Risk Averse Optimal Operation of a Virtual Power Plant using two Stage Stochastic Programming (original) (raw)
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International Journal of Energy Research, 2019
This paper proposes a stochastic scheduling model to determine optimal operation of generation and storage units of a virtual power plant (VPP) for participating in a joint energy and regulation service (RS) market under uncertainty. Beside electricity, the VPP provides required RSs according to the probability of delivery request in the electricity market. A new model for providing RS is introduced in which the dispatchable generation units are financially compensated with their readiness declarations and will be charged/paid for their realtime down/up regulations. Besides, the VPP sets up incentive price-quantity curves to benefit from the potential of demand side management in both energy and RS market. Within the model presented here, the VPP consists of two types of generation units: wind turbine and standby diesel generator; the latter is modeled by considering CO 2-emission penalty costs. The given uncertainties are divided into two parts. Firstly, the uncertainties from the energy market price are simulated using information gap decision theory to evaluate the risk-based resource scheduling for both risk-taker and risk-averse VPP. Other uncertainties affecting decision making such as wind turbine generation, load, regulation up/down calling probabilities, and regulation market prices are modeled via scenario trees. Three typical case studies are implemented to validate the performance and effectiveness of the proposed scheduling approach.
Offering model for a virtual power plant based on stochastic programming
Applied Energy, 2013
h i g h l i g h t s " A two-stage stochastic offering model for a virtual power plant is presented. " The virtual power plant consists of an intermittent source, a dispatchable source and a storage unit. " The virtual power plant trades in the day-ahead and balancing markets. " Characteristic scenarios are thoroughly analyzed and relevant conclusions are drawn. a b s t r a c t A virtual power plant aggregates various local production/consumption units that act in the market as a single entity. This paper considers a virtual power plant consisting of an intermittent source, a storage facility, and a dispatchable power plant. The virtual power plant sells and purchases electricity in both the day-ahead and the balancing markets seeking to maximize its expected profit. Such model is mathematically rigorous, yet computationally efficient.
Optimal operation of a virtual power plant with risk management
2012 IEEE PES Innovative Smart Grid Technologies (ISGT), 2012
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Risk-constrained stochastic optimal allocation of energy storage system in virtual power plants
Journal of Energy Storage, 2020
This paper aims to develop a decision-making procedure for efficient placement and sizing of energy storage system (ESS) within virtual power plants (VPPs) premises under the uncertainty of market price. The main aim is to minimize the overall cost of VPP within a fixed time horizon planning. The understudy VPP consists of wind turbine, photovoltaic system, curtailable loads, ESS, and diesel generators in which the VPP trades electricity with the upstream grid. The proposed framework investigates both optimal power and optimal energy of ESS based on the available budget for investment. To hedge against the uncertainty of investment, an efficient risk management manner based on the concept of conditional value at risk is applied. Moreover, from the reliability point of view, two reliability indices: the loss of load expectation and energy expected not served, are evaluated under different levels of investment to assess the impact of ESS on VPP reliability. The proposed model is formulated as a mixed-integer nonlinear programming problem and is solved by the well-known General Algebraic Modeling System commercial software package. The effectiveness of the proposed risk-based optimization approach is demonstrated through vigorous case studies and comprehensive cost-benefit analysis.
Optimisation and Management of Virtual Power Plants Energy Mix Trading Model
International Journal of Renewable Energy Development, 2021
In this study, a robust optimisation method (ROM) is proposed with aim to achieve optimal scheduling of virtual power plants (VPPs) in the day-ahead electricity markets where electricity prices are highly uncertain. Our VPP is a collection of various distributed energy resources (DERs), flexible loads, and energy storage systems that are coordinated and operated as a single entity. In this study, an offer and bid-based energy trading mechanism is proposed where participating members in the VPP setting can sell or buy to/from the day-ahead electricity market to maximise social welfare (SW). SW is defined as the maximisation of end-users benefits and minimisation of energy costs. The optimisation problem is solved as a mixed-integer linear programming model taking the informed decisions at various levels of uncertainty of the market prices. The benefits of the proposed approach are consistency in solution accuracy and traceability due to less computational burden and this would be beneficial for the VPP operators. The robustness of the proposed mathematical model and method is confirmed in a case study approach using a distribution system with 18-buses. Simulation results illustrate that in the highest robustness scenario, profit is reduced marginally, however, the VPP showed robustness towards the day-ahead market (DAM) price uncertainty.
Optimal Offering Strategy of a Virtual Power Plant: A Stochastic Bi-Level Approach
IEEE Transactions on Smart Grid, 2015
This paper addresses the optimal bidding strategy problem of a Commercial Virtual Power Plant (CVPP), which comprises distributed energy resources (DER), battery storage systems (BSS) and electricity consumers and participates in the day-ahead electricity market. The CVPP ultimate goal is the maximization of the day-ahead profit in conjunction with the minimization of the anticipated real-time production and consumption imbalance charges. A three-stage stochastic bi-level optimization model is formulated, where the uncertainty lies in the day-ahead CVPP DER production and load consumption as well as in the rivals' offer curves and real-time balancing prices.
Sādhanā, 2020
Renewable energy-based on virtual power plants (VPPs) has recently attracted considerable attention for participating in energy and reserve markets due to the disadvantages of thermal power plants (TPPs). The present paper aims to maximize the VPP profitability in distribution networks including thermal power plants, at minimum load cost, using a mathematical model for implementing the VPP and evaluating its role in the energy and reserve markets. The proposed model includes a series of probabilistic scenarios used to consider the uncertainty of wind/solar generation. Therefore in the first step, the lower bound of the problem, i.e., minimizing demand cost for all the units, should be calculated. It determines the status of VPP units based on the best-case scenarios. Afterward, the problem is cut to calculate the upper bound of the problem which is maximizing the profit of the VPP. The problem is evaluated in two cases: one is the presence of VPP only in the energy market and the other is the simultaneous presence of the VPP in the reserve and energy markets. The computation ends with the convergence of lower and upper bounds of the problem. Since the proposed method uses a piece-wise model of thermal units and the problem has nonlinear equations, Mixed Integer Programming (MIP) used to calculate the contribution of units by utilizing GAMS software. Finally, the VPP profitability calculated for the day-ahead energy and reserve market after determining the method for the participation of power plants in supply at the minimum cost. The proposed method was then applied to a sample system consisting of three thermal plants, three wind farms, two solar farms, and two energy storage systems, considering several situations to examine the impact of the resources and also the resulting profitability in the energy and reserve market. The final step was the analysis of the results.
Economic Optimal Implementation of Virtual Power Plants in the German Power Market
Energies
The burden of excess energy from the high renewable energy sources (RES) share creates a significant reduction of residual load for the future, resulting in reduced market prices. The higher the share of stochastic RES, the more often the price will be 0 €/MWh. The power market needs new methods to solve these problems. The development of virtual power plants (VPPs) is aimed at solving techno-economic problems with an increasing share of RES in the power market. This study analyses a possible implementation of stochastic and deterministic RES in a VPP to generate secured power, which can be implemented in the European Power Exchange (EPEX)/European Energy Exchange (EEX) power market using existing market products. In this study, the optimal economic VPP configuration for an RES-based power plant is investigated and implemented into standard power market products. The results show that the optimal economic VPP configuration for different market products varies, depending on the energ...
OPTIMIZATION BY STOCHASTIC PROGRAMMING FOR THE AGGREGATION OF A COMMERCIAL VIRTUAL POWER PLANT
Future large penetration of Distributed Energy Resources (DER) leads to explore the potential of technical integration of these dispersed small-size generators into the distribution network. New actors may emerge, devoted to the commercial or technical aggregation, in order to provide ancillary services or to gain global productivity. Aggregating a set of small producers into a commercial Virtual Power Plant could enable its market participation like a conventional power plant. The function of aggregation should be able to reduce imbalance risk in the market, by the means of an existing methodology based on stochastic programming. This methodology is described and extended to new generation characteristics, with a discussion about the necessary improvements and about its application to a real-size case, on a rural alpine area.