Optimal Dispatch in Power Systems with Intermittent Power Sources

With the increasing integration of intermittent power sources (IPSs) into the power system, the uncertainty of IPSs requires solution and current dispatch system needs improvement. This paper aims to generate the optimal dispatch plan for day-ahead scheduling and real-time dispatch using the proposed model of characteristic optimal power flow (COPF). The integral time period represented by the median load point and the heavy and light load point with simplicity and accuracy. Simulation case studies on a 30-bus system are presented, which shows that COPF is an effective model to generate the optimal dispatch plan for power systems with high penetration of IPSs.

Localization and characterization of intermittent pollutant source in buildings with ventilation systems:Development and validation of an inverse model

Terrorist attacks through building ventilation systems are becoming an increasing concern.In case pollutants are intentionally released in a building with mechanical ventilation systems,it is critical to localize the source and characterize its releasing curve.Previous inverse modeling studies have adopted the adjoint probability method to identify the source location and used the Tikhonov regularization method to determine the source releasing profile,but the selection of the prediction model and determination of the regularization parameter remain challenging.These limitations can affect the identification accuracy and prolong the computational time required.To address the difficulties in solving the inverse problems,this work proposed a Markov-chain-oriented inverse approach to identify the temporal release rate and location of a pollutant source in buildings with ventilation systems and validated it in an experimental chamber.In the modified Markov chain,the source term was discrete by each time step,and the pollutant distribution was directly calculated with no iterations.The forward Markov chain was reversed to characterize the intermittently releasing profile by introducing the Tikhonov regularization method,while the regularized parameter was determined by an automatic iterative discrepancy method.The source location was further estimated by adopting the Bayes inference.With chamber experiments,the effectiveness of the proposed inverse model was validated,and the impact of the sensor performance,quantity and placement,as well as pollutant releasing curves on the identification accuracy of the source intensity was explicitly discussed.Results showed that the inverse model can identify the intermittent releasing rate efficiently and promptly,and the identification error for pollutant releasing curves with complex waveforms is about 20%.

Double-uncertainty optimal operation of hybrid AC/DC microgrids with high proportion of intermittent energy sources

This paper applies double-uncertainty optimization theory to the operation of AC/DC hybrid microgrids to deal with uncertainties caused by a high proportion of intermittent energy sources.A fuzzy stochastic expectation economic model for day-ahead scheduling based on uncertain optimization theory is proposed to minimize the operational costs of hybrid AC/DC microgrids.The fuzzy stochastic alternating direction multiplier method is proposed to solve the double-uncertainty optimization problem.A real-time intra-day unbalanced power adjustment model is established to minimize real-time adjustment costs.Through comparative analysis of deterministic optimization,stochastic optimization and fuzzy stochastic optimization of day-ahead scheduling and real-time adjustment,the validity of fuzzy stochastic optimization based on a fuzzy stochastic expectation model is proved.

Distributed generator-based distribution system service restoration strategy and model-free control methods

The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.

Swiss pumped hydro storage potential for Germany’s electricity system under high penetration of intermittent renewable energy

In order to cut greenhouse-gas emissions and increase energy security,the European Commission stimulates the deployment of intermittent renewable energy sources(IRES) towards 2050.In an electricity system with high shares of IRES implemented in the network,energy balancing like storage is needed to secure grid stability and smooth demand satisfaction.Pumped hydro storage(PHS) is at this moment the best option for large scale storage.Switzerland has strong ambitions to further develop their PHS sector and become the battery of Europe.In this research,the potential of the Swiss PSH plants is explored,whilst taking inflow into the upper reservoirs of the PHS plants into consideration.To simulate electricity imbalance,Germany is used as a case study.Germany already has a high penetration of IRES and has plans to increase installed IRES capacity.By using an energy planning model(Power Plan),three future scenarios of the German electricity system were designed,each with a different set of IRES installed(solar,mixed and wind).Results show that the Swiss battery ambition offers most benefits to a wind-oriented scenario,reducing both shortages as well as surpluses.Water inflow in Swiss PHS-reservoirs is of minor importance when looking at security of supply,although it was shown that the solarscenario profits more from inflow in terms of system stability.However,a potential conflict was observed in the solar-scenario between the need for electricity storage and the storage of natural inflow,resulting in more surpluses in the system when inflow was taken into account.

Advantages of intermittently aerated SBR over conventional SBR on nitrogen removal for the treatment of digested piggery wastewater

An intermittently aerated sequencing batch reactor （IASBR） and a traditional sequencing batch reactor （SBR） were parallelly constructed to treat digested piggery wastewater, which was in high NH4＋ -N concentration but in a low COD/TN ratio. Their pollutant removal perfonnance was compared under COD/TN ratios of 1.6-3.4 d and hydraulic retention times of 5 3 d. The results showed that the IASBR removed TN, NH4＋-N and TOC more efficiently than the SBR. The average removal rates of TN, NH4＋-N and TOC were 83.1%, 96.5%, and 89.0%, respectively, in the IASBR, significantly higher than the corresponding values of 74.8%, 82.0%, and 86.2%. in the SBR. Mass balance of organic carbon revealed that the higher TN removal in the IASBR might be attributed to its efficient utilization of the organic carbon for denitrification, since that 48.7%- 52.2% of COD was used for denitrification in the IASBR, higher than the corresponding proportion of 43.1%-47.4% in the SBR. A prc-anoxic process in the IASBR would enhance the ammonium oxidation while restrict the nitrite oxidation. Anoxic duration of 40-80 min should be beneficial for achieving stable nitritation.

Economics of energy storage technology in active distribution networks

An economic and environmental evaluation of active distribution networks containing lithium ion batteries(Li-ion),sodium sulfur batteries(NaS)and vanadium redox flow batteries(VRB)was carried out using the EnergyPLAN software.The prioritization schemes of the combination of energy storage systems and intermittent energy systems were studied technically and economically based on some specific situations of the grid integrated with wind power.The results suggest that the technical and economic optimal intermittent energy-storage capacity ratio was 2:1 in predetermined energy system scenarios.Liion batteries storage system performed the best in critical excess electricity production(CEEP)absorption,energy saving and emission reduction while NaS batteries storage system was the most competitive among the three due to its cheaper costs.

A new method for optimal FTU placement in distribution network under consideration of power service reliability

Modern distribution network with high penetration of intermittent renewable sources and the so-called prosumers requires more reliable distribution automation(DA) system for safe operation and control. The design of optimal feeder terminal units(FTU)placement is critical and economical for the effective DA application. Previously proposed solutions of optimal FTU placement aiming to ensure the accuracy of state estimation(SE), typically include the following two main shortcomings: 1) only to obtain the optimal FTU placement in quantity, and the analysis of FTU location is not considered yet; 2) few consider the uncertainty of intermittent power injections in the analysis of state estimation. In this paper, a modified methodology of FTU placement is proposed not only aiming to ensure the accuracy of state estimation with the minimum number of meters, but also finding those specific FTU locations to guarantee the power service reliability. Moreover, the uncertainty models of those intermittent power injections are also considered by using probability density function(PDF). The resultant optimization problem is addressed by using the covariance matrix adaptation evolution strategy(CMA-ES). Case studies demonstrate the feasibility and effectiveness of the proposed methodology.