Modeling Analysis Of Economic Emission Dispatch With Wind Power

Energy and environmental problems are two important issues of world economy and social sustainable development. To get rid of the restriction of the traditional energy utilization mode, many countries begin to develop and utilize renewable energy. Developing renewable energy industry, saving and replacing parts of fossil energy become an important strategic choice of China. It can ensure the safety of energy, tackle climate change, preserve the ecological environment, improve the national competiveness, and promote the national economy and social sustainable development. As a vast country, China has a long coastline. Thus abundant resources of wind power become an important alternative of fossil energy. With the improvements of policy system and technology, Chinese wind power installed capacity increases rapidly in recent years. However, thermal power is more competitive than wind power in reliability and cost. Therefore, wind power generation in China always plays a secondary role in energy supply system. With the improvement of wind turbines’ cost and reliability, except for reason of manufacturing technology level, operation management also becomes a significant reason. This work is meaningful for the research field of economic emission dispatch considering the influences of wind power integration on the economic and environmental indicators of power system. The main research work and conclusions are as follows:(1) This paper presents a model to solve the economic emission dispatch(EED) problem including wind power. Besides the classic EED factors, the factors accounting for overestimation and underestimation of available wind power in both economic and environmental aspects are specially considered. To deduce the deterministic model, the statistical characteristic of available wind power is determined based on the feature of wind speed. With the help of MATLAB optimizing toolbox, the optimization problem is solved by a scenario consisting of two conventional generators and two wind-powered generators. The simulation results are as follows: If the wind farm is owned by the other power system, the allocation of system generation capacity may be influenced by multipliers related to the cost and emissions for underestimation of available wind power, and by the multiplier related to the cost for overestimation of available wind power. Nevertheless, the multiplier related to the emissions for overestimation of available wind power has little impact on the allocation. If the power system possesses the wind farm, the allocation of system generation capacity may be influenced by multipliers related to the cost and emissions for underestimation of available wind power. Nevertheless, multipliers related to the cost and emissions for overestimation of available wind power have little impact on the allocation.(2) Based on multi-objective chance constrained programming, this paper formulates a dynamic economic emission dispatch(DEED) model for the system incorporating wind power. Besides the up spinning reserve and the down spinning reserve constraints, both the fuel cost and emission of atmospheric pollutants of thermal generators are considered as objective functions in the proposed model. According to the cumulative distribution function of wind power, this stochastic optimization model is transformed into a deterministic one. NSGA-II with a heuristic strategy is designed to solve the DEED problem. The proposed model and solution are tested on a system consisting of ten thermal generators and one large-scale wind farm. The simulation results demonstrate its rationality and effectiveness. And this paper draws the following conclusions: increasing the proportion of wind power will bring more risks for the power dispatch, although it is beneficial for economy and environment. The decision maker ought to digest more information from Pareto optimal solution set, and to balance the factors of economy, environment and uncertainty.(3) This paper presents a new model to solve the DEED problem incorporating uncertainties in the process of power generation. Besides the classic DEED factors, the constraints of both reliability and efficiency are specially considered to restrain the disturbances of uncertainties. Accordingly, the penalty and reserve cost function together with the penalty and reserve emission function are added in the multi-objective function respectively. In order to obtain some quantitative results, the characterizations of the different sources of uncertainty are discussed based on statistical theory, and this optimization problem is numerically solved by IPSO algorithm. Eventually, the simulation results demonstrate that improving the level of reliability will increase the operation costs and emissions of the power system, while increasing the level of efficiency will decrease the operation costs and emissions of the power system. Furthermore, there seems no significant linear correlation among the economic and environmental costs and the proportion of wind power generation under the requirements of reliability and efficiency.(4) Owing to its unpredictability and intermittency, the deterministic models for conventional power system applications are incapable of expressing the uncertainties from basic parameters of wind power. Aiming at these difficulties, this paper presents a review on the historical research works about this theme. The DEED model under uncertainty is further extended. Besides the classic DEED factors, both reliability and effectiveness are specially considered to restrain the disturbances of uncertainties. To obtain some quantitative results, the uncertainty characterizations are discussed based on the scenario-generation technique. The simulation results demonstrate that the uncertainties do affect the electric power dispatching. Moreover, whether or not the uncertainties are included, DEED is always an effective tool to minimize both total electrical energy costs and emissions over a short-term time span.