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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... 

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... 

Considerable developments in the real-time telemetry of demand-side systems allow independent system operators (ISOs) to use reserves provided by demand response (DR) in ancillary service markets. Currently, many ISOs have designed programs to utilize the reserve provided by DR in electricity markets. This paper presents a stochastic model to schedule reserves provided by DR in the wholesale electricity markets. Demand-side reserve is supplied by demand response providers (DRPs), which have the responsibility of aggregating and managing customer responses. A mixed-integer representation of reserve provided by DRPs and its associated cost function are used in the proposed stochastic model.... 

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... 

Electric energy storage (EES) installations in power systems are migrating from large centralized systems to more distributed installations for microgrid applications. This trend signifies modular EES installations for the local control of buildings and processes. A centralized EES system is often dispatched by grid operators for increasing the overall efficiency and enhancing the security of power systems. The distributed EES (DEES) is locally managed by aggregators to maximize the local impact of EES, before the aggregators' adjusted load profiles are submitted to grid operators for the day-ahead scheduling. In this paper, we present and analyze two models for the hourly scheduling of... 

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... 

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... 

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... 

Reducing the emissions produced by the electric power production may be one of the most challenging problems of the electricity sector in the coming future. As one of the potential solutions, demand response (DR) can play an important role to reduce emissions and costs associated with emission reduction activities. This paper aims to assess the short-term impacts of running a DR program on a power system constrained by emissions caps. The DR program is designed to procure operating reserve from demand-side participants. A day-ahead network-constrained market clearing model with emission cap constraints is used as the assessment tool, where the DR program participants along with generating... 

Health, Margin and Risk states which in recent years are known as well-being reliability indices, provide a comprehensive adequacy assessment of bulk power system reliability studies. Conventional reliability information about power system operation only considered health and risk states which were not often adequate criteria both in system planning and utilization. It seems margin state as the intermediate condition between health and risk must be considered. Well-being method which is a approach to power system generation adequacy evaluation incorporates deterministic criteria in a probabilistic framework and provides system operating information in addition to risk assessment and can be... 

Well-Being reliability indices (Health, Margin and Risk), provide a comprehensive measure to assess the adequacy of composite power systems. Conventional reliability information about power system operation only considered health and risk states, which were not often adequate criteria in both power system planning and operation. Well-being approach for power system generation adequacy evaluation incorporates deterministic criteria in a probabilistic framework, and provides system operating information in addition to risk assessment and can be evaluated using analytical techniques. The most important part of this approach is the algorithm for calculating the probability of the states.... 

This paper addresses the midterm preventive maintenance outage scheduling problem of thermal generating units which is becoming increasingly important due to the aging of power generation fleet. In this context, a novel midterm preventive maintenance outage scheduler is proposed based on decision tree and mixed integer linear formation which explicitly considers the thermal units aging momentum in terms of failure rate. This allows the system operators to determine the thermal units' maintenance outage window based on the cost/benefit analysis of preventive maintenance tasks while optimizing the time interval between consecutive maintenance tasks. Additionally, the division of the year-long... 

This paper addresses the midterm preventive maintenance outage scheduling problem of thermal generating units which is becoming increasingly important due to the aging of power generation fleet. In this context, a novel midterm preventive maintenance outage scheduler is proposed based on decision tree and mixed integer linear formation which explicitly considers the thermal units aging momentum in terms of failure rate. This allows the system operators to determine the thermal units' maintenance outage window based on the cost/benefit analysis of preventive maintenance tasks while optimizing the time interval between consecutive maintenance tasks. Additionally, the division of the year-long... 

The emergence and implementation of advanced smart grid technologies will enable enhanced utilization of electric vehicles (EVs) as mobile energy storage devices which can provide system-wide services. With significant penetration of EVs in the near future, the concept, introduced in literature as vehicle to grid (V2G), will be practically possible. The V2G concept eases the integration of renewable energy into power system and gives new force to inevitable move toward power generation by clean energy resources. Therefore utilizing energy storage in EVs is undeniable due to economic and environment benefits. The V2G concept has been the field of many researches in different aspects so far.... 

This paper proposes an operation framework for incorporating time-varying electricity rates into day-ahead distribution system operation. The day-ahead distribution system operation problem is formulated as a mixed-integer linear programming (MILP) model, in which profit of the distribution system operator (DSO) from serving local loads is maximized. The impact of time-varying electricity rates on local loads is determined based on the estimated price elasticity of the customers and the historical consumption data. The customers' consumption behaviors in the absence of time-varying electricity rates are captured in terms of the customer baseline load (CBL). The proposed model is applied to a... 

Existing real-time pricing (RTP) schemes charge the whole customer's consumption at one highly volatile time varying price, which, in turn, imposes financial risk to participating customers. This paper presents a two-part RTP scheme aiming at efficient distribution system operation while mitigating customers' risk level imposed by volatile RTP prices. Our proposed RTP scheme offers two different RTP price signals. The first RTP price signal is used to charge customer's consumption up to its customer baseline load (CBL) which presents customer's consumption in the absence of RTP signals. The second RTP price signal is announced a day ahead of the actual operation, and can be updated in real... 

Automation is acknowledged by distribution utilities as a successful investment strategy to enhance reliability and operation efficiency. However, practical approaches that can handle the complex decision-making process faced by decision makers to justify the long-term financial effects of distribution automation have remained scarce. An automated and remote-controlled sectionalizing switch play a fundamental role in an automated distribution network. This paper introduces a new optimization approach for distribution automation in terms of automated and remotely controlled sectionalizing switch placement. Mixed-integer linear programming (MILP) is utilized to model the problem. The proposed... 

Automation is acknowledged by distribution utilities as a successful investment strategy to enhance reliability and operation efficiency. However, practical approaches that can handle the complex decision-making process faced by decision makers to justify the long-term financial effects of distribution automation have remained scarce. An automated and remote-controlled sectionalizing switch play a fundamental role in an automated distribution network. This paper introduces a new optimization approach for distribution automation in terms of automated and remotely controlled sectionalizing switch placement. Mixed-integer linear programming (MILP) is utilized to model the problem. The proposed... 

As a high proportion of the total generated electricity energy and the power system costs is due to the power losses in lines, allocating the loss and associated cost to the system loads and generating units is a substantial issue in deregulated power systems. The procedure to accomplish this cost allocation is designated as 'loss cost allocation' (LCA). So far, a number of LCA methods have been proposed for transmission networks. A few papers have compared different loss allocation methods, which are the methods which calculate the loss (and not necessarily the loss cost) allocated to the loads and generating units. However, this paper presents a comparative study of LCA methods. In this... 

Recent advancements in photovoltaic (PV) system technologies have decreased their investment cost and enabled the construction of large PV farms for bulk power generations. The output power of PV farms is affected by both failure of composed components and solar radiation variability. These two factors cause the output power of PV farms be random and different from that of conventional units. Therefore, suitable models and methods should be developed to assess different aspects of PV farms integration into power systems, particularly from the system reliability viewpoint. In this context a reliability model has been developed for PV farms with considering both the uncertainties associated...