Luis Olmos

Demand Response in an Isolated System With High Wind Integration

Growing load factors in winter and summer peaks are a serious problem faced by the Spanish electric energy system. This has led to the extensive use of peak load plants and thus to higher costs for the whole system. Wind energy represents a strongly increasing percentage of overall electricity production, but wind normally does not follow the typical demand profile. As generation flexibility is limited due to technical restrictions, and in absence of large energy storages, the other side of the equilibrium generation-demand has to react. Demand side management measures intend to adapt the demand profile to the situation in the system. In this paper, the operation of an electric system with high wind penetration is modeled by means of a unit commitment problem. Demand shifting and peak shaving are considered in this operation problem. Demand shifting is modeled in two different ways. Firstly, the system operator controls the shift of demand; secondly, each consumer decides its reaction to prices depending on its elasticity. The model is applied to the isolated power system of Gran Canaria. The impact of an increased installed wind capacity on operation and the cost savings resulting from the introduction of responsive demand are assessed. Furthermore, results from the different implemented demand response options are compared.

Evaluation of Three Methods Proposed for the Computation of Inter-TSO Payments in the Internal Electricity Market of the European Union

Parties to the Internal Electricity Market of the European Union (IEM) decided in 2001 to abolish the method of pancaking of transmission tariffs for cross-border transactions that was originally in place. Instead, they have agreed to implement a system whereby national transmission tariffs provide access to the entire IEM. This system is supplemented by a scheme of inter-TSO payments. However, conflict may arise if the compensation that a country must pay another one is not in accordance with the electrical usage that the former is making of the grid of the latter. For instance, Inter TSO Compensation methods (ITC methods) implicitly allocate the cost of any existing or new transmission line. Therefore, the adoption of an inefficient method may be an obstacle for building some needed regional grid investments. Consequently, one should give careful consideration to the selection of the ITC method. This paper analyzes, both qualitatively and quantitatively, the implementation of the most relevant ITC methods that have been considered so far in the European debate. When assessing each method from a conceptual point of view, considerable attention is devoted to the critical examination of its main underlying assumptions.

New design for the Spanish AGC scheme using an adaptive gain controller

This paper investigates the application of adaptive control to the Spanish load-frequency regulation scheme, Automatic Generation Control (AGC). The Spanish AGC system regulates the frequency and the power exchange between France and Spain. The system is hierarchically structured with one master regulator that coordinates four control areas. Each control area is composed of several generating units providing AGC service. Coordinating signals are sent to the control areas so that the global system response achieves the objective established by the System Operator. The participation of each control area in the service is set according to the rated share that it has obtained in the secondary-reserve market and its relative response speed compared to that of the rest of the control areas. Some problems, such as the lack of sensitivity to the quality of the reserve provided by the control areas, have been detected in the operation of the current AGC scheme. A new design, which is presented in this paper, has been developed in order to overcome these problems. This paper attempts to outline how this new design improves the global AGC system response and the distribution of the regulation effort among the control areas. The proposed strategy is compared with the present design by means of simulation.

Demand response and its sensitivity to participation rates and elasticities

Activating the demand-side of the electric system is a comeback of an old idea. What decades ago did not work out due to the lack of proper technology, today raises hopes to meliorate some of the most problematic situations in electric system operation such as ever higher peak demands and high wind generation during low demand periods. Smart grid infrastructures are currently implemented in many countries. This communication and control infrastructure allows consumers to receive information on system conditions, for example in the form of price signals, and thus to react to these and reduce, increase or shift their electricity consumption. This paper presents the modelling of demand shifting with two Demand Response mechanisms, Direct Load Control and Dynamic pricing. The outcome of both mechanisms depends, to a great extent, on two parameters: the maximum share of load which consumers are able and willing to shift and the elasticities used to express consumers level of responsiveness in the dynamic pricing mechanism. An analysis of the sensitivity of the impact of Demand Response is carried out by varying these two parameters over a large range. Results regarding demand participation shares, cost savings, demand variation patterns and used generation technologies are compared for the different sensitivity cases. We find that cost saving increases are not proportional to increments in the maximum share of participating demand and in responsiveness to prices.

Cost benefit analysis in the context of the energy infrastructure package

Each semester the THINK project publishes two research reports based on topics proposed by the European Commission.

Public Support for the Financing of RD&D Activities in New Clean Energy Technologies

Several market failures, as well as other technical, economic and regulatory barriers to the market penetration of clean energy technologies result in under-investment of private innovators in RD&D. Therefore, public support is needed in order to induce innovations. Policy tools creating market conditions that are attractive for the exploitation of clean technologies (market pull) must be combined with other tools directly supporting the development of these technologies through the provision of public funds (technology push). Thereby, financing policy instruments should be chosen so that their characteristics match with those of the specific innovation process being targeted at the same time that social welfare is maximized. We develop an analytical framework to define the form of public support and to provide recommendations on the optimal choice of both technology push and market pull instruments.

Assessing the impact of distributed generation on distribution network costs

The support of electricity generation from renewable energy sources (RES) and combined heat and power (CHP) has led to increasing penetration levels of distributed generation (DG). Nevertheless, Large-scale connection of DG faces numerous regulatory, economic, social and technological challenges. Distribution networks were not originally designed to accommodate generation. Hence, distribution system operators (DSOs) face great uncertainties about the impacts of DG on distribution network planning and operation. This paper presents a quantification of how DG affects distribution network costs in three real distribution areas. Several scenarios of demand and DG have been analysed for each case study. Two reference network models (RNMs) have been used to consider the most critical snapshots within each scenario: maximum demand-minimum generation and maximum generation-minimum demand. Results yielded significant differences among the three case studies.

Compatibility of Investment Signals in Distribution, Transmission and Generation

This book responds to the opening up of electricity markets to competition, which has completely changed the nature of power generation. The building of new generation and transmission capacity and the setting of the energy mix between nuclear, gas and renewable resources are mainly left to private initiative and investors.

An Operational State Aggregation Technique for Transmission Expansion Planning Based on Line Benefits

This paper provides a novel technique to represent in a reduced, or compact, way temporal variability in transmission expansion planning (TEP). This reduction is handled by means of “snapshot selection.” Instead of taking into account all the possible operational states and their associated optimal power flow, a reduced group of them is selected that is representative of all the states that should have an influence on investment decisions. Considering this reduced group of operational states should lead to the same investment decisions as if all the snapshots in the target year were considered. Original operational states are compared in the space of the benefits produced by potential reinforcements considered, which are relevant drivers for investment decisions. The benefits produced by these potential reinforcements are computed based on the incremental change in operation costs resulting from their installation. A clustering algorithm is used to group together those operational states where similar line benefits are realized. Our algorithm has been tested on a modified version of the standard IEEE 24 bus system. The method produces promising results and proves to be more efficient than other snapshot selection methods used until now in computing an accurate enough selection of snapshots representing system operation variability in TEP.

A formulation for large-scale transmission expansion planning problem and a solution strategy

The expected deployment of massive renewable energy sources (RES, mainly of wind and solar) at a continental or even intercontinental level creates very complex transmission expansion planning (TEP) problems. Both the size of the system and the level of uncertainty are huge. Solving a TEP problem for such big networks under high levels of uncertainty demands an exceptionally huge computational effort when using reasonably precise models. Conventional modeling approaches and solution strategies cannot be directly reproduced in this case due to their computational limitations. In this paper, we show a systematic way of approaching the problem, which deals both with modeling and with solution strategy aspects. We formulate the TEP problem as a two period stochastic linear programming problem characterized by common investment decisions to all scenarios in the first period and scenario-dependent decisions in the second period. In order to make it tractable, we devise a solution strategy based on decomposing the problem into successive optimization phases. Each phase uses the results of the previous one to reduce the search space. This reduction in complexity allows each phase to use more complex models with a similar computational load. Each optimization phase could be defined and solved as an independent problem, thus, allowing the use of specific decomposition techniques, or parallel computation when possible. A modified Garvers system is used to illustrate the methodologies. Test results from IEEE-300 bus system show that the proposed solution strategy is very effective. And, integrating the proposed solution strategy in the solution process contributes to a significant reduction in computational effort while fairly maintaining optimality of the solution.