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Abstract This paper proposes novel decentralized control design methods for occupant comfort and energy saving in smart multi-zone buildings. First, the graph-based modeling technique for buildings is utilized to obtain a simplified lumped model for thermal dynamics of zones. Second, the graph theory is employed to derive features of the model useful for the control design. Next, two methods are proposed based on the pole placement in linear matrix inequality (LMI) region technique and the Lyapunov inequality to synthesize decentralized controllers to track the reference temperatures set by users for their thermal comfort and to save energy. The effectiveness of the proposed designs are then illustrated in a numerical example. [ABSTRACT FROM AUTHOR]

Abstract: In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1–6h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy. [Copyright &y& Elsevier]

The voltage collapse phenomenon is one of the serious concerns for power system stable operation. Power system blackout can take place in a part or entire system due to severe voltage instability and inadequate power transfer capability. Therefore, power system operation continuous monitoring and enhancement of the power transmission capability are major concerns for power system planning, design and operation. This study proposes an improved voltage stability index by drawing analogy from existing indices, which are based on active and reactive power changes in a power system. The objective of the employed computational technique is to measure the critical boundaries, therefore, the proposed index is called Critical Boundary Index CBI. The Lagrange Constant computational method is employed to derive the improved index. Then a comparative analysis of the similar indices are presented to show the advantage of the proposed index. Lastly, proposed and conventional indices are evaluated using IEEE 5, 14, and 57 bus test systems. The results indicate some advantages of the proposed index compared to the conventional indices in the same way. Such as applicability of the proposed index for various types of power system topologies with high accuracy. [ABSTRACT FROM AUTHOR]

Abstract: Due to the depletion of energy resources and global warming, renewable energies such as the solar collector (SC) and photovoltaic generation (PV), are gaining more widespread use in residential areas. In Japan, incentive to install these units for consumers is provided by governmental support with the introduction of feed-in tariffs (FIT) and governmental subsidies. Thus, it is possible to reduce electricity cost in houses using time-of-use (TOU) price and to get benefit from selling power generated by PV. Furthermore, investment costs of PV and battery systems are decreasing year by year; on however, the price of purchased power for consumers is increasing and the selling price by FIT is decreasing annually. Hence, it is important to reveal which year, at what capacity, and which system and appliances are best choices for the consumer. In this paper, an expansion planning model of PV and battery systems for the smart house is presented. The expansion planning period is 20 years and ranges from 2015 to 2035. The proposed method clarifies the optimal installation year, capacity and appliances during the twenty year period considering variable characteristics such as investment cost, selling price and purchasing price which change year by year. [Copyright &y& Elsevier]

Abstract: Recently, the deregulation and liberalization in power market increase the competition in retail and power sector. Therefore, power company needs to reduce operational cost and maximizes the profit by operating generator with higher efficiency. On the other hand, energy consumption is increasing rapidly due to the proliferation of all-electric houses. So the controllable load such as electric water heater, heat pump and electric vehicles are introduced to the power system. However conventional system does not operate the thermal unit and controllable load in a coordinated manner. This paper focuses on operating the controllable load, battery and thermal units in a coordinated manner. Furthermore, this paper considers the transmission constraints. The proposed method uses a tabu search for optimization method. Optimizing procedure is divided into two parts. Firstly, actual load is controlled by controllable load and battery. Finally, the schedule of thermal unit commitment problem is decided in the revised load. Simulation results show the validation of proposed method and validate the performance and effectiveness of the algorithm for controllable load and battery. [Copyright &y& Elsevier]

Abstract: From the perspective of global warming mitigation and depletion of energy resources, renewable energy such as wind generation (WG) and photovoltaic generation (PV) are getting attention in distribution systems. Additionally, all-electric apartment houses or residence such as DC smart houses are increasing. However, due to the fluctuating power from renewable energy sources and loads, supply-demand balancing of power system becomes problematic. Smart grid is a solution to this problem. This paper presents a methodology for optimal operation of a smart grid to minimize the interconnection point power flow fluctuation. To achieve the proposed optimal operation, we use distributed controllable loads such as battery and heat pump. By minimizing the interconnection point power flow fluctuation, it is possible to reduce the electric power consumption and the cost of electricity. This system consists of photovoltaic generator, heat pump, battery, solar collector, and load. To verify the effectiveness of the proposed system, results are used in simulation presented. [Copyright &y& Elsevier]

Abstract: A Photovoltaic system’s output power fluctuates as insolation varies with weather condition. Fluctuating PV power causes frequency deviations when large PV power is penetrated in the isolated utility. In this paper, a fuzzy based method for leveling the fluctuations of PV power in a PV-diesel hybrid power system is proposed. By means of the proposed method, output power control of PV system becomes possible considering power utility conditions and the conflicting objective of output power leveling and maximizing energy capture is achieved. Here, fuzzy control is used to generate the output leveling power command. The fuzzy control has three inputs of average insolation, variance of insolation, and absolute average of frequency deviation. First, the proposed method is compared with the method where captured maximum power is given to the utility without leveling. Second, the proposed method is compared with a conventional method where captured maximum power is leveled by using an energy storage system and is given to the isolated utility. Simulation results show that the proposed method is effective in leveling PV power fluctuations and is feasible to reduce the frequency deviations of the isolated power utility. [ABSTRACT FROM AUTHOR]

Abstract: Recently, renewable energy technologies such as wind turbine generators and photovoltaic systems have been introduced as distributed generation. The connection of large number of distributed generators causes voltage deviation beyond the statutory range in a distribution system. In this paper, a methodology for voltage control in proposed by using the tap changing transformers and the inverters interfaced with the distributed generators. In the proposed method, information of the voltage and power is collected via a communication network. Based on these information, the optimal reference values are calculated at the control center, and sent to the transformers and the inverters. The proposed method accomplishes a coordinated operation among the control equipments and reduces the voltage deviation. Effectiveness of the proposed method is verified by the numerical simulation results. [Copyright &y& Elsevier]

Abstract: Recently, dispersed generators have been installed in distribution network to supply power to commercial facilities. Renewable energy generation contains output power fluctuations and distributed generator produces sluggish response for power demand. In order to overcome these problems, an ultra capacitor energy storage system is used for compensating the instantaneous power imbalance. However, use of a large capacity ultra capacitor energy system increases system cost. In addition, PPSs (Power Producer and Supplier) that own these generators are supposed to achieve 30-min balancing control for stable supply of electric power. This paper proposes a control system to achieve both 30-min balancing control and interconnection point power flow control by using a fuel cell and an ultra capacitor based on the H ∞ control theory. Besides, remaining storage energy of the ultra capacitor is controlled to be constant to maintain compensation capability. Effectiveness of the proposed control system is verified by using simulation results. [Copyright &y& Elsevier]

Abstract: This paper deals with a DC-micro-grid with renewable energy. The proposed method is composed of a gearless wind power generation system, a battery, and DC loads in a DC distribution system. The battery helps to avoid the DC over-voltages by absorbing the power of the permanent magnet synchronous generator (PMSG) during line-fault. In addition, the control schemes presented in this paper including the maximum power point tracking (MPPT) control and a pitch angle control for the gearless wind turbine generator. By means of the proposed method, high-reliable power can be supplied to the DC distribution system during the line-fault and stable power supply from the PMSG can be achieved after line-fault clearing. The effectiveness of the proposed method is examined in a MATLAB/Simulink® environment. [Copyright &y& Elsevier]

Abstract: In recent years, distributed generations based on natural energy or co-generation systems are increasing due to global warming and reduction of fossil fuels. Many of the distributed generations are set up in the vicinity of customers, with the advantage that this decreases transmission losses and transmission capacity. However, output power generated from renewable energy such as wind power and photovoltaics, is influenced by weather conditions. Therefore if the distributed generation increases with conventional control schemes, the voltage variation in a distribution system becomes a serious problem. In this paper, an optimal control method of distribution voltage with coordination of distributed installations, such as On Load Tap Changer (OLTC), Step Voltage Regulator (SVR), Shunt Capacitor (SC), Shunt Reactor (ShR), and Static Var Compensator (SVC), is proposed. In this research, the communication infrastructure is assumed to be widespread in the distribution network. The proposed technique combines genetic algorithm (GA) and Tabu search (TS) to determine the control operation. In order to confirm the validity of the proposed method, simulation results are presented for a distribution network model with distributed (photovoltaic) generation. [Copyright &y& Elsevier]

Abstract: The output power fluctuations of renewable energy plants such as wind turbine generators and photovoltaic systems cause frequency deviations and terminal voltage fluctuations. Furthermore, these power fluctuations also affect the turbine shaft of diesel generator and gas-turbine generators which are usually the main electric power systems in isolated islands. This paper presents a control strategy that achieves torsional torque suppression and power system stabilization. Since the measurement of the torsional torque is technically difficult and there is uncertainty in mechanical constants of the shaft torsional system, the torsional torque is estimated by using a H ∞ observer. The simulation results validate the effectiveness of the proposed control system. [Copyright &y& Elsevier]

Abstract: This paper investigates the control method under the 30-min balancing rule for grid-connected PV power. It is possible to adjust the noticed power for PV supply before two hours. The noticed power, that is the adjusted PV supply, and the measured power are controlled under the 30-min balancing rule using a battery, and the 30-min control section is divided. [Copyright &y& Elsevier]

Abstract: This paper proposes a technique that determines the optimal windmill operation speed and the optimal rotor flux. Moreover, the position and speed sensor-less wind generation system using the electromotive voltage observer to estimate rotor position and full-order observer to estimate rotor speed and the windmill output torque are proposed. The position and speed sensor-less maximum power point of wind power generation system is controlled by using the above estimated values, optimized windmill operation speed for maximum output power and optimized rotor flux for minimum generator losses. The effectiveness of the position and speed sensor-less maximum power point tracking control for wind power generation system with squirrel cage induction generator is verified by simulations. The simulation results confirm that the proposed method can estimate the operation speed efficiently. [Copyright &y& Elsevier]

Abstract: Operation of variable speed wind turbine generator (WTG) in the above-rated region characterized by high turbulence intensities demands a trade-off between two performance metrics: maximization of energy harvested from the wind and minimization of damage caused by mechanical fatigue. This paper presents a learning adaptive controller for output power leveling and decrementing cyclic loads on the drive train. The proposed controller incorporates a linear quadratic Gaussian (LQG) augmented by a neurocontroller (NC) and regulates rotational speed by specifying the demanded generator torque. Pitch control ensures rated power output. A second-order model and a stochastic wind field model are used in the analysis. The LQG is used as a basis upon which the performance of the proposed paradigm in the trade-off studies is assessed. Simulation results indicate the proposed control scheme effectively harmonizes the relation between rotor speed and the highly turbulent wind speed thereby regulating shaft moments and maintaining rated power. [Copyright &y& Elsevier]

Abstract: Probabilistic paradigms for wind turbine controller design have been gaining attention. Motivation derives from the need to replace outdated empirical-based designs with more physically relevant models. This paper proposes an adaptive controller in the form of a linear quadratic Gaussian (LQG) for control of a stall-regulated, variable speed wind turbine generator (WTG). In the control scheme, the strategy is twofold: maximization of energy captured from the wind and minimization of the damage caused by mechanical fatigue due to variation of torque peaks generated by wind gusts. Estimated aerodynamic torque and rotational speed are used to determine the most favorable control strategy to stabilize the plant at all operating points (OPs). The performance of the proposed controller is compared with the classical proportional-integral-derivative (PID) controller. The LQG is seen to be significantly more efficient especially in the alleviation of high aerodynamic torque variations and hence mechanical stresses on the plant drive train. Simulation results validate the effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: The authors propose a twofold simulated annealing (twofold-SA) method for the optimization of fuzzy unit commitment formulation in this paper. In the proposed method, simulated annealing (SA) and fuzzy logic are combined to obtain SA acceptance probabilities from fuzzy membership degrees. Fuzzy load is calculated from error statistics and an initial solution is generated by a priority list method. The initial solution is decomposed into hourly-schedules and each hourly-schedule is modified by decomposed-SA using a bit flipping operator. Fuzzy membership degrees are the selection attributes of the decomposed-SA. A new solution consists of these hourly-schedules of entire scheduling period after repair, as unit-wise constraints may not be fulfilled at the time of an individual hourly-schedule modification. This helps to detect and modify promising schedules of appropriate hours. In coupling-SA, this new solution is accepted for the next iteration if its cost is less than that of current solution. However, a higher cost new solution is accepted with the temperature dependent total cost membership function. Computation time of the proposed method is also improved by the imprecise tolerance of the fuzzy model. Besides, excess units with the system dependent probability distribution help to handle constraints efficiently and imprecise economic load dispatch (ELD) calculations are modified to save the execution time. The proposed method is tested using standard reported data sets. Numerical results show an improvement in solution cost and time compared to the results obtained from other existing methods. [Copyright &y& Elsevier]

Abstract: In isolated islands, usually diesel generators supply electric power. However, there are problems, e.g., a lack of fossil fuel, environmental pollution etc. So, isolated island, e.g. Miyako island, installs renewable energy power production plants. However, renewable energy power production plants are very costly. This paper presents an optimal configuration of power system in isolated island installing renewable energy power production plants. The generating system consists of diesel generators, wind turbine generators, PV system and batteries. Using the proposed method, operation cost can be reduced about 10% in comparison with diesel generators only from simulation results. [Copyright &y& Elsevier]

Abstract: This paper introduces the scheduling method for thermal and energy storage system (ESS) unit commitment. The ESS is incorporated to achieve peak load-levelling and reduce the total cost. The thermal scheduling is implemented by the extended priority list (EPL) method. The EPL method consists of two steps, in the first step we get rapidly some initial unit commitment schedules by the priority list (PL) method. In this step, operational constraints are disregarded. In the second step, unit schedules are modified using the problem specific heuristics to fulfill operational constraints and to reduce the total cost. To calculate efficiently, heuristics are only applied to solutions which can be expected improvement. The ramp constraints for thermal unit are considered at the last of EPL method. The ESS scheduling is carried out based on the thermal unit schedule obtained by the EPL method. Several numerical examples demonstrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

Abstract: In order to perform maximum power point tracking control of wind generation system, it is necessary to drive windmill at an optimal rotor speed. For that purpose, a rotor position and a wind velocity sensors become indispensable. However, from the aspect of reliability and increase in cost, rotor position sensor and wind velocity sensor are not usually preferred. Hence, wind velocity and position sensorless operating method for wind generation system using observer is proposed in this paper. Moreover, improving the efficiency of the permanent magnet synchronous generator is also performed by optimizing d-axis current using the Powell method. [Copyright &y& Elsevier]

Abstract: This paper presents a practical method for short-term load forecast problem using artificial neural network (ANN) combined similar days approach. Neural networks applied in traditional prediction methods all use similar days data to learn the trend of similarity. However, learning all similar days data is a complex task, and does not suit the training of neural network. A Euclidean norm with weighted factors is used to evaluate the similarity between the forecast day and searched previous days. According to similar days approach, load curve is forecasted by using information of the days that are similar to weather condition of the forecast day. An accuracy of the proposed method is enhanced by the addition of temperature as a major climate factor, and special attention was paid to model accurately in different seasons, i.e. Summer, Winter, Spring, and Autumn. The one-to-six hour-ahead forecast errors (MAPE) range from 0.98 to 2.43%. Maximum and minimum percentage errors, and MAPE values obtained from the load forecasting results confirm that ANN-based proposed method provides reliable forecasts for several-hour-ahead load forecasting. [Copyright &y& Elsevier]

Abstract: This paper presents a new approach for unit commitment problem using Stochastic Priority List method. In this method, rapidly some initial unit commitment schedules are generated by Priority List method and priority based stochastic window system. Excess units are added with system dependent probability distribution to avoid overlooking a desired solution during repeated search. Constraints are not considered in this stage. Then schedules are modified gradually using the problem specific heuristics to fulfill constraints. To reduce calculations, heuristics are applied only to the solutions, which can be expected to improve. Besides, sign vector is introduced to reduce economic load dispatch (ELD) overhead recalculations. This process is repeated for optimal solution. The proposed method is tested using the reported problem data set. Simulation results for the systems up to 100-unit are compared to previous reported results. Numerical results show an improvement in solution cost and time compared to the results obtained from Genetic Algorithm and others. [Copyright &y& Elsevier]

In recent years, gas turbines have been attracting a lot of attention in the field of dispersed generations and co-generation systems. The gas turbine generation system always has the problem of the shaft torsional oscillation, and their counter measures that can apply especially for the in-house generating plants at 10 MW scale are required. For technical and financial reasons, the number of sensors has to be reduced to an acceptable minimum, and generally it is not possible to measure the torsional oscillations at all critical shaft locations. Thus the torsional oscillations on the crucial components should be estimated by using the measured rotating speed at turbine shaft end. This paper presents the shaft torque observer and coordinated controllers for the in-house generating plants. In this study the turbine model with 7-mass has been used, and the rate of the in-house generating shaft is 5 MVA. Linear quadratic regulat or theory (LQR) is used to design the observer gain, which provides acceptable estimated values. The estimation accuracy of this observer is within 10%, and the influence by the measurement error of the shaft parameter is also a little. [Copyright &y& Elsevier]