Virtual power producers integration into MASCEM

All over the world Distributed Generation is seen as a valuable help to get cleaner and more efficient electricity. Under this context distributed generators, owned by different decentralized players can provide a significant amount of the electricity generation. To get negotiation power and advantages of scale economy, these players can be aggregated giving place to a new concept: the Virtual Power Producer. Virtual Power Producers are multi-technology and multi-site heterogeneous entities. Virtual Power Producers should adopt organization and management methodologies so that they can make Distributed Generation a really profitable activity, able to participate in the market. In this paper we address the integration of Virtual Power Producers into an electricity market simulator –MASCEM – as a coalition of distributed producers.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

Renewable-based generation integration in electricity markets with virtual power producers

The development of renewable energy sources and Distributed Generation (DG) of electricity is of main importance in the way towards a sustainable development. However, the management, in large scale, of these technologies is complicated because of the intermittency of primary resources (wind, sunshine, etc.) and small scale of some plants. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. VPPs can ensure a secure, environmentally friendly generation and optimal management of heat, electricity and cold as well as optimal operation and maintenance of electrical equipment, including the sale of electricity in the energy market. For attaining these goals, there are important issues to deal with, such as reserve management strategies, strategies for bids formulation, the producers’ remuneration, and the producers’ characterization for coalition formation. This chapter presents the most important concepts related with renewable-based generation integration in electricity markets, using VPP paradigm. The presented case studies make use of two main computer applications:ViProd and MASCEM. ViProd simulates VPP operation, including the management of plants in operation. MASCEM is a multi-agent based electricity market simulator that supports the inclusion of VPPs in the players set.

Virtual power producers simulation - negotiating renewable distributed generation in competitive electricity markets

Sustainable development concerns made renewable energy sources to be increasingly used for electricity distributed generation. However, this is mainly due to incentives or mandatory targets determined by energy policies as in European Union. Assuring a sustainable future requires distributed generation to be able to participate in competitive electricity markets. To get more negotiation power in the market and to get advantages of scale economy, distributed generators can be aggregated giving place to a new concept: the Virtual Power Producer (VPP). VPPs are multi-technology and multisite heterogeneous entities that should adopt organization and management methodologies so that they can make distributed generation a really profitable activity, able to participate in the market. This paper presents ViProd, a simulation tool that allows simulating VPPs operation, in the context of MASCEM, a multi-agent based eletricity market simulator.

Dispachability improvement of wind generation by the virtual power producers

Nowadays, there is a growing environmental concern about were the energy that we use comes from, bringing the att ention on renewable energies. However, the use and trade of renewable e nergies in the market seem to be complicated because of the lack of guara ntees of generation, mainly in the wind farms. The lack of guarantees is usually addressed by using a reserve generation. The aggregation of DG p lants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of wind generation technologies, making them valuable in electricity markets. This paper presents some resul ts obtained with a simulation tool (ViProd) developed to support VPPs in the analysis of their operation and management methods and of their strat egies effects.

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.

Optimal offering strategies for wind power producers considering uncertainty and risk

This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

Distributed generation producers' reserve management

Sustainable development concerns are being addressed with increasing attention, in general, and in the scope of power industry, in particular. The use of distributed generation (DG), mainly based on renewable sources, has been seen as an interesting approach to this problem. However, the increasing of DG in power systems raises some complex technical and economic issues. This paper presents ViProd, a simulation tool that allows modeling and simulating DG operation and participation in electricity markets. This paper mainly focuses on the operation of Virtual Power Producers (VPP) which are producers’ aggregations, being these producers mainly of DG type. The paper presents several reserve management strategies implemented in the scope of ViProd and the results of a case study, based on real data.

MV producers and consumers agents characterization with DSM techniques

This paper consist in the establishment of a Virtual Producer/Consumer Agent (VPCA) in order to optimize the integrated management of distributed energy resources and to improve and control Demand Side Management DSM) and its aggregated loads. The paper presents the VPCA architecture and the proposed function-based organization to be used in order to coordinate the several generation technologies, the different load types and storage systems. This VPCA organization uses a frame work based on data mining techniques to characterize the costumers. The paper includes results of several experimental tests cases, using real data and taking into account electricity generation resources as well as consumption data.

MASCEM - an electricity market simulator providing coalition support for virtual power players

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.

The importance and accuracy of wind power forecasts

Due to the global crisis o f climate change many countries throughout the world are installing the renewable energy o f wind power into their electricity system. Wind energy causes complications when it is being integrated into the electricity system due its intermittent nature. Additionally winds intennittency can result in penalties being enforced due to the deregulation in the electricity market. Wind power forecasting can play a pivotal role to ease the integration o f wind energy. Wind power forecasts at 24 and 48 hours ahead of time are deemed the most crucial for determining an appropriate balance on the power system. In the electricity market wind power forecasts can also assist market participants in terms o f applying a suitable bidding strategy, unit commitment or have an impact on the value o f the spot price. For these reasons this study investigates the importance o f wind power forecasts for such players as the Transmission System Operators (TSOs) and Independent Power Producers (IPPs). Investigation in this study is also conducted into the impacts that wind power forecasts can have on the electricity market in relation to bidding strategies, spot price and unit commitment by examining various case studies. The results o f these case studies portray a clear and insightful indication o f the significance o f availing from the information available from wind power forecasts. The accuracy o f a particular wind power forecast is also explored. Data from a wind power forecast is examined in the circumstances o f both 24 and 48 hour forecasts. The accuracy o f the wind power forecasts are displayed through a variety o f statistical approaches. The results o f the investigation can assist market participants taking part in the electricity pool and also provides a platform that can be applied to any forecast when attempting to define its accuracy. This study contributes significantly to the knowledge in the area o f wind power forecasts by explaining the importance o f wind power forecasting within the energy sector. It innovativeness and uniqueness lies in determining the accuracy o f a particular wind power forecast that was previously unknown.

Coal-fired Power Plants with Flexible Amine-based CCS and Co-located Wind Power: Environmental, Economic and Reliability Outcomes

Carbon Capture and Storage (CCS) technologies provide a means to significantly reduce carbon emissions from the existing fleet of fossil-fired plants, and hence can facilitate a gradual transition from conventional to more sustainable sources of electric power. This is especially relevant for coal plants that have a CO2 emission rate that is roughly two times higher than that of natural gas plants. Of the different kinds of CCS technology available, post-combustion amine based CCS is the best developed and hence more suitable for retrofitting an existing coal plant. The high costs from operating CCS could be reduced by enabling flexible operation through amine storage or allowing partial capture of CO2 during high electricity prices. This flexibility is also found to improve the power plant’s ramp capability, enabling it to offset the intermittency of renewable power sources. This thesis proposes a solution to problems associated with two promising technologies for decarbonizing the electric power system: the high costs of the energy penalty of CCS, and the intermittency and non-dispatchability of wind power. It explores the economic and technical feasibility of a hybrid system consisting of a coal plant retrofitted with a post-combustion-amine based CCS system equipped with the option to perform partial capture or amine storage, and a co-located wind farm. A techno-economic assessment of the performance of the hybrid system is carried out both from the perspective of the stakeholders (utility owners, investors, etc.) as well as that of the power system operator.

In order to perform the assessment from the perspective of the facility owners (e.g., electric power utilities, independent power producers), an optimal design and operating strategy of the hybrid system is determined for both the amine storage and partial capture configurations. A linear optimization model is developed to determine the optimal component sizes for the hybrid system and capture rates while meeting constraints on annual average emission targets of CO2, and variability of the combined power output. Results indicate that there are economic benefits of flexible operation relative to conventional CCS, and demonstrate that the hybrid system could operate as an energy storage system: providing an effective pathway for wind power integration as well as a mechanism to mute the variability of intermittent wind power.

In order to assess the performance of the hybrid system from the perspective of the system operator, a modified Unit Commitment/ Economic Dispatch model is built to consider and represent the techno-economic aspects of operation of the hybrid system within a power grid. The hybrid system is found to be effective in helping the power system meet an average CO2 emissions limit equivalent to the CO2 emission rate of a state-of-the-art natural gas plant, and to reduce power system operation costs and number of instances and magnitude of energy and reserve scarcity.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.