Abstract:Global warming has been one of the most serious worldwide problems for a long time. A very large proportion of the carbon emissions are generated by the electric power industry from fossil fuel combustion. Therefore, the promotion of low-carbon electricity is imperative to achieve sustainable development of power industry. Low-carbon electricity faces both opportunities and challenges. Low-carbon power system is bound to play a unique role with the development of low-carbon society all over the world. Development of low-carbon electricity is inseparable from the support of all kinds of new technologies. With the efforts of both academia and industry, new types of low-carbon electricity technologies emerge mush- rooming from the traditional thermal power sector to the renewable energy. The construction of pilot carbon trading, the demonstration of carbon capture power plant and other aspects of low-carbon technologies have achieved initial results. Even the low-carbon electricity technology has broad development potential; it is still in its infancy, which means more types of low-carbon electricity technologies have yet to be deepened. Low-carbon electricity has become a hot issue with the development of the global power industry. With the inclusion of 15 papers, this Special Issue focuses on strategies, mechanisms, techniques and methods of low-carbon development of power industry, showing the latest research progress of both domestic and international scholars on low-carbon electricity. This Special Issue has a wide variety of paper sources, covering universities, research institutions and power companies. Except for 9 domestic papers, there are 6 papers from overseas, including the United States, Japan, Australia, Denmark and India. The papers in this Special Issue can be divided into 4 subtitles as follows: 1) Planning of low-carbon power system; 2) Dispatch of low-carbon power systems; 3) Stability and control of low-carbon power systems; 4) Performance evaluation of a low-carbon power system.

Abstract:The objective of this paper is to model a hybrid power system for buildings, which is technically feasibleand economically optimal. With a view to promote renewable energy sources, photovoltaics and wind turbinesare integrated with the grid connected building. The systemis modeled and the optimal system configuration is estimated with the help of hybrid optimization model forelectric renewables (HOMER). The logic is illustrated with a case study based on the practical data of a building located in southern India. This building is associated with 3.4 MWh/day priority load (peak load as 422 kW), as well as 3.3 MWh/day deferrable load (peak load as 500 kW).Sensitivity analysis is performed to deal with uncertainties such as the increase in electricity consumption and gridtariff, environmental changes, etc. From the simulation result, it is observed that the designed system is costeffective and environment friendly, which leads to 6.18% annual cost savings and reduces CO2 emissions by 38.3 %.Sensitivity results indicate that the system is optimal andadaptable in a certain range of unanticipated variances with respect to best estimated value. Finally, an energy management strategy is developed for the optimal system toensure reliable power during contingency and disturbances.The green and hybrid power system designed can beadaptable to any critical and large consumers of urban buildings.

Abstract:Following the deregulation of the power industry, transmission expansion planning (TEP) has become more complicated due to the presence of uncertainties and conflicting objectives in a market environment.Also, the growing concern on global warming high lights the importance of considering carbon pricing policies during TEP. In this paper, a probabilistic TEP approach is proposed with the integration of a chance constrained load curtailment index. The formulated dynamic programming problem is solved by a hybrid solution algorithm in aniterative process. The performance of our approach is demonstrated by case studies on a modified IEEE 14-bussystem. Simulation results prove that our approach canprovide network planners with comprehensive information regarding effects of uncertainties on TEP schemes, allowing them to adjust planning strategies based on their riskaversion levels or financial constraints.

Abstract:The concern of the environment and energy sustain ability requests a crucial target of CO2 abatement and results in a relatively high penetration of renewable energy generation in the transmission system . For maintaining system reliability and security, the transmission company(TRANS CO) has to make strategic planning to handle the uncertainty challenges from the intermittent renewable energy resources. In this paper , a stochastic multipe riodmulti objective transmission planning (MPMOTP) model is proposed to reduce correlated uncertainties from renewable energy generation, conventional generation, demand sidevariations, market price volatility, and transmission configuration. Three objectives, i.e. social CO2 reduction benefit, energy purchase and network expansion cost and powerdelivery profit, are optimized simultaneously by a developedtwo-phase multi-objective particles warm optimization(MOPS O) method. The feasibility and effectiveness of the proposed uncer tainty-averse MPMOTP model have beenverified by the IEEE 24-bus test system .

Abstract:In order to boost contributions of power systems to a low-carbon economy, the installed capacity ofrenewable power generation, such as wind and photovoltaic (PV) power generation should be well planned. Abilevel formulation is presented to optimize the proportion of wind and PV capacity in provincial power systems, in which, carbon emissions of generator units and features of renewable resources are taken into account. In the lower-level formulation, a time-sequence production simulation(TSPS) model that is suitable for actual power system has been adopted. In order to maximize benefits of energy conservation and emissions reduction resulting from renewable power generation, the commercial software called General Algebraic Modeling System (GAMS) is employed to optimize the annual operation of the power system. In the upper-level formulation, the optimal pattern search(OPS) algorithm is utilized to optimize the proportion of wind and PV capacity. The objective of the upper-level formulation is to maximize benefits of energy conservation and carbon emissions reductions optimized in the lower-level problem. Simulation results in practical provincial power systems validate the proposed model and corresponding solving algorithms. The optimization results can provide support to policy makers to make the polices related to renewable energy.

Abstract:Various kinds of new engineering technologies have been studied to realize the low-carbon and sustainable power supply systems all over the world. In actual implementation of these technologies, mostly, there are multiple objectives with trade off relationships among each other,and also various constraints in the achievement of these objectives. Therefore, it should be essential to solve multiobjective optimization problems effectively in the applications of these new technologies in power systems. This paper proposes an improved method to realize multi-objective optimization for critical challenges in advanced power systems. To realize that, in an optimal dispersed generation installation problem, that is, one of effective measures for low-carbon power systems, various optimi-zation methods and their combination methods are evaluated and a hybrid method for evolutionary algorithms was developed. The method can provide improved results compared with other state-of-the-art multi-objective opti-mization methods.

Abstract:Under the environmental crisis of global warming, more efforts are put in application of low carbon energy, especially low-carbon electricity. Development of wind generation is one potential solution to provide low-carbon electricity source. This paper researches operationof wind generation in a deregulated power market. Itdevelops bidding models under two schemes for variable wind generation to analyze the competition among generation companies (GENCOs) considering transmission constraints. The proposed method employs the supply function equilibrium (SFE) for modeling the bidding strategy of GENCOs. The bidding process is solved as abi-level optimization problem. In the upper level, the profit of an individual GENCO is maximized; while in the lower level, the market clearing process of the independent system operator (ISO) is modeled to minimize the production cost. An intelligent search based on genetic algorithm and Monte Carlo simulation (MCS) is applied to obtain the solution. The PJM five-bus system and the IEEE 118-bus system are used for numerical studies. The results show when wind GENCOs play as strategic bidders to set the price, they can make significant profit uplifts as opposed toplaying as a price taker, because the profit gain will out-weigh the cost to cover wind uncertainty and reliability issues. However, this may result in an increase in total production cost and the profit of other units, which means consumers need to pay more. Thus, it is necessary to update the existing market architecture and structure con-sidering these pros and cons in order to maintain a healthy competitive market.

Abstract:The paper proposes a stochastic unit commitment (UC) model to realize the low-carbon operation requirement and cope with wind power prediction errors for power systems with intensive wind power and carboncapture power plant (CCPP). A linear re-dispatch strategyis introduced to compensate the wind power deviation from the spot forecast. The robust optimization technique is employed to obtain a reliable commitment plan against all realizations of wind power within the uncertainty set givenby probabilistic forecast. The proposed model is validated with IEEE 39-bus system. The advantages of flexible CCPPs are compared to the normal coal-fueled plants and the impacts of robustness controlling are discussed.

Abstract:Smart grid construction is an important carrierand an effective way to promote the development of low-carbon economy. Demand response (DR) is commonly regarded as an important core technology in smart grid field,and it reflects the flexible and interactive features of the corebusiness in smart electricity. It is the developing direction ofautomated demand response (ADR) technology, and its mainfeatures are the standardization of information exchange,together with the intelligence of decision-making and the automation of implementations. ADR technology can improve the efficiency of the whole power system and enhance the ability to accept new energy sources. This paper analyzes the role of demand response in improving efficiency and low-carbon energy saving power systems. The automated demand response system architecture is investi-gated, and the ADR roadmap of commercial/industrial and residential customer is proposed. The key technologies for ADR system are analyzed, including demand response strategy, information exchanging model, measurement and verification techniques, and multiagent scheduling techniques. To ensure the interoperability between the grid side and the user side, the ADR business in smart grid user interface standards is concluded to support further demand side management project.

Abstract:One of the important features of low-carbon electric power system is the massive deployment of renewable energy resources in the advent of a new carbon-strained economy. Wind generation is a major technology of generating electric power with zero carbon dioxide emission. In a power system with the high penetration of wind generation,the displacement of conventional synchronous generators with variable speed wind turbines reduces system inertia.This leads to larger system frequency deviation following aloss of large generation. In this paper, the impact of the reduction of system inertia on system frequency is analyzed as the result of the integration of a significant amount of wind generation into power systems. Further more, we present apreliminary study of the impact of the distribution of the inertia contributions from those online conventional synchronous generators on the rate of change of frequency(ROCOF) based on the total energy injected into the system due to the fault. The total fault energy is represented using Hamiltonian formulism. With the IEEE 39-bus system, it is shown that for a fault with the given injected total energy,clearing time, and location, the distribution of inertia contributions can significantly affect the magnitude of ROCOF.Moreover, for such a fault with different locations, the average of the magnitudes of ROCOF caused by the fault at different locations is larger when the distribution of the inertia contributions is more dispersed.

Abstract:Integrating a battery energy storage system (ESS)with a large wind farm can smooth the intermittent power obtained from the wind farm, but the smoothing function will not be achieved if multiple ESSs are used to smooth the fluc-tuations in individual wind powe r plants in a distributed pattern.Therefore, this study focuses on the development of a control strategy to optimize the use of m ultiple ESSs to accelerate the adoption of wind energy resources. This paper proposes aquasi-automated generation control (QAGC ) strategy to coordinate multiple ESSs, which responds to the grid dispatch demand rather than smoothing out the intermittent power from individual wind farms. The aims of QAGC are to ensure that multiple ESSs provide a service that is as balanced as possible,so more wind power systems at various scales can be accepted by the grid, as well maximizing the low-carbon benefits of ESSs. The effectiveness of QAGC is demonstrated by using data from an actual gigawatt scale cluster of wind plants.

Abstract:With the increasing integration of wind farm sand electric vehicles (EVs) in power systems, voltage stability is becoming more and more serious. Based onvehicle-to-grid (V2G), an efficient power plant model of EVs (E-EPP) was developed to estimate EV charging load with available corresponding response capacity under different charging strategies. A preventive control strategy based on E-EPP was proposed to maintain the static voltage stability margin (VSM) of power system above apredefined security level. Two control modes were used including the disconnection of EV charging load (‘V1G’mode) and the discharge of stored battery energy back to power grid (‘V2G’ mode). A modified IEEE 14-bus system with high penetration of wind power and EVs was used toverify the effectiveness of preventive control strategy.Simulation results showed that the proposed strategy can not only improve the static voltage stability of power system with considerable wind generation, but also guarantee the travelling comfort for EV owners.

Abstract:The implementation of developing the wind power is an important way to achieve the low-carbon power system. However, the voltage stability issues caused by the random fluctuations of active power output and the irrational regulations of reactive power compensation equipment have become the prominent problems of theregions where large-scale wind power integrated. In view of these problems, this paper proposed an optimal reactive power dispatch (ORPD) strategy of wind power plantscluster (WPPC) considering static voltage stability for low-carbon power system. The control model of the ORPD strategy was built according to the wind power prediction,the present operation information and the historical operation information. By utilizing the automatic voltage control capability of wind power plants and central substations,the ORPD strategy can achieve differentiated management between the discrete devices and the dynamic devices of the WPPC. Simulation results of an actual WPPC in North China show that the ORPD strategy can improve thevoltage control performance of the pilot nodes and coordinate the operation between discrete devices and the dynamic devices, thus maintaining the static voltage stability as well.

Abstract:The energy conservation plays an important role for low carbon development. In order to evaluate the energy conservation in the full life-cycle, a scheme toestimate the energy consumption, or alternatively the energy pay, in constructing an overhead transmission lineis proposed in this paper. The analysis of a typical projection is given for demonstration. With new additional overhead transmission lines, the energy consumption,known as the power loss in power network, is expected tobe decline, which is defined in this paper as the energy payback. In order to estimate this kind of contribution, the scheme that consisted of load forecast, production simulation for generating systems, load flow simulation and power loss calculation has been proposed. Case studies,based on the IEEE 24-bus test system, are given to demonstrate the efficacy of the schemes. Moreover, several presumptive scenarios are deployed and analysed with the presented schemes for comparison.

Abstract:As a major CO2 emission source, the low-carbon development of the power sector requires the sector's own efforts and the cooperation with other industries, especiallyin the context of rapid development of renewable generation technologies. The industrial demand response resources(IDRR) will be helpful to improve wind power penetration and bring low-carbon benefits if they are utilized to provide ancillary services (AS) for the power system. In this paper,demand response (DR) characteristics of industrial users are firstly analyzed according to their production process and electricity consumption distribution. In order to have an in-depth study of the response mechanism of industrial loads to provide AS, cement and aluminum smelter are selected as two typical IDRR, and the AS type they provided and response mechanism are analyzed. Based on the data of these two industries in certain provinces of China, low-carbon benefits considering IDRR to provide AS are analyzed.

Abstract:In response to the severe energy and environmental issues, CO2 emission reduction and low-carbon development are inevitable. China has become the biggest CO2 emitter in the world since 2006. As a major CO2 emission source in China, the power industry is facing greater pressure for carbon emission abatement. By applying various low-carbon power technologies andmechanisms, the potential for CO2 emission reduction in power systems is considerable. This paper proposes apseudo-sequential Monte Carlo simulation method for the low-carbon benefit evaluation of distribution system including distributed wind turbines, solar array and battery energy storage systems. The hourly sequential models andstate variation models for wind turbines, solar array and battery are established. The non-power components are sequentially sampled and the components of the wind turbine, the solar array and the battery are non-sequentially sampled. The failure modes and effect analysis (FMEA)procedure for the system are discussed and the heuristicload shedding approach is used, then the lowcarbon benefit evaluation procedure is illustrated. Based on this, the system state transition sampling method for calculating the loss of expected energy index with high DG penetration isproposed. The state transition models for non-active elements and DGs are established. The validity of the proposed method is demonstrated by a study case. The method can be used for the low-carbon benefit analysis on DG penetration distribution networks.