Scenario-Based Stochastic Framework for Optimal Planning of Distribution Systems Including Renewable-Based DG Units (original) (raw)
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This paper proposes a probabilistic dynamic model for multi-objective distributed generation planning which also considers network reinforcement at presence of uncertainties associated to the load values, generated power of wind turbines and electricity market price. Monte Carlo simulation is used to deal with the mentioned uncertainties. The planning process is considered as a two-objective problem. The first objective is the minimization of total cost including investment and operating cost of DG units, the cost paid to purchase energy from main grid and the network reinforcement costs. The second objective is defined as the minimization of technical risk, including the probability of violating the safe operating technical limits. The Pareto optimal set is found using NSGA-II method and the final solution is selected using a max-min method. The model is applied on two distribution networks and compared with other models to demonstrate its effectiveness.
Energy, 2016
Due to the development of renewable energy sources (RESs), maximization of hosting capacity (HC) of RESs has gained significant interest in the existing and future power systems. HC maximization should be performed considering various technical constraints like power flow equations, limits on the distribution feeders' voltages and currents, as well as economic constraints such as the cost of energy procurement from the upstream network and power generation by RESs. RESs are volatile and uncertain in nature. Thus, it is necessary to handle their inherent uncertainties in the HC maximization problem. Wind power is now the fastest growing RESs around the world. Hence, in this paper a stochastic multi-objective optimization model is proposed to maximize the distribution network's HC for wind power and minimize the energy procurement costs in a wind integrated power system. The following objective functions are considered: 1) Cost of the purchased energy from upstream network (to be minimized) and 2) Operation and maintenance cost of wind farms. The proposed model is examined on a standard radial 69 bus distribution feeder and a practical 152 bus distribution system. The numerical results substantiate that the proposed model is an effective tool for distribution network operators (DNOs) to consider both technical and economic aspects of distribution network's HC for RESs.
Mathematics
Renewable energy integration has been recently promoted by many countries as a cleaner alternative to fossil fuels. In many research works, the optimal allocation of distributed generations (DGs) has been modeled mathematically as a DG injecting power without considering its intermittent nature. In this work, a novel probabilistic bilevel multi-objective nonlinear programming optimization problem is formulated to maximize the penetration of renewable distributed generations via distribution network reconfiguration while ensuring the thermal line and voltage limits. Moreover, solar, wind, and load uncertainties are considered in this paper to provide a more realistic mathematical programming model for the optimization problem under study. Case studies are conducted on the 16-, 59-, 69-, 83-, 415-, and 880-node distribution networks, where the 59- and 83-node distribution networks are real distribution networks in Cairo and Taiwan, respectively. The obtained results validate the effec...
Robust planning methodology for integration of stochastic generators in distribution grids
IET Renewable Power Generation, 2007
The number of distributed generation (DG) units being connected at the low-and medium-voltage level is evermore increasing. Because of the mostly non-dispatchable generation profile of small-scale renewable power sources, grid performance can be ameliorated as well as deteriorated. A traditional mathematical optimisation of techno-economic objectives is elaborated upon. A conservative approach can, however, easily underestimate performance deviations due to the stochastic output of DG. A robust planning methodology is formulated, based on accuracy improving Monte Carlo simulations nested in an evolutionary algorithm. Multiple objectives are pursued to assess proper trade-offs regarding the technical and economical aspects.
Multi-objective planning framework for stochastic and controllable distributed energy resources
Iet Renewable Power Generation, 2009
The amount of distributed energy resources (DER) in the grid is continually increasing, and the potential benefits and drawbacks are becoming clearer. However, there is still a lack of clarity in how these multiple effects interact and which trade-offs should be made in the integration of new DER. There is a clear need for appropriate DER planning tools in the current market environment, in which both DER operators and distribution system operators (DSOs) may have multiple, often conflicting objectives and where uncertainty remains present as to which targets can be reached with a high amount of DER in the grid. A novel multi-objective planning framework is presented for the integration of stochastic and controllable DER in the distribution grid. A case study that illustrates the proposed framework is presented. Active DER management in terms of curtailment as well as dispatch of units is studied using the proposed multi-objective approach. Additionally, the extent to which active DER can be used as an alternative for grid reinforcements is analysed. The results show that the proposed multi-objective approach permits a better evaluation of the potential of active DER to support system operation.
Anais do Simpósio Brasileiro de Sistemas Elétricos 2020, 2020
Nowadays, the penetration of distributed generation (DG) units in power systems is increasing because of their benefits on the power systems. Place, type and size of distributed generators play an important role in power loss reduction, power quality improvement, security enhancement, and cost reduction. Therefore, optimal placement and sizing of DG units in electric power systems are one of the most important problems that should be evaluated carefully. DG allocation is a constrained optimization problem with different important objectives such as power loss minimization, voltage profile improvement, reliability enhancement, investment and operation cost reduction, etc. In this paper, regarding higher distribution active losses compared to transmission and generation losses and investment limitation, DG allocation problem is solved for photovoltaic units, aiming minimization of energy and investment costs considering generation uncertainty and load variation. Due to high uncertainties of solar energy resource, the problem is evaluated under different scenarios of solar radiation under a stochastic programming approach. Tests were carried out using the 33-node distribution system and the obtained results demonstrate the advantage of optimal DG allocation as well as the efficiency of the adopted mathematical to find the optimal solution.
So far, Distributed Generations (DGs) have been vast put in practice due to their evident roles in both technical and economical performance of power distribution systems. This paper investigates the presence of renewable energies once DG integration to the network has to be planned. A multiobjective optimization approach has been presented where the risk costs, the share of private investments, and imposed costs are considered as the main objectives. Performancebased regulation is also incorporated as an incentive mechanism in the DG planning process in presence of renewable energy sources (RES). The proposed scheme is adapted to the 37-Bus IEEE standard test system and the anticipated efficiency of the proposed method is well verified by then.
Reliability worth is very important in power system planning and operation. Due to continuous growth of demand, power system restructuring, and deregulation, small scattered generators referred as Dispersed Generation (DG) units are gaining momentum due to their network support capabilities and modular designs. Integration of the DG units into distribution systems is one of the effective and viable planning option for improving the supply quality and reliability of the system with ever increasing demand. It is predicted that non-conventional DG units may play key role in future power distribution systems for sustainable and emission free energy supply. However the stochastic nature and the uncertainties associated with the renewable sources introduce special technical and economical challenges that have to be comprehensively investigated in order to facilitate the deployment of these stochastic DG units in the distribution system. With this intent, this paper aims to analyze the effectiveness of various stochastic DG units available in literature based on the calculations of various reliability indices. The focus of this paper is on generating a probabilistic generation-load model that combines all possible operating conditions of the stochastic renewable DG units with their probabilities, hence accommodating this model in a deterministic planning problem for enhancement of system reliability.