81results about How to "Reduce electricity purchase cost" patented technology

The invention discloses a dual-layer optimization method for power distribution network expansion planning and light storage locating and sizing. The method comprises the steps of building an upper-layer optimization model for active power distribution network expansion planning: determining a target function and constraint conditions of the upper-layer model; building a lower-layer optimization model for light storage capacity configuration: determining a target function and constraint conditions of the lower-layer model; and solving the upper-layer model and the lower-layer model: executing an upper-layer model optimization method, a lower-layer model optimization method and a dual-layer optimization method. According to the method, the built dual-layer optimization models taking a distribution network enterprise and users as subjects and taking calculation of optimal economic cost as a target comprehensively analyze economic influence of light storage system access and power distribution network expansion planning on the distribution network enterprise and the users; a planning model taking annual cost expense as a target function can well assess the economy of a power distribution network; and the light storage system can be reasonably configured, so that the power purchase costs of the users are effectively reduced, the on-spot consumption of photovoltaic energy is increased, and the network loss of a power distribution system can be effectively reduced.

The invention discloses a distribution network expansion planning method considering the optimized operation of a regional integrated energy system. Firstly, a regional integrated energy system modelis established and the internal energy flow relationship is analyzed. Secondly, based on the multi-agent system, a three-layer interactive structure including the main layer, the regional layer and the device layer is built to realize the interaction of different entities on the spatial scale. Then, a bi-level optimization model is established for the distribution network with residential, commercial and industrial regional integrated energy systems. The upper level is used for the expansion planning of distribution network, and the lower level is used for the optimization operation of regional integrated energy systems. Genetic membrane algorithm and sequential quadratic programming are used to solve the upper and lower level models nested nested. Finally, the simulation example shows that the distribution network planning considering the optimal operation of regional integrated energy system can reduce the total cost of planning, improve energy efficiency and new energy consumption rate.

The invention relates to a method for controlling an automatic gain control (AGC) set, in particular to the method for controlling the AGC set based on a generator set regulating performance real-time measurement system and a particle swarm optimization algorithm. The method for controlling the AGC set is under a control performance standard (CPS). After an AGC set allocation strategy is improved by using the method, a regulating target of the set having different regulating performances is more definite. A quick set group is in charge of quick load fluctuating quantity in an area, and the advantages of short response time and high regulating speed rate of the quick set group are fully utilized. A main regulating effect can be quite ideal when a load is steady or fluctuates quickly, so a CPS index of a regional power grid can be stable in an acceptable range and at a power grid frequency, a quite good social benefit is obtained, electricity-purchasing cost is minimized, and an excellent economical benefit is obtained.

The invention discloses a demand side response-based microgrid optimal unit and time-of-use electricity price optimization method, which comprises the following steps: (1) acquiring supply and demandhistorical data of a microgrid, including internal load data of the microgrid, a supply situation of distributed regenerable energy and basic information of all types of energy supply units; (2) analyzing outputs of all energy supply systems by using the historical data so as to analyze a supply and demand situation in the microgrid; (3) setting an optimized target function subjected to distributed optimization; (4) performing optimized solving by using a particle swarm search algorithm and an interior point method. According to the demand side response-based microgrid optimal unit and time-of-use electricity price optimization method disclosed by the invention, the supply situation of the regenerable energy of the microgrid and a demand side response under the excitation of time-of-use electricity price are organically combined, and an optimal unit combination of the microgrid and a time-of-use electricity price strategy are subjected to the distributed optimization through the particle swarm search algorithm and the interior point method, so that the problems of extremely high operation cost of the microgrid and too large lack of internal loads are effectively relieved, and the electricity use demand of a user can be well met.

The invention relates to a charging control method and system for an electric vehicle aggregator. The charging control method comprises the steps of establishing a dual-layer optimization model for electric vehicle aggregator bidding based on the current driving mode; solving the dual-layer optimization problem according to constraint conditions to obtain the optimal solution of the dual-layer optimization problem; determining the charging policy of the electric vehicle aggregator according to the optimal solution; and controlling the electric vehicle aggregator to be charged according to the charging policy. According to the charging control method, the influence of the driving mode on the electric vehicle aggregator in participation in the electricity market trading bidding is taken into full consideration; the actual optimal bidding is realized under the premise of considering the coordination between the electricity purchasing cost of the electric vehicle aggregator and the current market benefit; and the charging policy is determined according to the optimal bidding in order to control the electric vehicle aggregator to be charged at the proper bidding cost so as to lower the electricity purchasing cost of the electric vehicle aggregator consequently.

The invention discloses a series-structure light-storing-type multi-micro-grid economical operation system and a method. The series-structure light-storing-type multi-micro-grid economical operation system comprises a primary system and a control system. The primary system is formed in the mode that two sub-micro-grids are connected in series through a grid-connection and off-grid switch K1, and the primary system comprises a photovoltaic power generation array, a storage battery and local loads. The control system is formed by sub-micro-grid controllers, photovoltaic controllers, energy storing controllers, load controllers and a communication network. According to the series-structure light-storing-type multi-micro-grid economical optimization method, a distributed model prediction control algorithm considering a peak-valley electricity price is adopted, and according to the source load characteristic and the operating characteristic in the multiple micro-grids, a micro-grid prediction model and an optimized objective function are established. The established series-structure light-storing-type multi-micro-grid economical operation system and the method have the important engineering application value in developing researching of planning, design, mode switching and optimizing operation of the light-storing-type multi-micro-grid system.

The invention relates to a charging control method and system of an electric automobile group. The charging control method of the electric automobile group comprises the steps of building a double-layer random dynamic planning model of the electric automobile group for participating in a market bidding strategy; solving the double-layer random dynamic planning model based on a constraint condition to obtain an optimal solution, and determining a charging strategy of the electric automobile group based on the optimal solution; and controlling the charging of the electric automobile group based on the charging strategy. As the upper-layer optimization problem of the double-layer random dynamic planning model corresponds to cost minimization in a charging period of the electric automobile group, and the lower-layer optimization problem corresponds to scheduling of a demand-side resource to realize minimum power generation cost, the true optimal bidding is realized under a precondition of considering coordination of a electricity purchasing cost of the electric automobile group and a minimum power generation cost; and as the charging strategy is determined based on the optimal bidding to schedule a electric automobile group user to adjust a charging behavior and control the charging of the electric automobile group at a suitable bidding cost, the electricity purchasing cost of the electric automobile group is reduced.

The invention discloses a wind power consumption optimization method considering multi-level market linkage, which is characterized by comprising the following steps of: firstly, before the market opening of a spot market, executing wind power fair load, i.e., non-fluctuation basic level section clearing to correct a daily load curve, and taking a clearing result before the market opening as a data information source of the market ahead of day; Then, in the day-ahead market, the market organization members give the wind-fire clearing electric quantity and the electricity price of the current stage according to the cooperative game theory and the corrected daily load curve, and the clearing result of the day-ahead market serves as the data information reference of the day-ahead market; Andfinally, entering the intraday market, and executing the wind-fire clearing electric quantity and the electricity price at the stage through listing transaction. And market clearing results of all stages are summarized, and the clearing results are fed back to members of all stages of the market. The problem that wind power consumption is insufficient is solved, establishment and perfection of clean energy in the spot market are facilitated, and therefore the consumption rate of wind power in a short time is increased, the power purchase cost is reduced, and social welfare is increased.

The invention discloses a direct electricity purchase bilateral trade contract electricity price formulating method based on a leader-follower game. The method adopts a leader-follower game model to study an optimal contract offer decision of a generation company in direct electricity purchase bilateral trade: first, optical planning models of generation companies and big consumers are built respectively, and then a complete leader-follower game model containing two interested parties of a plurality of generation companies and a plurality of big consumers is built. The method provided by the invention provides a basis for contract electricity price formulation for the generation companiesin a bilateral trade process, and also provides a basis for electricity purchase decision for the big consumers under a determined generation company bilateral contract offer, thereby realizing maximum contract electricity-selling profits of the generation companies and minimum electricity purchasing cost of the big consumers under a determined contract electricity price in bilateral trade with participation of the plurality of generation companies and the plurality of big consumers.

The invention provides a clearing method for participation of multi-element small and micro subjects in spot market based on virtual power plant, and solves the risk problem brought by uncertainty ofcompetitors to VPP earnings in a transaction decision game process. The method comprises the steps: firstly, constructing a double-layer clearing model considering electricity price uncertainty and constraint conditions of the double-layer clearing model based on power grid side VPP parameters and information of electric energy buyers and sellers; secondly, solving the double-layer clearing modelbased on constraint conditions of the double-layer clearing model to obtain an optimal bidding result and an optimal income of a day-ahead frequency modulation market of day-ahead energy and duration;and finally, obtaining the bid winning condition, the optimal quotation and the clearing price of each market subject according to the optimal bidding result and the optimal income. According to themethod, through the two-stage double-layer clearing model and the two-stage double-layer constraint condition established by the clearing method, visual benefit analysis and bidding decision of the peak regulation market in which the power grid side energy storage participates in considering the electricity price uncertainty can be simply and conveniently achieved.

The invention belongs to the technical field of the Internet, and particularly discloses a multi-factor electric quantity transaction matching method and device based on a block chain. The method comprises the following steps: enabling an electricity selling node to submit electricity selling information in a period; generating an electricity selling record according to the electricity selling information, and uploading and storing the electricity selling record; enabling an electricity purchasing node to submit electricity purchasing information in a period; generating an electricity purchasing record according to the electricity purchasing information, and uploading and storing the electricity purchasing record; performing electricity selling record pre-matching by adopting a dissimilarity calculation formula according to the electricity purchasing record; enabling an electricity selling user to authorize the electric quantity transaction pre-matching record to complete electric power matching and update the electricity selling record; enabling the electric quantity transaction matching record to take effect, and uploading and storing the electric quantity transaction matching record; and enabling the electricity purchasing user to complete electric quantity transaction transfer according to the electric quantity transaction matching record. The problems of power transmissionwaste caused by a traditional electric quantity transaction matching mode and difficult matching caused by high clean energy selling price are solved; and meanwhile, the problems of high transactioncost, poor information security and mutual trust of transaction subjects caused by centralized management of transaction information of a centralized institution are also solved.

The invention belonging to the energy optimization field of the energy storage system relates to a distributed-extreme-value-search-algorithm-based energy storage system and an energy optimization management method thereof. The method comprises: operating state information of a current energy storage unit and an adjacent energy storage unit are detected; on the basis of the operating state information, whether power generated by a distributed power generating unit meets the need of a load is determined; if so, whether an energy storage system needs to be charged or a distributed power supply provides power for a large grid is determined intelligently based on an economic dispatch requirement; if not, whether the energy storage system needs to be discharged or the load purchases power fromthe large grid is determined intelligently based on an economic dispatch requirement; if the charging or discharging of the energy storage units is selected, a distributed extreme value search algorithm is used for control an execution unit; whether the charge quantities of the energy storage units meet an expected standard is determined; if so, the operation is completed; and if not, the controller is used continuously to carry out optimized controlling. Therefore, the input and output of the energy storage system are controlled in real time; stability of the system is ensured; and the energylosses are reduced effectively.

The invention discloses a different user energy storage configuration evaluation and operation optimization method based on energy storage model selection. The method comprises the steps: building a battery energy storage model selection evaluation model based on an interval analytic hierarchy process based on battery energy storage market indexes, a verification energy storage technology and performance index parameters, and obtaining an energy storage battery through evaluation; selecting an energy storage battery, and establishing an energy storage full-life-cycle configuration model basedon a time-of-use electricity price mechanism, an energy storage battery technology and performance parameters; selecting different user annual average load curves to perform energy storage configuration, and calculating corresponding user energy storage evaluation index parameters; evaluating energy storage configurations of different users based on an analytic hierarchy process; and for users suitable for configuring energy storage, establishing a day-ahead energy storage optimal scheduling model, and optimizing the energy storage charging / discharging power in the day scheduling period basedon the LSTM day-ahead load prediction data. According to the invention, evaluation and analysis can be carried out on energy storage configured for different typical users, guidance is provided for energy storage installation of different users, and the development of user-side energy storage is promoted.

The invention provides a medium and long term electricity purchase planning method capable of considering a three-public-service-related consumption schedule and the electricity purchase cost. The method comprises the steps of 1, building a three-public-service-related consumption schedule constraint model which is capable of meeting the condition that the deviation between the three-public-service-related consumption schedule of each unit and an ideal three-public-service-related consumption schedule is in a given range; 2, building a production run constraint model of each unit; 3, considering different grid purchase prices of different units, building an electricity purchase cost objective function model of the units at a plurality of optimizing months, and calculating the value, meeting the three-public-service-related consumption schedule deviation constraint and the production run constraint, of the electricity purchase cost objective function model, wherein the electricity purchase cost objective function model enables the purchase cost of all units at the optimizing months to be minimum. By using the medium and long term electricity purchase planning method, the problem that the three-public-service-related consumption schedule contradicts with the electricity purchase cost in the medium and long term electricity purchase planning is solved, the electricity purchase plan meets the three-public-service-related consumption schedule requirements, and the electricity purchase cost is reduced as far as possible.

The invention provides a provincial power grid hedging electricity purchase optimization method. The method specifically comprises the steps of S1, acquiring data, wherein the data comprises load prediction data, the inter-provincial tradable electricity quantity, hydroelectricity prediction output, a local unit power generation schedule, an inter-provincial connecting line schedule and the like, S2, carrying out data analysis and processing, and calculating compressible space of a local thermal power unit in the next month, S3, building a provincial power grid hedging electricity purchase optimization model, and S4, designing a solving algorithm of the hedging electricity purchase optimization model. The step S4 further comprises the sub-steps of S4-1, calculating the lowest power generation capacity of the thermal power unit in the current month, and determining the electricity purchase optimization space, S4-2, comparing the inter-provincial transaction electricity price and the thermal power on-grid price with the transmission loss being considered, and carrying out rank ordering, and S4-3, firstly arranging uncontrollable power generation scheduling output and the lowest power generation of the thermal power unit with the insufficient section being undertaken by hydroelectricity, sequentially arranging thermal power and extra-provincial electricity according to a sequence from low to high of the on-grid price if the power is still insufficient, and ensuring the total power generation of various power supplies in the current month to meet an upper limit restriction until a load requirement is satisfied. The electricity purchase optimization method provided by the invention can significantly improve the on-grid proportion of clean power such as wind power and photovoltaic power, and the electricity purchase cost of a power grid company is reduced.

The invention provides an inter-provincial power purchase plan arrangement method taking regard of energy saving and emission reduction. The method comprises steps that I, a multi-target power purchase model comprehensively taking regard of the least total power purchase cost, the least total energy consumption of a thermal power set, the least SO2 emissions and the least CO2 emissions is established; II, single-target power purchase models respectively taking regard of the least total power purchase cost, the least total energy consumption of the thermal power set, the least SO2 emissions andthe least CO2 emissions are established and solved; III, dimensionless processing is carried out based on the four indexes; IV, a weighted value of each index is determined according to actual conditions; and V, the index values after dimensionless processing and the respective weighted value are utilized to establish a target function, a multi-target optimization problem is converted into a single-target optimization problem, the particle swarm optimization algorithm is further utilized for solution, and an inter-provincial power purchase plan taking regard of energy saving and emission reduction is made. The method is advantaged in that for the made inter-provincial power purchase plan, energy consumption of the thermal power set and pollution gas emission are reduced on the condition that the power purchase cost can be reduced.

The invention discloses a unit combination acquiring method considering out-going power transaction, transprovincial or interregional line transaction and security constraint. The method is characterized in that the transaction plan an operation plan of a power company are treated as the background, a mathematical model facing transaction component is created to solve the problem that the economic characteristics of transaction variety and rules are to be reflected in the power transaction; the optimized target function is that the cost of the power company purchasing out-going power transaction and transprovincial or interregional line transaction is minimized; the constraint conditions include security constraint for the power grid operation, physical constraint for unit operation, and transaction component constraint. With the adoption of the method, the power company considering the transaction variety and rules can prepare the transaction plan and the operation plan, so that the decision-making science and effectiveness can be improved; the power purchase strategy and power purchase cost of the power company can be optimized, and as a result, the lean operation level of the power transaction service can be raised.

The invention discloses a multi-wind-field bidding method for electric heating and promoting wind electricity consumption on spot, belonging to the electric power system technology field. Targeting a minimum electric consumption cost of a thermal storage type electric boiler system, the multi-wind-field bidding method uses wind curtailment power prediction data and a quotation chart which are provided by a wind field according a thermal load requirement of the heat storage electric boiler system, adopts a particle swarm to perform optimization and realizes the minimum electric consumption cost of the thermal storage electric boiler system under a multi-wind filed bidding mode. The multi-wind-field bidding method for electric heating and promoting wind electricity consumption on spot can promote the consumption of wind curtailment electric quantity, improves electricity selling incomes, benefits the wind electricity consumption on spot, can improve a utilization rate of power transmission properties of a power grid company in off-peak hours and effectively reduces electricity buying cost of the thermal storage electric boiler. As a result, the multi-wind-field bidding method for electric heating and promoting wind electricity consumption on spot can effectively promote popularization and application of electric heating in heat supplying northern regions of China in winter.

The invention provides a multi-target new energy source planning method and device. The method is applied to the technical field of the new energy source planning. The method comprises the following steps: collecting output data of a typical wind power plant and a photovoltaic power station; for new energy sources in different grid-connecting ways in the region, constructing a multi-target optimization model in the nearby consumption, minimum system network loss and minimum electricity purchasing cost; and determining the new energy source grid-connecting location and installed capacity according to the output data and the multi-target optimization model. The multi-target new energy source planning method and device provided by the invention can effectively improve the generation utilization efficiency of the new energy plant station in the region, and the wind-abandoning and light-abandoning risk is reduced.

The invention relates to an interval optimization-based day-ahead market power purchase optimization method for a power system with wind power. The situation of combined clearing of a day-ahead energymarket and a standby capacity market is comprehensively considered; a multi-objective nonlinear interval optimization model with the wind power is built by taking a minimum total expense and a minimum real-time market power deviation interval as goals in combination with real-time market power deviation intervals; and the multi-objective nonlinear interval optimization model is converted into anoptimistic and pessimistic solution optimization model. An optimal power purchase interval and a standby capacity interval of a thermal power unit in the day-ahead market can be obtained; a referencecan be provided for a power purchase decision; the power purchase cost can be reduced; and wind resources can be reasonably utilized.

The invention discloses a base station with an energy cooperation function and an energy cooperation method. Each base station includes an energy collecting device and a storage battery, wherein the energy collecting device can adopt an appropriate energy collecting mode according to the environment wherein the energy collecting device is located, and stores collected energy in the store battery for use by the base station; the plurality of base stations share the collected energy through connected power carrier lines to fully utilize the collected free energy; in addition, the base stations are also connected to a power grid as a supplement when the collected energy is insufficient. Based on the dynamic electricity price of the power grid, the base stations dynamically determines how muchelectricity is purchased from the power grid and stored in the storage batteries when the electricity price is low, according to factors such as the current storage capacity of the storage batteries,the energy demand, and the energy collection, so that the electricity can be used when the electricity price is high and the collected energy cannot meet the demand of the base stations; the cost ofthe electricity of the base stations purchased from the power grid is minimum, carbon dioxide emission is reduced, the grid load is smoothened, and the consumption cavity of the power grid is improved.

The invention discloses an AC / DC hybrid microgrid optimization method, which comprises the following steps: according to historical data of photovoltaic power generation and load power consumption in a preset historical period, obtaining photovoltaic power generation prediction data and load power consumption prediction data of a day to be predicted through a least square support vector machine; according to the photovoltaic power generation prediction data and the load power consumption prediction data,optimizing and balancing the photovoltaic utilization rate and the comprehensive cost of the AC / DC hybrid microgrid through a comprehensive economic optimization model and a comprehensive cost model of the AC / DC hybrid microgrid, and allowing a multi-objective function to be solved and normalized into a single-objective function; and solving the single objective function by adopting a particle swarm algorithm to obtain photovoltaic, energy storage, power flow controller, power electronic transformer, microgrid and large power grid exchange power dispatching values of the day to be predicted. According to the scheme, the purposes of self-generation and self-use and residual internet access are effectively achieved, the life cycle of the alternating-current and direct-current hybrid micro-grid is prolonged, the cost of purchasing electricity from a large power grid by the micro-grid is reduced, and comprehensive benefit maximization is achieved.

The invention discloses a day-ahead-real-time optimization control method for a power distribution network based on an energy storage reactive power regulation model. The method comprises the following steps: constructing a day-ahead optimization control model based on the minimum daily operation cost of the power distribution network and a real-time optimization control model for hierarchical coordination of the power distribution network and a charging station; the day-ahead optimization control model determines the day-ahead active power of the charging station by taking a charging station power model, a power distribution network power flow equation and the like as constraint conditions and combining with an optimization target with the lowest daily operation cost. And the real-time optimization control model takes a day-ahead optimization result as an operation reference point, and realizes effective power distribution among the power distribution network, the charging station and the electric vehicle through coordination and complementation among multiple layers of optimization models so as to realize real-time optimization control of energy storage reactive power regulation. The technical problem of energy storage reactive power regulation in the power system is solved, the performance difference between the day-ahead optimization model and the real-time optimization model is considered, and the accuracy of the optimization result is improved.

The invention discloses a power distribution network electric energy distributed transaction model based on distributed database support, which is characterized in that electricity purchasing and selling parties send electricity purchasing and selling information through a distributed database network, and an electric energy transaction negotiation market chain code model completes negotiation oftransaction electric quantity and transaction price to form a temporary contract; the network security constraint chain code model performs security check on the temporary contract line power flow andthe node voltage; and the on-chain and off-chain model determines the temporary contract passing the security check as a final contract, and executes a transaction. According to the invention, the market main body is allowed to participate in the power market in a decentralized manner and negotiate the transaction electric quantity and the transaction price, the electricity purchasing cost of themarket main body can be effectively reduced, and the electricity selling income of the market main body is increased. Line power flow blocking and node voltage deviation conditions can be effectivelyjudged, and safe operation of a power distribution network is facilitated. The constructed distributed database capacity expansion architecture can ensure the safety and traceability of all historical data storage while ensuring the computing power of the distributed database.

The invention relates to a system of an optical storage source and a water vapor energy heat pump based on a peak-valley price difference and a grid-connected control method thereof. The system comprises a photovoltaic system, an optical storage operation control module, a battery energy storage system, the water vapor energy heat pump, a DC bus, a low voltage side AC bus, and an AC distribution network; the photovoltaic system and the battery energy storage system are connected with the DC bus after being subjected to DC / DC transformation respectively; the photovoltaic system and the battery energy storage system are connected with the low voltage side AC bus after being subjected to DC / AC transformation respectively; and the water vapor energy heat pump and a residential power load are respectively connected to the low voltage side AC bus. The system of the optical storage source and the water vapor energy heat pump based on the peak-valley price difference provided by the invention develops an operation scheduling strategy of the optical storage source and the water vapor energy heat pump based on the peak-valley price difference, and realizes the purposes of household energy saving and emission reduction and reducing the household electricity purchasing cost to achieve economic optimum.

The utility model relates to a method for analyzing the interests of an electricity seller considering the load forecasting accuracy, which relates to the technical field of analyzing the interests ofthe seller. Under the policy of liberalization of electricity sales, there is competition in the electricity market, earn income, cost containment For e-marketers, the most fundamental is load forecasting, the accuracy of forecasting will affect the purchase cost and income of the electricity sellers, such as the large deviation of load forecasting will bring additional real-time market transaction costs, so constantly adjusting the medium-and long-term contract power through accurate load forecasting is an important means to reduce costs and improve corporate profits. The invention comprisesthe following steps: a power quantity prediction analysis model based on system dynamics is constructed; a profit analysis model of electricity sellers considering load forecasting accuracy is constructed.

The invention discloses a node marginal electricity price calculation method and device based on network loss. The node marginal electricity price calculation method comprises the following steps: optimizing a preset economic dispatching model through a preset weight; constructing a first constraint condition of the optimized preset economic dispatching model, wherein the first constraint condition comprises a node power balance constraint, a generator set output constraint, a direct current power flow relationship constraint and a network transmission capability constraint; establishing a second constraint condition between the power transmission line power flow and the network loss, wherein the second constraint condition meets quadratic term constraints; converting the optimized preseteconomic dispatching model, the first constraint condition and the second constraint condition into a model Lagrange function; and calculating the marginal electricity price of the node according to the model Lagrange function and the original economic dispatch power flow. According to the node marginal electricity price calculation method, the technical problem that the system network loss is increased while the system electricity purchasing cost is reduced because the influence of the system network loss is not considered in the existing node marginal electricity price mechanism is solved.

The invention relates to the technical field of dust recycling systems, in particular to a comprehensive recycling power generating system applicable to purifying dust, dust-removing dust and semi-coke powder. The system comprises a proportioning system body, a combusting system body, an excessive heat power generating system body and a waste gas treatment system body, the proportioning system body mixes the dust-removing dust, the purifying dust and the semi-coke powder according to a ratio to prepare particles of which the particle diameter is smaller than 3 mm, and the particles are delivered to the combusting system; the combusting system fully combusts the particles and generates overheated steam and waste gas, the overheated steam is delivered to the excessive heat power generating system to generate power, and the waste gas is delivered to the waste gas treatment system to be subjected to waste gas treatment and is then exhausted to atmosphere. The dust-removing dust and purifying dust in the producing process of a calcium carbide plant are systematically recycled, the problems of environment pollution, land occupancy and the like are solved, to serve as the basis of boilercombustion utilization, excessive heat is used for generating electricity, the electricity purchase cost is lowered, the market competitiveness is improved, the social benefit and environmental benefit are increased, the waste gas treatment system treats the waste gas, and the pollution is lowered.

The invention discloses an environment-friendly utilization method of a waste power battery of a new energy automobile. The method comprises the following steps of S1, screening waste power batteries,wherein the SOH of each screened waste power battery is not less than 50%; and S2, detecting the waste power batteries in Step S1, and recombining and integrating the waste power batteries meeting adetection standard to obtain a battery pack. The method is good in recycling effect.

The invention discloses an energy-saving control device for a coal-to-electricity user air source heat pump. The energy-saving control device comprises a communication module, a storage module, a calculation module, a microprocessor module, air source heat pump equipment and an interface module; a load aggregator transmits demand response information to the coal-to-electricity user through the communication module; the air source heat pump equipment is inserted into the interface module for communication; the storage module stores information collected in the communication module and a control strategy and related configuration parameters when the device works normally; the microprocessor module is used for controlling the air source heat pump equipment to operate based on the communication information; and based on the collected actual operation state of the air source heat pump equipment, coal-to-electricity user load reduction amount and energy-saving income are calculated.