Many problems have arose along with the practical implementation of restructured electrical business in USA and European Union such as lack of generation, network constraints, etc. A good example for these problems is the scarce participation of the demand in the electricity markets-energy, reserve and other ancillary services-problem that can be solved through new Demand Responsive Programs, aimed to replace the traditional Demand Side Management programs into voluntary demand participation programs. A methodology for the generation of demand side bids and offers in large customer facilities and a real application to a university customer is presented in this paper. This methodology is based on knowledge of the physical processes involved in the electricity consumption and the flexibility in the required supply. The result of the methodology proposed is a set of Demand Packages, that can be used to participate in different electricity markets, whose possibilities-in the market arena-will be explored in a consequent paper.

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Inhabited islands depend primarily on fossil fuels for electricity generation and they also present frequently a vehicle fleet, which result in a significant environmental problem. To address this, several governments are investing in the integration of Renewable Energy Sources (RESs) and Electric Vehicles (EVs), but the combined integration of them creates challenges to the operation of these isolated grid systems. Thus, the aim of this paper is to propose an Electric Vehicle charging strategy considering high penetration of RES. The methodology proposes taxing CO2 emissions based on high pricing when the electricity is mostly generated by fossil fuels, and low pricing when there is a RES power excess. The Smart charging methodology for EV optimizes the total costs. Nine scenarios with different installed capacity of solar and wind power generation are evaluated and compared to cases of uncoordinated charging. The methodology was simulated in the Galapagos Islands, which is an archipelago of Ecuador, and recognized by the United Nations Educational, Scientific and Cultural Organization (UNESCO) as both aWorld Heritage site and a biosphere reserve. Simulations results demonstrate that the EV aggregator could reduce costs: 7.9% for a case of 5 MW installed capacity (wind and PV each), and 7% for a case of 10 MW installed (wind and PV each). Moreover, the use of excess of RES power for EV charging will considerably reduce CO2 emissions

The problem of load modeling for Demand Side Management ( E M ) purposes is addressed in this paper. The proposed load models rely on information about both the physical characteristics of elemental load devices at the distribution level, and usage statistics of these devices.Although the class of models discussed here has been previously proposed in the literature, its suitability for DSM purposes is definitely established by showing how the models can be a tool for real E M actions evaluation. Some results are shown. -INTBODUCTIONThe use of Demand-Side Managementalternatives is gaining adepts between utilities and distribution companies in order to achieve a better operation of the Electric Power System.Two different approaches may be used to cope with the growth of the demand in an Electric Power System. The first one is to expand the Power System so that the new energy requirements can be met (Supply-Side policy). The second one is to try to influence the electric energy consumption so as to reduce the investment requirements (Demand-Side policies). Demand Side Managementhas been defined as those activities oriented to influence customer uses of electricity in ways that will produce the desired changes in the load shape [ l l . We will refer t o the Control actions directly performed upon the customer loads as Load Management (LM) actions.The reason for considering the possibility of influencing the customer uses must be found in the continuous rise in the cost of electricity and equipment, the availability of the required technology, more severe environmental constraints on power system generat ion, transmission and expansion, and the necessity to offer new options to the customer. Voltage reduction is a typical LM action that has been traditionally used by the utility for power peak consumption reduction.Some other actions need to be considered as potential LM control actions, mainly those related to the possibility of end-user load shedding: load interruption and load cycling.Obviously, the possibility of performing these kinds of actions upon the consumers must be attached to a flexible rates policy.One of the most critical problems when considering the application of DSM by the utility is to be able to assess whether this policy is going to produce the desired effects or not. Thus, in order to evaluate the DSM policies, it is necessary to have load models that can fulfill at least two objectives: First they should provide the necessary information to evaluate the benefits obtained through the use of the DSM and, secondly, they must allow the evaluation of every control action from the end-customer side, for example, through the evaluation of some "comfort index".These comfort indices, in conjunction with a proper rates structure, can become very important in securing U high level of acceptance of DSM policies among the customers.The load models we are about to discuss in this paper have appeared earlier elsewhere in the literature [61, [71, [81, [91 and [121. However, due to their relative math...

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Demand response is a basic tool used to develop modern power systems and electricity markets. Residential and commercial segments account for 40%-50% of the overall electricity demand. These segments need to overcome major obstacles before they can be included in a demand response portfolio. The objective of this paper is to tackle some of the technical barriers and explain how the potential of enabling technology (smart meters) can be harnessed, to evaluate the potential of customers for demand response (end-uses and their behaviors) and, moreover, to validate customers' effective response to market prices or system events by means of non-intrusive methods. A tool based on the Hilbert transform is improved herein to identify and characterize the most suitable loads for the aforesaid purpose, whereby important characteristics such as cycling frequency, power level and pulse width are identified. The proposed methodology allows the filtering of aggregated load according to the amplitudes of elemental loads, independently of the frequency of their behaviors that could be altered by internal or external inputs such as weather or demand response. In this way, the assessment and verification of customer response can be improved by solving the problem of load aggregation with the help of integral transforms.