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The paper proposes a hybrid methodology based on a Gaussian local search and a genetic algorithms to address the multi-objective and multistage optimal distribution expansion planning problem. The methodology is applied to solve the problem of optimal network investment under the new possibilities enabled by the smart grid, namely the new observability and controllability investments that will be...
Due to the inevitable prediction errors and/or sudden ramping down, the high penetration of wind power in electricity markets entails significant challenges. In this paper, a new demand response (DR) design targeting the power deficit (mainly caused by wind power) in the real-time market is proposed. When a power deficit is expected in the short-term operation, in comparison to exaggerated spot prices,...
A demand response program designed to mitigate peak load during hot summer days has been designed. Pacific Northwest National Laboratory (PNNL) developed taxonomy distribution feeder has been used to evaluate the effectiveness of the demand response program. The simulation includes direct load control, dynamic price control, residential PV penetration and their comparisons. The results will help guide...
The unstable output of renewable energy sources, such as wind turbines or photovoltaics, causes various issues in power system operation. With a large number of renewable energy sources, it is well known that the supply and demand balance control becomes a difficult issue. In addition, together with the progress of the electric power deregulation, the power flow problem will be more complex and important...
The use of distributed generation and demand response programs in smart grids implies management and integration of these resources when they are interconnected with the main power system. In the present paper, it is defined a methodology that can be used by the Virtual Power Player in order to aggregate and schedule the resources. The aggregated producers and consumers are optimally managed, making...
Demand aggregators are new market players that represent a group of consumers in the electricity market. This paper proposes an aggregator model responsible for gathering residential and commercial consumers, which has the role of managing their flexible consumption in the day-ahead electricity market. A methodology to optimize the aggregator's bids is also presented. It optimizes the scheduling of...
Demand response based on real time pricing introduces a new feedback loop between consumers' behavior and short term electricity markets. This feedback raises some concerns due to its potential destabilizing impact on electricity markets. Any analysis of this impact requires electricity market model. In this paper, several market models used for this purpose in the literature are analyzed and it is...
By influencing the demand side by means of price signals (Demand Response) additional flexibility potential in electric supply systems can be provided. However, by influencing the demand side typical consumption patterns of previously unaffected consumers are changed. This will lead to increasing uncertainty in load forecasting. This paper deals with the forecast of load time series in consideration...
This paper examines the value of load shifting (LS) and its impact on the scheduling and operation of large insular power systems which are typically characterized by high electricity generation cost and often by high Renewable Energy Resources (RES) share in the generation mix. An optimization model for the integration of load shifting in the unit commitment problem is presented and consecutive daily...
This paper proposes an optimal bidding strategy for a wind producer who participates as price-maker in the day-ahead electricity market. In order to empower the wind producer against the challenges introduced by the intermittent nature of wind power and improve his position into the market, demand response schemes are considered to be incorporated into his portfolio. The producer objective is the...
This paper reports on the quantification of the variable effects of the integration of demand response resources (DRRs) in a power system with integrated renewable energy sources (RESs) and utility-scale energy storage systems (ESSs) with the various sources of uncertainty explicitly represented. We deploy a stochastic simulation approach based on Monte Carlo techniques to emulate the transmission-constrained...
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...
Recent energy policies in several countries around the world, including in Europe, points the need to integrating growing amounts of distributed generation in electric power systems, namely at distribution networks level. Such resources are mainly of a distributed, non-dispatchable, and natural sources based nature (including wind power). With this, several changes in the operation and planning of...
This paper proposes a multi-agent model and strategy for aggregator-based residential demand response, and details how elements in the system interact to solve an issue requiring load to be temporarily decreased. The system uses assets such as plug-in hybrid electric vehicles, air conditioning units, and electric water heaters to achieve this goal. Simulation results, based on probabilistic models...
Demand response (DR) is potentially an effective tool in the smart grid that allows shifting electric load demand to less congested time slots. These peak-load shaving measures serve to alleviate grid congestion, minimize cost of electricity generation and help in reducing the electricity bills of retail customers. This work considers a demand response approach whereby the local electricity utility...
Dynamic pricing constitutes a promising approach for realizing the significant potential of flexible demand. However, naïve application of dynamic pricing leads to demand response concentration at the lowest-priced periods, yielding significant new demand peaks and inefficient system operation. A previously proposed measure imposing a flexibility restriction on flexible loads may not be acceptable...
In the context of liberalized energy market, increase in distributed generation, storage and demand response has expanded the price elasticity of demand, thus causing the addition of uncertainty to the supply-demand chain of power system. In order to cope with the challenges of demand uncertainty under the unbundled electricity market, the concept of Market-based Control Mechanism (MCM) in retail...
Increasing environmental concerns have motivated efforts for the modernization of the power system recently. As a result, the distribution system (DS) has been given specific importance. Especially, residential end-users have been rendered active trough the introduction of several assets such as electric vehicles, energy storage systems and self-production units. Although many opportunities emerge...
The increasing number of PV system connected to LV distribution networks may trigger network reinforcement to maintain voltages and power flows within the statutory limits. The paper aims to investigate how different levels of Demand Response (DR) participation can facilitate the integration of PV. In order to get robust conclusion, fractal-based generic distribution network model is used to generate...
DC renewable energy sources and dc loads are gaining attraction and they are preferably connected in dc microgrids. To increase the availability of dc microgrids, voltage dependent demand response should be used to switch off low priority loads in case of insufficient supply. This is possible even without communication with the loads. In this paper it is shown that using a voltage hysteresis with...
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