers for the participation in wholesale electricity markets. Despite various advantages offered by the hourly DR in electricity markets, practical market tools that can optimize the economic options available to DR aggregators and market participants are not readily attainable. In this context, this paper presents an optimization framework for the DR aggregation in wholesale electricity markets. The proposed study... 

Despite of the great focus of attention dedicated to demand response (DR), the potential benefits of DR on distribution networks have not yet been quantitatively studied. This paper aims to assess DR potential impacts on major attributes of the operation of a residential distribution network. For doing so, grossly metered usage of more than 1600 residential consumers from Kainuu, Finland, is disaggregated to appliance-level load profiles. The flexibility of the load profiles is also estimated from the survey data and questionnaires. The individual profiles are then adjusted within their flexibility such that the most evenly distributed aggregated load profile is realized. Finally, the... 

Renewable energies as a solution for environmental issues have always been a key research area due to Demand Response Programs (DRPs). However, the intermittent nature of such energies may cause economic and technological challenges for Independent System Operators (ISOs) besides DRPs, since the acceptable effective solution may exceed the requirement of further investigations. Although, previous studies emphasized employing Demand Response and Renewable Energies in power systems, each problem was investigated independently, and there have been few studies which have investigated these problems simultaneously. In these recent studies, authors neither analyzed these problems simultaneously... 

Demand response enabled by time-varying prices can propel the power industry toward a greater efficiency. However, a noncoordinated response of customers may lead to severe peak rebounds at periods with lower prices. In this regard, a coordinated demand response scheme can mitigate concerns about the peak rebounds. This paper presents a system-wide demand response management model to coordinate demand response provided by residential customers. The objective of the model is to flatten the total load profile that is subject to minimum individual cost of customers. The model is first formulated as a bi-level optimization problem. It is then casted into equivalent single-level problems, which... 

The present study presents a new risk-constrained bidding strategy formulation of large electric utilities in, presence of demand response programs. The considered electric utility consists of generation facilities, along with a retailer part, which is responsible for supplying associated demands. The total profit of utility comes from participating in day-ahead energy markets and selling energy to corresponding consumers via retailer part. Different uncertainties, such as market price, affect the profit of the utility. Therefore, here, attempts are made to make use of Information Gap Decision Theory (IGDT) to obtain a robust scheduling method against the unfavorable deviations of the market... 

The multi-carrier microgrid (MCMG) is a restricted district comprising convertors and energy storage systems (ESSs) that are used to fulfill various energy demands. The structure and optimal operation of these MCMGs with regard to fulfilling multi-carrier demands are presented in relation to their rapid spread. In this paper, a two-stage optimum planning and design method for an MCMG is presented in the planning horizon. The investment and operation (fuel and maintenance) costs are considered concurrently to find the optimal type and size of components over the planning horizon. At the first stage, the genetic algorithm (GA) is applied to determine the optimal type and size of components,... 

Although demand responsive feeder bus operation is possible with human-driven vehicles, it has not been very popular and is mostly available as a special service because of its high operating costs due to intensive labor costs as well as requirement for advanced real-time information technology and complicated operation. However, once automated vehicles become available, small-sized flexible door-to-door feeder bus operation will become more realistic, so preparing for such automated flexible feeder services is necessary to take advantage of the rapid improvement of automated vehicle technology. Therefore, in this research, an algorithm for optimal flexible feeder bus routing, which... 

Demand responsive feeder transit can minimize passengers’ travel times and operator's costs by optimizing routing based on real demand. One question about the demand response feeder transit operation is whether it can be optimized with door-to-door service or with temporary stops for picking up and delivering passengers. Obviously, door-to-door service eliminates passengers’ walking distances, but it increases passenger in-vehicle travel times and vehicle operating distance and costs. On the other hand, demand responsive feeder transit with temporary stops, which designates the temporary locations picking up and dropping passengers, minimizes bus operating distance and time as well as... 

Application of residential demand response (DR) programs are currently realized up to a limited extent due to customers' difficulty in manually responding to the time-differentiated prices. As a solution, this paper proposes an automatic home load management (HLM) framework to achieve the household minimum payment as well as meet the operational constraints to provide customer's comfort. The projected HLM method controls on/off statuses of responsive appliances and the charging/discharging periods of plug-in hybrid electric vehicle (PHEV) and battery storage at home. This paper also studies the impacts of different time-varying tariffs, i.e., time of use (TOU), real time pricing (RTP), and... 

This paper summarizes a presentation to be given at the IEEE Power and Energy Society 2012 General Meeting, in the panel session Demand response: analytics, practice, and challenges in smart grid environment. The paper elaborates participation of demand response (DR) resources in electricity markets. Specially, different types of DR participation in the wholesale energy markets are discussed. Then, two DR program designs are presented which aim to enable customers' participation in day-ahead energy markets. The paper continues with presenting the modified structure of the day-ahead energy market in presence of the DR programs. The offer packages specifically designed for DR participation in... 

In this paper, the impact of demand response programs (DRPs) on reliability improvement of the restructured power systems is quantified. In this regard, the demand response (DR) model which treats consistently the main characteristics of the demand curve is developed for modeling. In proposed model, some penalties for customers in case of no responding to load reduction and incentives for customers who respond to reducing their loads are considered. In order to make analytical evaluation of the reliability, a mixed integer DCOPF is proposed by which load curtailments and generation re-dispatches for each contingency state are determined. Both transmission and generation failures are... 

Renewable energy resources, notably wind power, are expected to provide considerable portion of the world energy requirements in the near future. Many system operators around the world are challenged by the problems associated with integrating these intermittent resources into the grid. As one of the potential solutions, demand response (DR) is expected to play a major role for mitigating integration issues of intermittent renewable energy resources. In this context, this paper proposes a DR program which helps to integrate wind power by reshaping the load of the system. The DR program provides a framework to procure load reduction from DR resources in the wholesale energy market. The... 

This paper presented a combined scheduling and bidding algorithm for constructing the bidding curve of an electric utility that participated in the day-ahead energy markets. Day-ahead market price uncertainty was modeled using non-probabilistic information gap decision theory (IGDT). The considered utility consisted of generation units and a retailer part; the retailer part of the utility and its demand response program (DRP) could affect the utility's profit, which should be considered in the bidding strategy problem. The bidding strategy algorithm proposed in this paper dispatched units by optimizing the demand response programs of the retailer part. In addition, non-decreasing bidding...