A Novel Economic Dispatch Method in Active Distribution Grids with Correlated Uncertain Power Injections

The electricity supply chain system consists of power plants, transmission and distribution. Differences in power plant characteristics cause differences in fuel costs and emissions. Inaccuracies in scheduling the plant have an impact on the surge in fuel use. This becomes the basis for the optimization of power plant scheduling. Optimization on the generator side is usually using the economic dispatch model. However, the Economic Dispatch Model does not consider optimization on the transmission network. Optimization on the transmission network is needed because there are losses in the transmission network. Losses will be even greater when the distance between the power plant and the customer is getting further away. So if distance can be minimized, fuel costs can be reduced. Minimizing the distance for shipping goods can use the transportation model, but the transportation model cannot be used for electricity distribution. This is because there are differences between goods and electricity. Therefore, this study proposes the Single Echelon Economic Dispatch (SEED) model. This model is a combination of the economic dispatch model and the transportation model. This model is able to do simultaneous optimization between the generator side and the transmission side. The model is applied to the Mahakam system in East Kalimantan, using all PLN’s power plants. Load consists of two types, namely low load and peak load. As a result, in peak load and low load conditions, the P11 power plant produces the biggest losses and emissions. This is because electricity production in P11 has to go through a longer path compared to other plants. The P11 is also a power plant that requires the highest fuel costs

DRL based low carbon economic dispatch by considering power transmission safety limitations in internet of energy

A low‐carbon economic dispatch model for electricity market with wind power based on improved ant‐lion optimisation algorithm

The Economic Dispatch (ED) is one of the most important optimization problems in power systems the ultimate goal of the ED is to minimize the cost of operations in a power generation. In this paper, the Woodpecker Mating Algorithm (WMA) is used to solve the ED problem considering the nonlinear properties of generators such as valve point effects (VPE), prohibited operating zones (POZ), ramp rate limits, multiple fuel options, and transmission loss. The WMA algorithm is a novel metaheuristic algorithm inspired by the mating behavior of woodpeckers and sound intensity (a physical quantity). The WMA is implemented on six test systems of different operational dimensions and characteristics to show its capacity for solving the ED problem. The results are compared with the latest and most efficient methods introduced in the literature. Proving the efficiency of the WMA to solve the ED problem, simulation results are promising and offer the optimal fuel cost of production.

Look ahead dynamic security-constrained economic dispatch considering frequency stability and smart loads

The state-of-the-art MW-frequency control is performed by two hierarchical mechanisms: economic dispatch (ED) and automatic generation control (AGC). The ED is solved every 5 min identifying the most economic generation dispatch and reserve schedule. AGC is a feedback control system that regulates area control error by sending signals to regulation reserve every 2-6 s. In system with high renewable penetration and associated high net-load variability, the conventional ED-AGC hierarchical model may result in degraded MW-frequency performance and increasing operational cost. In this paper, an AGC dynamic constrained ED model is proposed to provide a more reliable and economical regulation reserve schedule in handling high net load variability. The continuous AGC dynamics is transformed into discrete state-space model, and the fast AGC dynamics are eliminated to reduce the system order. The discretized reduced-order AGC dynamics are incorporated into the ED to optimize the regulation schedule. The proposed model can be applied in a look-ahead mode with very short-term load forecast or in a look-back mode to provide a “perfect dispatch” benchmark based on historical net load data. The 5-bus and 118-bus systems are tested to demonstrate the effectiveness of the proposed model.

In order to reduce the impact of photovoltaic power output uncertainty on the economic operation of power system, this paper studies the problem of controllable output power of photovoltaic power generation system. In grid connected photovoltaic energy storage system, typical photovoltaic power generation capacity curves obtained by statistical analysis, using particle swarm optimization algorithm to optimize the economic model under different power system output control, when the lowest total cost is the optimal selection of the battery capacity. The battery capacity is determined, the photovoltaic power generation pre measurement, using particle swarm optimization algorithm to optimize the system economic operation model, each time the amount of output of photovoltaic power plant is expected to system debugging, the specific numerical output. Combined with the output of photovoltaic power generation, the output power of the battery is calculated by the analysis and calculation unit, and the economic operation of the grid connected photovoltaic energy storage power generation system is realized through the DC/DC control of the battery charging and discharging.

Hydrogen produced without carbon emissions could be a useful fuel as nations look to decarbonize their electricity, transport, and industry sectors. Using the iodine–sulfur (IS) cycle coupled with a nuclear heat source is one method for producing hydrogen without the use of fossil fuels. An economic dispatch model was developed for a nuclear-driven IS system to determine hydrogen sale prices that would make such a system profitable. The system studied is the HTTR-GT/H2, a design for power and hydrogen cogeneration at the Japan Atomic Energy Agency’s High Temperature Engineering Test Reactor. This study focuses on the development of the economic model and the role that input data plays in the final calculated values. Using a historical price duration curve shows that the levelized cost of hydrogen (LCOH) or breakeven sale price of hydrogen would need to be 98.1 JPY/m3 or greater. Synthetic time histories were also used and found the LCOH to be 67.5 JPY/m3. The price duration input was found to have a significant effect on the LCOH. As such, great care should be used in these economic dispatch analyses to select reasonable input assumptions.

The integrated energy system is an important carrier to improve energy utilization efficiency and promote the coordination and complementarity of multiple energy sources. In view of the complex multi-energy flow load demand in the residential integrated energy system (RIES) and insufficient consideration of the subsidy mechanism for user participation in demand response, a solution is proposed. The economic dispatch method of intelligent buildings that takes into account the comprehensive demand response. First of all, a building integrated energy system model of combined cooling, heating and power is constructed. Secondly, according to the user's temperature comfort and electricity price demand response, a flexible load demand model including cooling and heating load reduction and electric load transfer is established, and a comprehensive demand response mechanism based on stepped compensation is established. Then, an economic dispatch model with the goal of maximizing system operating profit is constructed, and the CPLEX optimizer is used to solve it. Finally, a simulation example shows that the building integrated energy system optimization strategy that takes into account the comprehensive demand response can coordinate the resources on both sides of supply and demand, and improve the economic benefits of the system and users.

Conventional dispatch models, which are primarily focused on cost minimization, prove insufficient to address the multidimensional challenges of a Just Energy Transition. In order to address this discrepancy, the present paper puts forth the Economic, Environmental, and Social Dispatch (EEDS) model. The EEDS model is a Mixed-Integer Linear Programming (MILP) Unit Commitment formulation that explicitly incorporates socio-environmental externalities. The methodology implements a two-stage rolling horizon simulator (Day-Ahead and Real-Time) with high temporal resolution (5 min), validated on a polygeneration microgrid integrated with Battery Energy Storage Systems (BESS). The numerical results indicate that the incorporation of quantified social costs substantially modifies the merit order, effectively displacing technologies that are deemed to be socially regressive. Moreover, the analysis demonstrates that demand morphology is a pivotal factor in determining system performance, achieving zero Unserved Energy (ENS) and competitive prices across diverse profiles. Finally, the application of scenario analysis demonstrates that BESS is essential for managing diverse demand morphologies and moderating price volatility across different operational contexts. Therefore, the EEDS framework provides a rigorous quantitative foundation upon which economic efficiency, sustainability, and operational social justice can be balanced.

A non-linear convex cost model for economic dispatch in microgrids

In order to coordinate the impact of the integration of electric vehicles and wind power on the economic dispatch of power systems, a multi-objective dispatch model for the environmental economy of wind farms with PHEVs connected to the grid was constructed. The uncertain factors of wind power generation and load will increase the difficulty of dispatching. The fuzzy theory will be used to realize the fuzzy modelling of the coordinated connection of wind power and electric vehicles. The satisfaction index will be used to transform the multi-objective problems of deterministic environment and economy into single For the objective optimization problem, based on the improvement of the traditional particle swarm optimization algorithm using linear descent search ideas and the particle information sharing method considering boundary constraints, the improved PSO algorithm is used to solve the proposed dynamic environment and economic dispatch model. From the grid operation and vehicle owners from the perspective of demand, the constraints of the system’s rotation reserve and the daily travel of the owner are considered. The comparison and analysis of the simulation of algorithms and calculation examples and multiple scheduling schemes in different scenarios verify the rationality of the model and the superiority of the improved PSO algorithm for solving such dynamic scheduling problems.

Large scale wind power generation complicated with restrictions on the tie line plans may lead to significant wind power curtailment and deep cycling of coal units during the valley load periods. This study proposes a dispatch strategy for interconnected wind‐coal intensive power systems (WCISs). Wind power curtailment and cycling of coal units are included in the economic dispatch analysis of regional systems. Based on the day‐ahead dispatch results, a tie line power plan adjustment strategy is implemented in the event of wind power curtailment or deep cycling occurring in the economic dispatch model, with the objective of reducing such effects. The dispatch strategy is designed based on the distinctive operation characteristics of interconnected WCISs, and dispatch results for regional systems in China show that the proposed strategy is feasible and can improve the overall system operation performance.

Planning, operation and control of active distribution grids by increasing the number of dispersed generators is becoming more important but also more complex. Hence, the importance of controlling the voltage is highlighted in many research papers. Traditionally, in passive distribution networks the voltage rise has been mitigated by network reinforcement. Nowadays, local voltage control, coordinated voltage control and centralized voltage control have been discussed for active networks in research papers. Although all the approaches have been proven to solve the problem of voltage rise in distribution grids, using plenty of sensors to gather huge number of measurement could cause complexity. This paper represents a literature review of different voltage control approaches in active distribution grids and proposes a new procedure to set up a local voltage control law devoted to properly manage the voltage profile (e.g. minimizing losses on MV feeders).

The distributed power generation is an energy development way which can most manifest the multiple advantages such as the energy saving, emission reduction, safety and flexible trait. As a kind of distributed power generation technology of renewable energy, photovoltaic power generation has already transited from supplement energy to alternative energy. Although solar photovoltaic power generation industry develops very quickly in China, actual application cases of substation photovoltaic grid-connected power generation system are few. In this paper, the research of photovoltaic grid-connected power generation system is used in Zhuishan substation in Bengbu Anhui province. The system is the first set of substation photovoltaic-connected grid power generation system in Anhui province. It has being operated for three years safety and steady. The whole application of the system is advanced and groundbreaking in the domestic.