This work combines a detailed model of the electricity sector with a general equilibrium model for Spain, to analyze the effects of new investments and technological evolution in the electricity sector, as well as their impact in global aspects of the economy. A reference scenario with high prices for CO2 emissions together with insufficient investments in renewable energy was simulated, showing an expected negative economic impact. This scenario was then combined with five potential policies of economic reactivation. The most positive one was related to the reduction of the cost of access to capital, leading to improvements in capital income and GDP, thus mitigating the impact of the electricity price increase. This policy also leads to a migration of the labour from the production to the service sectors and suggests that a transition towards a cleaner electricity sector with minor economic impacts is possible, when energy policies are combined with adequate fiscal policies.
—Integration of renewable energy sources (RES) like wind into the power system is a high priority in many countries, but it becomes increasingly difficult as renewables reach a significant share of generation. Demand response (DR) can potentially mitigate some of these difficulties, but the best way to control and integrate DR into the power system remains an open question. Integration into existing electricity markets is one option, but dynamic pricing with DR has been observed to be unstable, resulting in oscillations in supply and demand. This so-called Cobweb effect is presented here using the market structure and measurements from the EcoGrid EU demonstration, where five minute electricity pricing is sent to 1900 houses. A new tool for quantifying volatility is presented, and the causes for volatility are investigated. A key outcome of this study shows that increases in social welfare due to DR appear to be limited by the cost of volatility in existing market structures.
The nationwide launch of electric vehicles (EV) requires new approaches of market integration. The controlled charging of EV offers a possibility to trade at the energy market in particular at the reserve power market. New actors enter the energy market to perform the business case of trading secondary reserve power which leads to a change in the market role model. But not all actors benefit from this business in the same way. Some are more suited than others. This paper describes the adapted role model which includes all new EV-related market actors. Furthermore a new approach to evaluate the feasibility for different actors to perform the regarded business case is presented. The cost-utility-analysis calculates individual values for each actor by quantifying soft parameters and describes his capability. Using a case study this paper compares the capability of three different market actors - a car manufacturer, an energy supplier and a grid operator.
With the growing environmental and energetic concern, the issue of adapting our energy systems is paramount. This paper deals with the issue of new optimal energy mixes in a high renewable energy share context, and capacity investment in such a framework. We use the “screening curve” method to determine competitors' investments and deduce the benefit of a conventional generator. This work is carried out using a robust approach i.e. we determine a threshold of benefit we want to reach with a defined probability no matter the actual demand and renewable penetration. To determine this solution, we consider four demand scenarii and levels of installed capacity both for wind and for photovoltaic energy. This work is undertaken for the French case. Some results are shown for a coal power plant with 2030 scenarii for demand, wind and solar capacity.
Pumped storage hydropower plants can contribute to a better integration of intermittent renewable energy and to balance generation and demand in real time by providing rapid-response generation. In order to invest in a new pumped storage plant, it is necessary to assess carefully the profitability of the project as the recovery of investment costs could be jeopardised by many factors. Apart from participating in the day-ahead market, ancillary services can also play an important role when determining the incomes. The aim of this paper is to make a preliminary comparison of pumped storage plant's market incomes with and without ability to regulate power in pumping mode through variable speed technology. A deterministic mixed-integer programming model is proposed to calculate power bids for the day-ahead and secondary regulation markets. The model considers the hourly day-ahead and secondary reserve market prices as well as usage and prices of secondary regulation-up and down energy requested by the Spanish System Operator.
One of the main barriers to the complete integration of the fully electric vehicle (FEV) in the energetic system is the expected impact on the electric infrastructure and particularly on the electric demand profile. In the scope Spanish electric system, the relationship between the fully electric vehicle total charging demand and the final price of electricity has been analyzed. To accomplish this objective, different scenarios have been defined attending to the level of use of FEV, the daily distribution of the vehicle charging processes and the season of the year. Feasible demand profiles have been created based on these scenarios, combining the described. From these demand profiles, the variation of the hourly price in the Spanish spot electricity market and the capability of the Spanish power system to manage the fully electric vehicle demand have been analyzed.
Using an agent-based modeling approach we show how personal attributes, like conformity or indifference, impact opinions of individual electricity consumers regarding innovative dynamic tariff programs. We also examine the influence of advertising, discomfort of usage and the expectations of financial savings on opinion dynamics. Our main finding is that currently the adoption, understood as a positive opinion or attitude toward the innovation, of dynamic electricity tariffs is virtually impossible due to the high level of indifference in today's societies. However, if in the future the indifference level is reduced, e.g., through educational programs that would make the customers more engaged in the topic, factors like tariff pricing schemes and intensity of advertising will became the focal point.
Policy makers are in broad agreement that demand response should play a major role in EU electricity systems and provide much needed future system flexibility. Yet, little demand response has been forthcoming in member states to date. This paper identifies some of the technical potential for demand response, based on empirical data from one UK demand aggregator. Half-hourly electricity readings of demand during normal operation and during response events have been analysed for different industry and service sectors. We review these findings in the context of ongoing EU policy developments with particular focus on the role appropriate arrangements to enhance the available resource. We conclude that in some sectors appropriate policy and regulation could triple the available response capacity and thereby lead to stronger commercial uptake of demand response.
The paper proposes different approaches to the determination of a nodal gas price component that corresponds to the cost of transportation constraints. To this end the research focuses on such methods for calculation of nodal prices as traditional, contribution factor, average prices and the Aumann-Shapley method given in the game theory for allocation of total costs. These methods were applied to calculate the cost of transportation constraints for a test and real gas supply systems. In the paper the discussed methods are compared to the Aumann-Shapley method.
Currently functioning European electricity markets are subjected to a comprehensive transformation, which includes the unification of different day-ahead power exchanges (PXs) into an all-European bidding and clearing process. The inner core of this platform is intended to be an algorithm called EUPHEMIA, which can be viewed as a hybrid of different existing PX designs. One of the most important contibutors of EUPHEMIA is the COSMOS algorithm which is currently operated for market clearing in several countries. If viewed as an extended version of COSMOS, properties of EUPHEMIA can be put into their proper context. Our paper attempts to examine the most important newly introduced components and the effects of their integration into the COSMOS' framework. Particular attention is paid to possible growth of computational complexity. The resulting model is investigated to find feasible solution techniques and to discuss the expected practical benefits of several optimization methods and softwares.
A coupled optimization of the electricity and gas systems is presented in this paper. The electricity problem involves a unit commitment with co-optimization of energy and reserves under a power pool, considering all system operational and unit technical constraints. The gas problem involves a large-scale highly non-convex and non-linear problem structure, which is modeled as a Mixed Integer Non-Linear Programming model. The decomposition of the overall problem is based on the Augmented Lagrangian method. An iterative process is implemented, coordinating the two interdependent systems using an alternating minimization method, in which the Lagrange multipliers are updated using a subgradient method. The solution algorithm is evaluated using the Greek power and gas system, employing thirteen gas-fired units and fifty-three gas network nodes. The test results indicate the strong interdependence of the two systems, and demonstrate the efficiency of the presented algorithm in coordinating them.
The paper presents fast method of unit commitment on balancing market, which also provides system security both in steady and all N-1 contingency states. Two types of generating units were modelled: thermal steam-turbine unit and pumped-storage unit. Unit parameters were specified accordingly to available data from Polish power plants and Transmission System operator (TSO). The day-ahead balancing market was chosen because the most frequent on this market the technical requirements of the system are checked. The mixed integer linear optimization was proposed as an optimization technique, as the most promising from the literature survey. The objective linear function includes energy bids, reserve bids and start-up costs for each time interval, each market participant and each commissioned unit. The 636-bus network based on the frame of the Polish power system network, was used in the calculations. The model included 52 generator nodes with 117 units which are dispatched in the optimization process.
Electricity transmission system operators (TSO) in Europe are increasing subject to high-powered performance-based regulation, such as revenue-cap regimes. The determination of the parameters in such regimes is challenging for national regulatory authorities (NRA), since there is normally a single TSO operating in each jurisdiction. The solution for European regulators has been found in international regulatory benchmarking, organized in collaboration with the Council of European Energy Regulators (CEER) in 2008 and 2012 for 22 and 23 TSOs, respectively. The frontier study provides static cost efficiency estimates for each TSO, as well as dynamic results in terms of technological improvement rate and efficiency catch-up speed. In this paper, we provide the methodology for the benchmarking, using non-parametric DEA under weight restrictions, as well as an analysis of the static cost efficiency resutls for 2011. The overall cost efficiency is measured with a three-output model, explaining 91.2 % of variance, using a DEA model under non-decreasing returns to scale assumptions. The methodology is innovative in the sense that it combines endogenous outlier detection, technologically relevant output weight restrictions and a correction method for opening balances.
In many countries, groups of producers and consumers are organized into virtual entities to participate in electricity markets. These entities are called balance groups (BGs), or are given similar names, because they are responsible for maintaining an energy balance for the group, and experience costs in case of imbalances. With large shares of uncertain renewable energy sources (RES), BGs are exposed to the risk of high balancing costs. In this paper, we propose a day-ahead (DA) scheduling and a real-time (RT) control scheme to minimize the spot market and balancing costs of a BG using flexible loads and storage resources. In the DA scheduling problem, we account for RES and price uncertainties by formulating a two-stage stochastic optimization problem with recourse. The RT control problem is formulated as a stochastic model predictive control (MPC) problem that uses short-term RES forecasts. We demonstrate the performance of the proposed scheme considering a BG with a wind farm, an industrial load, and a pumped-storage plant. The results show that the proposed scheme reduces the BG costs, but the cost savings vary and are case dependent.
In this paper, we present a model of the German spot and balancing markets. We focus on the secondary and tertiary balancing market, analyzing the effect of two factors on procurement costs. First, the length of the time period a single supplier has to provide balancing power for. Second, balancing auctions are held well before the bidding period starts, at a time when electricity demand, as well as renewable feed-in is uncertain. Our results suggest that changing the market design, considering early commitment and the length of time period, could decrease inefficiencies.
Increasing levels of wind power generation in the coming years will displace conventional generation, impacting the need for balancing reserves. The upcoming integration of pan-European balancing markets seeks to increase collaboration between areas for optimal provision of services. The challenge of increased variability due to wind and other renewables could be tackled by the exchange of balancing services among regional groups within the larger interconnected system. In this work, load-frequency control models of the United Kingdom and Continental Europe were developed in the MATLAB/Simulink environment and a worst-case event for the UK in the year 2020 is chosen for analysis. Fast control actions are then exchanged between the power systems of UK and Continental Europe. The performance of the coupled system in terms of frequency deviation is evaluated and compared to the decoupled situation. The results show that the frequency response improves, with lower maximum deviations. A cross-border balancing arrangement also leads to less deployment of reserves for UK.
This paper presents a unified unit commitment and economic dispatch tool for the short-term scheduling of a power system under high renewable penetration. The proposed model uses variable time resolution and scheduling horizon extended up to 36 hours ahead and produces robust real-time decisions making the short-term operation of the power system almost insensitive to RES forecast errors. The proposed model is tested for a monthly period on the Greek interconnected power system using real load and wind power data for two different wind penetration levels. Simulation results show that the proposed methodology allows for the accommodation of large amounts of wind energy into the short-term scheduling of the power system at minimum cost.
