A trader portfolio optimization of bilateral contracts in electricity retail markets

Electricity markets are systems for effecting the purchase and sale of electricity using supply and demand to set energy prices. Two major market models are often distinguished: pools and bilateral contracts. Pool prices tend to change quickly and variations are usually highly unpredictable. In this way, market participants often enter into bilateral contracts to hedge against pool price volatility. This article addresses the challenge of optimizing the portfolio of clients managed by trader agents. Typically, traders buy energy in day-ahead markets and sell it to a set of target clients, by negotiating bilateral contracts involving three-rate tariffs. Traders sell energy by considering the prices of a reference week and five different types of clients. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

Change of Electricity Distribution Industry: Drivers and Opening Business Opportunities

As a result of the recent regulatory amendments and other development trends in the electricity distribution business, the sector is currently witnessing radical restructuring that will eventually impact the business logics of the sector. This report represents upcoming changes in the electricity distribution industry and concentrates on the factors that are expected to be the most fundamental ones. Electricity network companies nowadays struggle with legislative and regulatory requirements that focus on both the operational efficiency and the reliability of electricity distribution networks. The forces that have an impact on the distribution network companies can be put into three main categories that define the transformation at a general level. Those are: (1) a requirement for a more functional marketplace for energy, (2) environmental aspects (combating climate change etc.), and (3) a strongly emphasized requirement for the security of energy supply. The first point arises from the legislators’ attempt to increase competition in electricity retail markets, the second one concerns both environmental protection and human safety issues, and the third one indicates societies’ reduced willingness to accept interruptions in electricity supply. In the future, regulation of electricity distribution business may lower the threshold for building more weather-resistant networks, which in turn means increased underground cabling. This development pattern is reinforced by tightening safety and environmental regulations that ultimately make the overhead lines expensive to build and maintain. The changes will require new approaches particularly in network planning, construction, and maintenance. The concept for planning, constructing, and maintaining cable networks is necessary because the interdependencies between network operations are strong, in other words, the nature of the operation requires a linkage to other operations.

Sähkökaupan asiakassegmenttien riskikorjattu kannattavuus

Työn tavoitteena oli luoda laskentamalli sähkökaupan asiakassegmenttien riskikorjatun kannattavuuden selvittämiseksi. Lisäksi tavoitteena oli löytää tekijät, jotka aiheuttavat hyvän ja huonon kannattavuuden esiintymisen. Työssä selvitettiin sähkökaupan kustannusten ja riskien taustatekijät. Lisäksi työssä laadittiin menetelmät kustannusten laskemiselle ja kohdistamiselle sekä riskien määrittämiselle. Asiakkaat segmentoitiin kustannuksiin sekä riskeihin vaikuttavien tekijöiden mukaan. Kannattavuuslaskennan perustana käytettiin katetuottoajattelua ja asiakkaan sähkönhankintakustannus määritettiin markkinaehtoisesti siten, että sähkönkäytölle laskettiin tarkasteluhetken markkina-arvo. Kustannusten jakamisessa noudatettiin aiheuttamisperiaatetta ja riskit laskettiin historialliseen simulaatioon perustuen. Laskentamallilla saatujen tulosten perusteella puolet segmenteistä ja 83 % asiakkaista oli kannattavia. Kannattavuuteen vaikuttivat eniten sopimuksen pysyvyys ja hinnoittelutapa sekä erityisesti annetut alennukset ja tuote eli tariffi. Lisäksi havaittiin, että nykyinen asiakastietojärjestelmä ei tue riittävästi asiakaskannattavuuksien selvittämistä uusiutuneilla sähkömarkkinoilla.

Sähkönmyyntiyhtiöiden riskienhallinnan haasteet ja kehittäminen

Diplomityön tavoitteena on esitellä sähkökaupan ja erityisesti sähköyhtiöiden kokemia sähkönmyynnin riskejä sekä kuvata sähkönmyyntiin liittyvää riskienhallinnan problematiikkaa. Tarkastelun näkökulmana on tietojärjestelmien ja saatavissa olevan tiedon hyödyntäminen energiayhtiöiden riskienhallinnassa. Toinen päätavoitteista on tutkia, kuinka saatavilla olevaa tiedon hyödyntämistä voidaan kehittää sähkönmyynnin hinnoittelussa sekä suojausten suunnittelussa. Työ toteutettiin työskentelemällä asiantuntijana energia-alaan keskittyneessä ohjelmistoyrityksessä sekä haastattelemalla yhdeksän suomalaisen sähkönmyyntiyhtiön henkilöitä riskienhallinnan haasteiden sekä tietojärjestelmien näkökulmasta. Saatavilla olevien tietojen nykyistä parempi hyödyntäminen ja automatisointi voivat auttaa pienentämään yhtiöiden riskitasoa ja parantaa menestymisen edellytyksiä sähkönmyynnin vähittäismarkkinoilla. Lisäksi kulloiseenkin markkinatilanteeseen sopivat sähkön hankintahinnan suojausstrategiat sekä monipuoliset dynaamiset hinnoittelumallit auttavat pienentämään yhtiön kokemia riskejä tai niiden vaikutuksia. Näiden hyödyntäminen vaatii laajaa ymmärrystä sähkö- ja johdannaismarkkinoiden toiminnasta sekä usein myös nykyisten tietojärjestelmien kehittämistä. Tulevaisuudessa yhä yleistyvä hajautettu tuotanto sekä kysynnän jousto asettavat tietojärjestelmille uusia vaatimuksia, jotka toteutuessaan mahdollistavat uudenlaisten palveluiden käyttöönoton sekä voivat tuoda tilaa myös alan uusille toimijoille. Työssä käsitellään energiayhtiöiden kokemia riskejä sähkönmyynnin näkökulmasta, esitellään alan yleisimmät riskit sekä keinot ja työkalut niiltä suojautumiseen. Työn lopuksi tarkastellaan sähkönmyynnin ja –hankinnan oleellisimpia prosesseja riskienhallinnan kehittämisen näkökulmasta.

Households’ willingness to engage in demand response in the Finnish retail electricity market: an empirical study

If electricity users adjusted their consumption patterns according to time-variable electricity prices or other signals about the state of the power system, generation and network assets could be used more efficiently, and matching intermittent renewable power generation with electricity demand would be facilitated. This kind of adjustment of electricity consumption, or demand response, may be based on consumers’ decisions to shift or reduce electricity use in response to time-variable electricity prices or on the remote control of consumers’ electric appliances. However, while demand response is suggested as a solution to many issues in power systems, actual experiences from demand response programs with residential customers are mainly limited to short pilots with a small number of voluntary participants, and information about what kinds of changes consumers are willing and able to make and what motivates these changes is scarce. This doctoral dissertation contributes to the knowledge about what kinds of factors impact on residential consumers’ willingness and ability to take part in demand response. Saving opportunities calculated with actual price data from the Finnish retail electricity market are compared with the occurred supplier switching to generate a first estimate about how large savings could trigger action also in the case of demand response. Residential consumers’ motives to participate in demand response are also studied by a web-based survey with 2103 responses. Further, experiences of households with electricity consumption monitoring systems are discussed to increase knowledge about consumers’ interest in getting more information on their electricity use and adjusting their behavior based on it. Impacts of information on willingness to participate in demand response programs are also approached by a survey for experts of their willingness to engage in demand response activities. Residential customers seem ready to allow remote control of electric appliances that does not require changes in their everyday routines. Based on residents’ own activity, the electricity consuming activities that are considered shiftable are very limited. In both cases, the savings in electricity costs required to allow remote control or to engage in demand response activities are relatively high. Nonmonetary incentives appeal to fewer households.

Pricing and competition in the Swedish retail market for electricity

Sweden, together with Norway, Finland and Denmark, have created a multi-national electricity market called NordPool. In this market, producers and retailers of electricity can buy and sell electricity, and the retailers then offers this electricity to end consumers such as households and industries. Previous studies have shown that pricing at the NordPool market is functioning quite well, but no other study has to my knowledge studied if pricing in the retail market to consumers in Sweden is well functioning. If the market is well functioning, with competition and low transaction costs when changing electricity retailer, we would expect that a homogeneous good such as electricity would be sold at the approximately same price, and that price changes would be highly correlated, in this market. Thus, the aim of this study is to test whether the price of Vattenfall, the largest energy firm in the Swedish market, is highly correlated to the price of other firms in the Swedish retail market for electricity. Descriptive statistics indicate that the price offered by Vattenfall is quite similar to the price of other firms in the market. In addition, regression analysis show that the correlation between the price of Vattenfall and other firms is as high as 0.98.

Az európai villamosenergia-árak központi szabályozásának hatása a fogyasztói árakra (The impacts of the price regulation on the level of retail electricity prices in Europe)

Az Európai Unión belül az elmúlt időszakban megerősödött a vita arról, vajon a Közösség versenyképességének javításához milyen módon és mértékben járulhat hozzá az ipari és lakossági fogyasztók számára kedvező áron elérhető villamos energia. Az uniós testületek elsődlegesen a verseny feltételeinek további javításában látják a versenyképesség javításának fő eszközét, ám egyesek az aktívabb központi szabályozás mellett érvelnek. A jelenleg alkalmazott európai szabályozási gyakorlat áttekintése, a szabályozási modellek és a piaci árak alakulásának vizsgálata hozzásegíthet, hogy következtetéseket vonjunk le a tagállami gyakorlatok tekintetében, vajon sikeresebb-e a központi ármegállapításon alapuló szabályozói mechanizmus, mint a liberalizált piacmodell. ______ There is a strengthening debate within the European Union in recent years about the impact of the affordable industrial and household electricity prices on the general competitiveness of European economies. While the European Institutions argues for the further liberalization of the energy retail sector, there are others who believe in centralization and price control to achieve lower energy prices. Current paper reviews the regulatory models of the European countries and examines the connection between the regulatory regime and consumer price trends. The analysis can help to answer, whether the bureaucratic central regulation or the liberalized market model seems more successful in supporting the competitiveness goals. Although the current regulatory practice is heterogeneous within the EU member states, there is a clear trend to decrease the role of regulated tariffs in the end-user prices. Our study did not find a general causal relationship between the regulatory regime and the level of consumer electricity prices in a country concerned. However, the quantitative analysis of the industrial and household energy prices by various segments detected significant differences between the regulated and free-market countries. The first group of member states tends to decrease the prices in the low-consuming household segments through cross-financing technics, including increased network tariffs and/or taxes for the high-consuming segments and for industrial consumers. One of the major challenges of the regulatory authorities is to find the proper way of sharing these burdens proportionally with minimizing the market-distorting effects of the cross-subsidization between the different stakeholder groups.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

An integrated system to support electricity tariff contract definition

This paper presents an integrated system that helps both retail companies and electricity consumers on the definition of the best retail contracts and tariffs. This integrated system is composed by a Decision Support System (DSS) based on a Consumer Characterization Framework (CCF). The CCF is based on data mining techniques, applied to obtain useful knowledge about electricity consumers from large amounts of consumption data. This knowledge is acquired following an innovative and systematic approach able to identify different consumers’ classes, represented by a load profile, and its characterization using decision trees. The framework generates inputs to use in the knowledge base and in the database of the DSS. The rule sets derived from the decision trees are integrated in the knowledge base of the DSS. The load profiles together with the information about contracts and electricity prices form the database of the DSS. This DSS is able to perform the classification of different consumers, present its load profile and test different electricity tariffs and contracts. The final outputs of the DSS are a comparative economic analysis between different contracts and advice about the most economic contract to each consumer class. The presentation of the DSS is completed with an application example using a real data base of consumers from the Portuguese distribution company.

Commercial agents portfolio optimization in electricity markets

As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.

Power Producers Trading Electricity in Both Pool and Forward Markets

The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.

Power producers trading electricity in both pool and forward markets

The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.

Commercial agentes portfolio optimization in electricity markets

As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.