We consider the energy sourcing decision problem faced by industrial power consumers who must determine their long-term electricity procurement plan and need to evaluate various options to meet load requirements for t...
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ISBN:
(纸本)9781612847894
We consider the energy sourcing decision problem faced by industrial power consumers who must determine their long-term electricity procurement plan and need to evaluate various options to meet load requirements for their facilities including those which may involve on-site renewable generation. Other than sourcing from on-site renewable generation such as solar photovoltaic or wind, power can be purchased from spot markets or through a power purchase agreement, i.e. energy supply contract. We develop a mixed-integerlinear model to make decisions that include investments in renewable generation, power purchases from spot markets, and amount sourced from supply contracts. Taking into account renewable energy certificates, the model's objective is to maximize revenue from trading renewable certificates minus the expected total costs of investing and operating on-site renewable generation, and purchasing from electricity markets. Real load data from manufacturing plants are used to illustrate a numerical case study for our model.
In this paper an algorithm for the solution of the European electricity market coupling is presented, considering all block and complex orders available in the European Power Exchanges. The model takes into account th...
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In this paper an algorithm for the solution of the European electricity market coupling is presented, considering all block and complex orders available in the European Power Exchanges. The model takes into account the clearing conditions of profile and regular block orders, linked block orders, exclusive group of block orders and flexible hourly orders, as well as the clearing conditions of Minimum Income Condition and Load Gradient orders, possibly under a scheduled stop condition. The model considers also hourly flow ramping constraints on single interconnections or group of interconnections, net position ramping constraints, interconnection losses and tariffs. The flow-based approach is implemented, using the zonal PTDF matrix. The algorithm eliminates possible paradoxically accepted block and MIC orders within an iterative process. The proposed algorithm is evaluated in a pan-European day-ahead electricity marketplace.
The “Target Model” for the European electricity markets integration has received the attention of regulators, economists and market designers in the last years, namely the substitution of local electricity markets w...
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ISBN:
(纸本)9781467356688
The “Target Model” for the European electricity markets integration has received the attention of regulators, economists and market designers in the last years, namely the substitution of local electricity markets with a harmonized multi-area market, with same market segments in all European countries. In view of this market integration, a Europe-wide market-splitting model is presented in this paper, in which each national market retains its regulatory framework/design, namely remains a power pool or a Power Exchange. The developed model is tested in a Europe-wide test case, comprising three power pools and twenty two existing and prospective Power Exchanges. The model solution and the computational efficiency of the proposed implementation are presented here.
Reliable electric power supply is extremely important in modern societies. Distribution system operators (DSOs) are obligated to ensure high supply security, especially in deregulated electricity markets. DSO face pen...
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Reliable electric power supply is extremely important in modern societies. Distribution system operators (DSOs) are obligated to ensure high supply security, especially in deregulated electricity markets. DSO face penalties or pay compensatory costs when they are unable to supply electricity reliably to customers. DSOs can increase their supply reliability by either employing expensive high-reliability technology or backup power supply such as battery energy storage systems (BESSs) or generators. We have presented a novel mixed integer linear programming model to determine the economic feasibility of installing BESSs at a secondary substation in a medium voltage network. We have also determined the minimum capacity and optimal schedule of the installed BESS. Moreover, we have examined the cost-effectiveness of using BESSs if they are also used for peak shaving instead of remaining idle when there are no outages. We validated our simple but effective methodology by applying it to a substation network in Finland. All the interruptions were reduced with a BESS capacity of 112 kWh, and the savings were significant for BESS costs less than 300 {EUR}/kWh. Moreover, peak shaving increased the cost savings. However, the current costs of lithium-ion-based BESSs are nearly thrice as high, and they must decrease further before BESSs can be cost-effectively used for interruption management and peak shaving.
This paper presents an efficient method for the optimal generation scheduling of a microgrid comprising various distributed generators (DG), storage device. To give the optimal operation strategy, an optimization mode...
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ISBN:
(纸本)9781467325950
This paper presents an efficient method for the optimal generation scheduling of a microgrid comprising various distributed generators (DG), storage device. To give the optimal operation strategy, an optimization model is proposed respecting various distributed energy resources (DER) constraints and system constraints. The objective function is aimed at minimizing the system cost associated with the DCs energy production and start-up and shut-down decisions, along with possible profits. The problem is similar to a unit commitment problem in power system, however, there are some differences due to the special characteristics of DERs in the microgrid, each DER is modeled based on its characteristics and constraints. Finally, a mixed integer linear programming (MILP) method is applied to solve the problem. The effectiveness of the proposed approach is validated by case studies, the test results also indicate the MILP method is a promising approach to solve this kind of problem with high accuracy and low time consumption.
The paper deals with the day-ahead optimization of the operation of a local energy system consisting of photovoltaic units, energy storage systems and loads aimed to minimize the electricity procurement cost. The loca...
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The paper deals with the day-ahead optimization of the operation of a local energy system consisting of photovoltaic units, energy storage systems and loads aimed to minimize the electricity procurement cost. The local energy system may refer either to a small industrial site or to a residential neighborhood. Two mixed integer linear programming models are adopted, each for a different representation of the battery: a simple energy balance constraint and the Kinetic Battery Model. The paper describes the generation of the scenarios, the construction of the scenario tree and the intraday decision-making procedure based on the solution of the multistage stochastic programming. Moreover, the daily energy procurement costs calculated by using the stochastic programming approach are compared with those calculated by using the Monte Carlo method. The comparison is repeated for two different sizes of the battery and for two load profiles.
Renewable energy generation, such as photovoltaic and wind power, has been growing rapidly in recent years. However, as the penetration rate of renewable energy generation grows, the uncertainty and instability of pow...
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ISBN:
(纸本)9781538642924
Renewable energy generation, such as photovoltaic and wind power, has been growing rapidly in recent years. However, as the penetration rate of renewable energy generation grows, the uncertainty and instability of power system increases. Therefore, it is necessary to find a way to contribute toward the massive introduction of renewable energy power generation. In the present study, the authors develop an interconnection-based unit commitment model by using mixed integer linear programming considering the function of batteries. The relationship among battery energy capacity, battery output power capacity, curtailment of renewable energy generation, and fuel cost of thermal units is analyzed using this model. As a result, it is found that increasing both output power capacity and battery capacity can reduce fuel cost and encourage the introduction of renewable energy resources. Furthermore, it was found that the rated output power capacity of the battery is more important than its energy capacity.
We investigate the joint problem of relay selection and optimal sharing of relay power in wireless cellular networks with multicast traffic. We use two different performance metrics to maximize the network performance...
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ISBN:
(纸本)9781457720529
We investigate the joint problem of relay selection and optimal sharing of relay power in wireless cellular networks with multicast traffic. We use two different performance metrics to maximize the network performance. We first present a mixed Boolean-convex optimization model to maximize the overall network capacity and solve this combinatorial problem optimally using branch and bound technique. We then show that obtaining the optimal solution is computationally not feasible for large network sizes and, unlike the case of unicast traffic, a water filling method does not yield near optimal solutions in multicast scenarios. We thus adopt an algorithm based on sequential fixing which substantially reduces the computation time and achieves near optimal solutions. In addition, we present a mixed integer linear programming model to maximize the capacity of the minimum capacity link and show that the model is very efficient to reach the optimal solutions.
This paper proposes an energy-reserve market clearing model for microgrids which considers a probability reserve criteria. The probabilistic reserve criteria include pre-selected scenarios associated to the unreliabil...
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This paper proposes an energy-reserve market clearing model for microgrids which considers a probability reserve criteria. The probabilistic reserve criteria include pre-selected scenarios associated to the unreliability of generators and uncertainties caused by loads and renewable units. Unlike traditional deterministic reserve-constrained market clearing models, this paper determines the optimal amount of reserve as the point in which the sum of its operating costs and the expected cost of load shed reach a minimum. The proposed model is formulated as a stochastic programming problem oriented to co-optimize two electricity markets. The first market is the hour-ahead which evaluate the unit commitment and the energy-reserve scheduling before the realization of scenarios in the microgrid. The second is the balancing market that investigates the security assurance in the pre-selected scenarios of the microgrid. An energy management procedure was developed in order to implement the stochastic programming problem on the real microgrid ATENEA. From this, it was concluded that the reserve capacity of the microgrid throughout the scheduling horizon mainly varies according to the power output of renewable units.
The topic of this paper is coarse offline path planning for cooperating Unmanned Aerial Vehicles (UAVs), and is motivated by applications such as surveillance of power lines and railways, inspection of gas pipes, and ...
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ISBN:
(纸本)9781467349420
The topic of this paper is coarse offline path planning for cooperating Unmanned Aerial Vehicles (UAVs), and is motivated by applications such as surveillance of power lines and railways, inspection of gas pipes, and topological surveying to support the planning of new road routes. Such applications typically require a vast amount of data to be transmitted to a control center for analysis. We define a mixed integer linear programming (MBLP) optimization problem in order to solve a surveillance mission using multiple UAVs, and to effectively transmit the data back to the base station we allow for ferrying and relaying, in addition to direct transmission. The paths obtained by solving the optimization problem are analyzed using a realistic radio propagation path loss simulator. If the radio propagation path loss exceeds the maximum design criterion the optimization problem is solved again with stricter communication constraints, and the procedure is continued in an iterative manner until the criterion is met.
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