Multidimensional scaling analysis of electricity market prices

This paper studies the impact of energy and stock markets upon electricity markets using Multidimensional Scaling (MDS). Historical values from major energy, stock and electricity markets are adopted. To analyze the data several graphs produced by MDS are presented and discussed. This method is useful to have a deeper insight into the behavior and the correlation of the markets. The results may also guide the construction models, helping electricity markets agents hedging against Market Clearing Price (MCP) volatility and, simultaneously, to achieve better financial results.

Price forecasting in the day-ahead Iberian electricity market using a conjectural variations Arima model

Price forecast is a matter of concern for all participants in electricity markets, from suppliers to consumers through policy makers, which are interested in the accurate forecast of day-ahead electricity prices either for better decisions making or for an improved evaluation of the effectiveness of market rules and structure. This paper describes a methodology to forecast market prices in an electricity market using an ARIMA model applied to the conjectural variations of the firms acting in an electricity market. This methodology is applied to the Iberian electricity market to forecast market prices in the 24 hours of a working day. The methodology was then compared with two other methodologies, one called naive and the other a direct forecast of market prices using also an ARIMA model. Results show that the conjectural variations price forecast performs better than the naive and that it performs slightly better than the direct price forecast.

Defining Electricity Tariffs Using the Knowledge About the Consumers Profiles in ELECON Project

The increasing importance of the integration of distributed generation and demand response in the power systems operation and planning, namely at lower voltage levels of distribution networks and in the competitive environment of electricity markets, leads us to the concept of smart grids. In both traditional and smart grid operation, non-technical losses are a great economic concern, which can be addressed. In this context, the ELECON project addresses the use of demand response contributions to the identification of non-technical losses. The present paper proposes a methodology to be used by Virtual Power Players (VPPs), which are entities able to aggregate distributed small-size resources, aiming to define the best electricity tariffs for several, clusters of consumers. A case study based on real consumption data demonstrates the application of the proposed methodology.

Elspot: Nord Pool Spot Integration in MASCEM Electricity Market Simulator

The energy sector in industrialized countries has been restructured in the last years, with the purpose of decreasing electricity prices through the increase in competition, and facilitating the integration of distributed energy resources. However, the restructuring process increased the complexity in market players' interactions and generated emerging problems and new issues to be addressed. In order to provide players with competitive advantage in the market, decision support tools that facilitate the study and understanding of these markets become extremely useful. In this context arises MASCEM (Multi-Agent Simulator of Competitive Electricity Markets), a multi-agent based simulator that models real electricity markets. To reinforce MASCEM with the capability of recreating the electricity markets reality in the fullest possible extent, it is crucial to make it able to simulate as many market models and player types as possible. This paper presents a new negotiation model implemented in MASCEM based on the negotiation model used in day-ahead market (Elspot) of Nord Pool. This is a key module to study competitive electricity markets, as it presents well defined and distinct characteristics from the already implemented markets, and it is a reference electricity market in Europe (the one with the larger amount of traded power).

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Towards a unified European electricity market: The contribution of data-mining to support realistic simulation studies

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.

Analysis of Electricity Market Prices Using Multidimensional Scaling

This paper studies the impact of the energy upon electricity markets using Multidimensional Scaling (MDS). Data from major energy and electricity markets is considered. Several maps produced by MDS are presented and discussed revealing that this method is useful for understanding the correlation between them. Furthermore, the results help electricity markets agents hedging against Market Clearing Price (MCP) volatility.

A green future for European electricity? :Energy sources, policies and further determinants of the household price of electricity

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

The dynamics of the Swiss electricity market : three essays

Executive Summary Electricity is crucial for modern societies, thus it is important to understand the behaviour of electricity markets in order to be prepared to face the consequences of policy changes. The Swiss electricity market is now in a transition stage from a public monopoly to a liberalised market and it is undergoing an "emergent" liberalisation - i.e. liberalisation taking place without proper regulation. The withdrawal of nuclear capacity is also being debated. These two possible changes directly affect the mechanisms for capacity expansion. Thus, in this thesis we concentrate on understanding the dynamics of capacity expansion in the Swiss electricity market. A conceptual model to help understand the dynamics of capacity expansion in the Swiss electricity market is developed an explained in the first essay. We identify a potential risk of imports dependence. In the second essay a System Dynamics model, based on the conceptual model, is developed to evaluate the consequences of three scenarios: a nuclear phase-out, the implementation of a policy for avoiding imports dependence, and the combination of both. We conclude that the Swiss market is not well prepared to face unexpected changes of supply and demand, and we identify a risk of imports dependence, mainly in the case of a nuclear phase-out. The third essay focus on the opportunity cost of hydro-storage power generation, one of the main generation sources in Switzerland. We use and extended version of our model to test different policies for assigning an opportunity cost to hydro-storage power generation. We conclude that the preferred policies are different for different market participants and depend on market structure.

Are agent-based simulations robust? The wholesale electricity trading case

Agent-based computational economics is becoming widely used in practice. This paperexplores the consistency of some of its standard techniques. We focus in particular on prevailingwholesale electricity trading simulation methods. We include different supply and demandrepresentations and propose the Experience-Weighted Attractions method to include severalbehavioural algorithms. We compare the results across assumptions and to economic theorypredictions. The match is good under best-response and reinforcement learning but not underfictitious play. The simulations perform well under flat and upward-slopping supply bidding,and also for plausible demand elasticity assumptions. Learning is influenced by the number ofbids per plant and the initial conditions. The overall conclusion is that agent-based simulationassumptions are far from innocuous. We link their performance to underlying features, andidentify those that are better suited to model wholesale electricity markets.

Improving electricity market price scenarios by means of forecasting factor models

In liberalized electricity markets, generation Companies must build an hourly bidthat is sent to the market operator. The price at which the energy will be paid is unknown during the bidding process and has to be forecast. In this work we apply forecasting factor models to this framework and study its suitability.

Maintenance and construction outsourcing in a public-owned electricity network company

Euroopan sähkösektori on ollut viimeisen vuosikymmenen suurten mullistusten kourissa. Sähkömarkkinoiden avautumisen jälkeen monopoliliiketoimintaa harjoittavien sähköyhtiöiden on ollut pakko parantaa tuottavuuttaan. Ratkaisuksi tähän on etsitty apua huolto- ja rakennustoimintojen ulkoistamisella. Ulkoistaminen on kuitenkin uusi menetelmä tällä sektorilla. Tämän tutkielman tavoitteena on selvittää syyt, jotka tanskalaisella sähköverkkoyhtiöllä oli huolto- ja rakennustoimintojen ulkoistamiseen, sekä löytää siitä saatavat hyödyt ja siihen sisältyvät riskit. Tutkimus suoritetaan käyttäen apuna kirjallisuutta, saatavilla olevia due diligence-, sekä muita raportteja ja analyysejä, sekä tapausta koskettavien tahojen haastatteluja.Lisäksi sähköverkkoalan asiantuntijoiden kanssa käytyjä konsultointia käytetäänselvitykseen. Tutkimus osoittaa, että perimmäiset ajurit huolto- ja rakennustoimintojen ulkoistamiseen tulivat lainmuutosten ja vapautuneiden sähkömarkkinoiden asettamista paineista. Kunnallisessa organisaatiossa parantaa tehokkuutta ulkoistamalla jotain toimintoja yksityisomisteiselle palvelun tuottajalle. Muut ulkoistamisesta odotetut hyödyt olivat alentuneet kustannukset, virtaviivaisempi organisaation ja sähköverkkoyhtiön tehottomista osista eroon pääseminen ennen sen myymistä.

Regulation of Electricity Transmission and Distribution in Russia

The regulation of electricity transmission and distribution business is an essential issue for any electricity market; it is widely introduced in developed electricity markets of Great Britain, Scandinavian countries and United States of America and other. Those markets which were liberalized recently also need well planned regulation model to be chosen and implemented. In open electricity markets the sectors of electricity distribution and transmission remain monopolies, so called "natural monopolies", as introducing the competition into these sectors in most cases appears to be inefficient. Thatis why regulation becomes very important as its main tasks are: to set reasonable tariffs for customers, to ensure non-discriminating process of electricity transmission and distribution, at the same time to provide distribution companies with incentives to operate efficiently and the owners of the companies with reasonable profits as well; the problem of power quality should be solved at the same time. It should be mentioned also, that there is no incentive scheme which will be suitable for any conditions, that is why it is essential to study differentregulation models in order to form the best one for concrete situation. The aim of this Master's Thesis is to give an overview over theregulation of electricity transmission and distribution in Russia. First, the general information about theory of regulation of natural monopolies will be described; the situation in Russian network business and the importance of regulation process for it will be discussed next. Then there is a detailed description ofexisting regulatory system and the process of tariff calculation with an example. And finally, in the work there is a brief analysis of problems of present scheme of regulation, an attempt to predict the following development of regulationin Russia and the perspectives and risks connected to regulation which could face the companies that try to enter Russian electricity market (such as FORTUM OY).

Sähkön markkinahintaa selittävät tekijät. Case: Nord Pool 2000-2005

Sähkön markkinahinta on saanut osakseen suurta huomiota viimeaikoina. Sähkömarkkinoiden vapautuminen ja päästökaupan avaaminen Euroopassa onentisestään nostanut sähkömarkkinoita näkyville lehdissä. Tämä tutkielma tutkii erilaisten tekijöiden vaikutusta sähkön markkinahintaan regressioanalyysin avulla. Edellä mainitun päästösopimusten markkinahinnan lisäksi tutkittiin kivihiilen sekä maakaasun markkinahintojen, lämpötilojen, jokien virtaamien, vesivarantojen täyttöasteiden sekä Saksan sähkömarkkinoiden hinnan vaikutusta sähkön markkinahintaan Nord Pool -sähköpörssissä. Työssä luotiin myös sähkön markkinahintaa ennustava malli. Kaikkien selittävien tekijöiden korrelaatiot olivat oletusten mukaiset ja regressioanalyysi onnistui selittämään yli 80 % sähkön markkinahinnan vaih-teluista. Merkittävimpiä selittäviä tekijöitä olivat vesivarannot sekä jokien virtaamat. Ennustavan mallin keskimääräinen suhteellinen virhe oli noin 10 %, joten ennustetarkkuus oli melko hyvä.