Energy-only markets with deferrable demand (original) (raw)
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2018
Demand response (DR) as a source of flexibility is considered to become increasingly important in power systems based on renewable energy sources (RES), which are characterised by increasingly distributed, volatile and uncertain supply. We explore the impact of DR on generator investments and profits from different markets, on costs for different consumers from different markets, and on CO2 emissions under consideration of the uncertainties associated with the RES generation. We develop a novel stochastic mixed complementarity model in this paper that considers both operational and investment decisions, that considers interactions between an energy market, a capacity market and a feed-in premium and that takes into account the stochasticity of electricity generation by RES. We find that DR particularly increases renewable generator profits. While DR may reduce consumer costs from the energy market, these savings may be (over)compensated by increasing costs from the capacity market a...
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Timing of Markets- the Key Variable in Design of Ancillary Service Markets for Power Reserves
2010
Proper design of ancillary service markets for power reserves, which are used as the means to insure system security and to balance generation and consumption in real time (also known as balancing services), is a complex task regarding the variables in design of these markets and high interrelations of these markets with other electricity markets. This paper concentrates on timing of these markets as a decisive and widely overlooked variable in design of balancing services markets. The case of Germany is studied as the main case and the market in the Netherlands is used for comparison. The focus of the study is on the secondary control markets (both reserve capacity and balancing energy) and we study the influence of alternative settings regarding timing of these markets on performance of the market as a whole analyzing the bid prices, excess supply ratios, pivotal supplier tests, and imbalance volumes.
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Impact of Incentive Based Demand Response on Large Scale Renewable Integration
—The large scale deployment of renewable generation is generally seen as the most promising option for displacing fossil fuel generators, especially coal-fired power plants. A key challenge in integrating Renewable Energy Resources (RERs) is to find approaches that ensure long term sustainability and economic profit. One approach for mitigating the variability issue of integrating RERs is Demand Response (DR). The majority of current research is focuses on the role of DR for reliability support while economic concerns of RERs are barely addressed. In this paper, we investigate how DR can provide a potential solution to improve economic integration of RERs. More specifically , we propose Incentive Based DR (IBDR) programs, which is generally more attractive than real-time pricing programs for small customers. The proposed optimization framework in this paper finds an adequate amount of load change and incentive payments at each hour using a behavior model of customers. For this case study, the retirement of seven coal-fired power plants and expansion of RERs from less than 5% to 30%, is simulated for one year using data in the reduced WECC 240-bus system. Results show although renewable expansion could lead to benefit loss for utilities and sharp changes in market price, the proposed IBDR program could minimize these impacts.
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International Journal of Electrical Power & Energy Systems
Demand response (DR) has recently become an important resource in both system operation and market operation. The focus of this paper is to investigate and quantify the cost impact of various demand response modelings on unit commitment and dispatch in a day-ahead market regime. We have used mixed integer programming unit commitment model, in the market operation framework. Day-ahead market is modeled with a typical test system. Our research results show that DR can exert downward pressure on electricity prices, causing significant implications on social welfare. Results from this work will help policy makers, resource planners, and market designers to make more informed decisions with the goal of better accommodating more demand response resources in the future.
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