Stochastic control for risk under deregulated electricity market — a case study using a new formulation

2005 ◽  
Vol 32 (4) ◽  
pp. 719-725 ◽  
Author(s):  
Joyce Li Zhang ◽  
K Ponnambalam
Keyword(s):  
Electricity Market ◽  
Explicit Method ◽  
State Variables ◽  
Risk Minimization ◽  
Solution Approach ◽  
Second Moments ◽  
Deregulated Electricity Market ◽  
New Formulation ◽  
Dual Dynamic Programming

This paper describes the implementation of a new solution approach — Fletcher-Ponnambalam model (FP) — for risk management in hydropower system under deregulated electricity market. The FP model is an explicit method developed for the first and second moments of the storage state distributions in terms of moments of the inflow distributions. This method provides statistical information on the nature of random behaviour of the system state variables without any discretization and hence suitable for multi-reservoir problems. Also avoiding a scenario-based optimization makes it computationally inexpensive, as there is little growth to the size of the original problem. In this paper, the price uncertainty was introduced into the FP model in addition to the inflow uncertainty. Lake Nipigon reservoir system is chosen as the case study and FP results are compared with the stochastic dual dynamic programming (SDDP). Our studies indicate that the method could achieve optimum operations, considering risk minimization as one of the objectives in optimization.Key words: reservoir operations, explicit method, uncertainty, stochastic programming, risk.

scholarly journals Optimal scheduling of regional integrated energy system considering multiple uncertainties

2021 ◽  
Vol 256 ◽  
pp. 02027
Author(s):  
Shufeng Guan ◽  
Lingling Wang ◽  
Chuanwen Jiang
Keyword(s):  
Electricity Market ◽  
Deterministic Model ◽  
Energy System ◽  
Economic Benefits ◽  
Optimal Scheduling ◽  
Mcmc Sampling ◽  
Deregulated Electricity Market ◽  
Integrated Energy System ◽  
Energy Service

Integrated energy system (IES) is an effective way to realize the efficient utilization of energy. Under the deregulated electricity market, IES operator gains profits by providing customers with energy service, including electricity, heat or cooling energy. With the deepening of market reform, higher penetration rate of renewable energy, economic risks embed in the IES. Based on this, an optimal scheduling model of regional IES considering uncertainties is proposed, aiming at maximizing the profits. Scenario analysis method has been adopted to model the uncertainties: Markov-Chain-Monte-Carlo (MCMC) sampling method, which has a better performance in fitting the probability distribution, is utilized to generate scenarios; K-means clustering method is applied to narrow down the sampling sets. By replacing the parameters in the deterministic model with the sampling sets, a series of optimal results can be achieved. The case study shows that the cooling storage tank can improve the economic benefits about 4.97% by converting electricity to cooling energy at lower price period and releasing energy at peak hours. Besides, through the proposed optimization model, operators can have a straight understanding of the venture brought by the uncertainties and a more reliable scheduling result is formed for reference.

scholarly journals Prosumer Community Portfolio Optimization via Aggregator: The Case of the Iberian Electricity Market and Portuguese Retail Market

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3747
Author(s):  
Ricardo Faia ◽  
Tiago Pinto ◽  
Zita Vale ◽  
Juan Manuel Corchado
Keyword(s):  
Portfolio Optimization ◽  
Electricity Markets ◽  
Electricity Market ◽  
Retail Market ◽  
Wholesale Market ◽  
Generation Capacity ◽  
Wholesale Electricity Market ◽  
Portfolio Optimization Model ◽  
Photovoltaic Generators

The participation of household prosumers in wholesale electricity markets is very limited, considering the minimum participation limit imposed by most market participation rules. The generation capacity of households has been increasing since the installation of distributed generation from renewable sources in their facilities brings advantages for themselves and the system. Due to the growth of self-consumption, network operators have been putting aside the purchase of electricity from households, and there has been a reduction in the price of these transactions. This paper proposes an innovative model that uses the aggregation of households to reach the minimum limits of electricity volume needed to participate in the wholesale market. In this way, the Aggregator represents the community of households in market sales and purchases. An electricity transactions portfolio optimization model is proposed to enable the Aggregator reaching the decisions on which markets to participate to maximize the market negotiation outcomes, considering the day-ahead market, intra-day market, and retail market. A case study is presented, considering the Iberian wholesale electricity market and the Portuguese retail market. A community of 50 prosumers equipped with photovoltaic generators and individual storage systems is used to carry out the experiments. A cost reduction of 6–11% is achieved when the community of households buys and sells electricity in the wholesale market through the Aggregator.

Deregulated electricity market, a stochastic variational approach

2021 ◽  
Vol 103 ◽  
pp. 105493
Author(s):  
Michele Limosani ◽  
Monica Milasi ◽  
Domenico Scopelliti
Keyword(s):  
Electricity Market ◽  
Variational Approach ◽  
Deregulated Electricity Market

Undersaturated Hydrocarbon Reservoir Waterflooding: A simulation Approach to Performance Assessment

2021 ◽  
Author(s):  
Adekunle Tirimisiyu Adeniyi ◽  
Miracle Imwonsa Osatemple ◽  
Abdulwahab Giwa
Keyword(s):  
Oil Recovery ◽  
Net Present Value ◽  
Oil Production ◽  
Base Case ◽  
Present Value ◽  
Sweep Efficiency ◽  
Recovery Method ◽  
Solution Approach ◽  
Hydrocarbon Reservoir

Abstract There are a good numbers of brown hydrocarbon reservoirs, with a substantial amount of bypassed oil. These reservoirs are said to be brown, because a huge chunk of its recoverable oil have been produced. Since a significant number of prominent oil fields are matured and the number of new discoveries is declining, it is imperative to assess performances of waterflooding in such reservoirs; taking an undersaturated reservoir as a case study. It should be recalled that Waterflooding is widely accepted and used as a means of secondary oil recovery method, sometimes after depletion of primary energy sources. The effects of permeability distribution on flood performances is of concerns in this study. The presence of high permeability streaks could lead to an early water breakthrough at the producers, thus reducing the sweep efficiency in the field. A solution approach adopted in this study was reserve water injection. A reverse approach because, a producing well is converted to water injector while water injector well is converted to oil producing well. This optimization method was applied to a waterflood process carried out on a reservoir field developed by a two - spot recovery design in the Niger Delta area of Nigeria that is being used as a case study. Simulation runs were carried out with a commercial reservoir oil simulator. The result showed an increase in oil production with a significant reduction in water-cut. The Net Present Value, NPV, of the project was re-evaluated with present oil production. The results of the waterflood optimization revealed that an increase in the net present value of up to 20% and an increase in cumulative production of up to 27% from the base case was achieved. The cost of produced water treatment for re-injection and rated higher water pump had little impact on the overall project economy. Therefore, it can conclude that changes in well status in wells status in an heterogenous hydrocarbon reservoir will increase oil production.

scholarly journals Analysis of a Stochastic Programming Model for Optimal Hydropower System Operation under a Deregulated Electricity Market by Considering Forecasting Uncertainty

Water ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 885 ◽  
Author(s):  
Bin Xu ◽  
Ping-An Zhong ◽  
Baoyi Du ◽  
Juan Chen ◽  
Weifeng Liu ◽  
...  
Keyword(s):  
Stochastic Programming ◽  
Electricity Market ◽  
Energy Production ◽  
Programming Model ◽  
Optimal Operation ◽  
Spot Price ◽  
Deregulated Electricity Market ◽  
Hydropower System ◽  
Stochastic Programming Model ◽  
Hydropower Operation

In a deregulated electricity market, optimal hydropower operation should be achieved through informed decisions to facilitate the delivery of energy production in forward markets and energy purchase level from other power producers within real-time markets. This study develops a stochastic programming model that considers the influence of uncertain streamflow on hydropower energy production and the effect of variable spot energy prices on the cost of energy purchase (energy shortfall). The proposed model is able to handle uncertainties expressed by both a probability distribution and discretized scenarios. Conflicting decisions are resolved by maximizing the expected value of net revenue, which jointly considers benefit and cost terms under uncertainty. Methodologies are verified using a case study of the Three Gorges cascade hydropower system. The results demonstrate that optimal operation policies are derived based upon systematic evaluations on the benefit and cost terms that are affected by multiple uncertainties. Moreover, near-optimal operation policy under the case of inaccurate spot price forecasts is also analyzed. The results also show that a proper policy for guiding hydropower operation seeks the best compromise between energy production and energy purchase levels, which explores their nonlinear tradeoffs over different time periods.

Sign in / Sign up

Export Citation Format

Share Document