A congestion management and transmission price simulator for competitive electricity markets

In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Demand response in electrical energy supply: an optimal real time pricing approach

In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit. The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.

Pricing no mercado financeiro

Dada a importância da variável preço no desenvolvimento dos negócios nas economias monetarizadas e a sua relevância no mercado financeiro apresentamos, recorrendo-nos das análises de alguns autores, alguns conceitos sobre a mesma e continuamos o trabalho relacionando-a com diversos aspectos da gestão, nomeadamente o planeamento, a relação entre a formação do preço e a estrutura de custos, a importância da análise da sensibilidade do mercado à política de pricing e o impacto desta variável na competitividade. O artigo desenvolve-se depois na perspectiva da relação entre o pricing e a gestão na óptica do marketing, apontando algumas estratégias de política de preço, e a relação desta com a segmentação e o ciclo de vida do produto. Dado que a literatura específica sobre pricing no mercado financeiro não é extensa concluímos com algumas considerações próprias sobre o tema.

Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Real-Time Simulation of Real-Time Pricing Demand Response to Meet Wind Variations

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

Gestão nos Serviços com Sistemas de Monitorização e Implementação do Smart Pricing

A presente dissertação foi elaborada no âmbito do Mestrado em Engenharia Electrotécnica (MEE) no Instituto Superior de Engenharia do Porto (ISEP), em regime empresarial, na empresa PH Energia Lda. Tem-se verificado que, ao longo dos últimos anos, os mercados estão cada vez mais competitivos, tornando-se quase imperativo que as empresas apostem numa boa otimização dos processos produtivos. Produzir cada vez mais, mais rapidamente e com menos recursos disponíveis, ou seja, de forma eficiente, são os desafios de todas as empresas que pretendem permanecer no mercado. Neste contexto surge o tema de tese, “Gestão nos Serviços com Sistemas de Monitorização e Implementação do Smart Pricing”, cujo objetivo tem como base principal a otimização das plataformas da PH Energia numa cultura de melhoria contínua e orientação para o cliente e promover aplicação da tarifa indexada e Smart Pricing em empresas de maneira a que exista uma maior poupança. Ao longo desta dissertação, foram desenvolvidos cálculos associados à monitorização e gestão nos serviços, bem como demonstrada a viabilidade dos mesmos na aplicação de tarifasindexadas e Smart Pricing no setor empresarial e, para finalizar, a compensação que é possível obter ao deslocar o diagrama de cargas, mantendo sempre o mesmo consumo. Na elaboração deste trabalho fez-se o cruzamento de duas plataformas informáticas designadas GesEnergy e Kisense, com ajuda da empresa VPS que tem como parceria a empresa Energia Simples. Em relação ao plano indexado, foram realizados dois estudos de dois balcões do Banco Popular de Portugal de forma a explicitar quando e como deve ser aplicada a tarifa indexada, gestão da procura, bem como deve ser deslocação do consumo, de forma a abranger as horas mais vantajosas em que o preço de energia elétrica é mais baixo.